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  </style:style>
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  </style:style>
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    </style:tab-stops>
   </style:paragraph-properties>
  </style:style>
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  <style:style style:name="Heading_20_2" style:display-name="Heading 2" style:family="paragraph" style:parent-style-name="Heading" style:next-style-name="Text_20_body" style:default-outline-level="2" style:list-style-name="" style:class="text">
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   <style:text-properties style:font-name="Liberation Serif" fo:font-family="&apos;Liberation Serif&apos;" style:font-family-generic="roman" style:font-pitch="variable" fo:font-size="10pt" fo:font-weight="bold" style:font-name-asian="Tahoma" style:font-family-asian="Tahoma" style:font-family-generic-asian="system" style:font-pitch-asian="variable" style:font-size-asian="10pt" style:font-weight-asian="bold" style:font-name-complex="Tahoma" style:font-family-complex="Tahoma" style:font-family-generic-complex="system" style:font-pitch-complex="variable" style:font-size-complex="10pt" style:font-weight-complex="bold"/>
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  <style:style style:name="Quotations" style:family="paragraph" style:parent-style-name="Standard" style:class="html">
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  </style:style>
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   <style:text-properties style:text-underline-style="solid" style:text-underline-width="auto" style:text-underline-color="font-color"/>
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   <style:text-properties fo:font-weight="bold" style:font-weight-asian="bold" style:font-weight-complex="bold"/>
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   <style:text-properties style:font-name="OpenSymbol" fo:font-family="OpenSymbol" style:font-charset="x-symbol" style:font-name-asian="OpenSymbol" style:font-family-asian="OpenSymbol" style:font-charset-asian="x-symbol" style:font-name-complex="OpenSymbol" style:font-family-complex="OpenSymbol" style:font-charset-complex="x-symbol"/>
  </style:style>
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   <style:text-properties fo:font-style="italic" style:font-style-asian="italic" style:font-style-complex="italic"/>
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
    </style:list-level-properties>
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   <text:outline-level-style text:level="5" loext:num-list-format="%5%" style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
    </style:list-level-properties>
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   <text:outline-level-style text:level="6" loext:num-list-format="%6%" style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
    </style:list-level-properties>
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   <text:outline-level-style text:level="7" loext:num-list-format="%7%" style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
    </style:list-level-properties>
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   <text:outline-level-style text:level="8" loext:num-list-format="%8%" style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
    </style:list-level-properties>
   </text:outline-level-style>
   <text:outline-level-style text:level="9" loext:num-list-format="%9%" style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
    </style:list-level-properties>
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   <text:outline-level-style text:level="10" loext:num-list-format="%10%" style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab"/>
    </style:list-level-properties>
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  </text:outline-style>
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
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    </style:list-level-properties>
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
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    </style:list-level-properties>
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab" text:list-tab-stop-position="1in" fo:text-indent="-0.25in" fo:margin-left="1in"/>
    </style:list-level-properties>
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    </style:list-level-properties>
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
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    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
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   <text:list-level-style-number text:level="9" loext:num-list-format="%9%." style:num-suffix="." style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab" text:list-tab-stop-position="2.5in" fo:text-indent="-0.25in" fo:margin-left="2.5in"/>
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   </text:list-level-style-number>
   <text:list-level-style-number text:level="10" loext:num-list-format="%10%." style:num-suffix="." style:num-format="">
    <style:list-level-properties text:list-level-position-and-space-mode="label-alignment">
     <style:list-level-label-alignment text:label-followed-by="listtab" text:list-tab-stop-position="2.75in" fo:text-indent="-0.25in" fo:margin-left="2.75in"/>
    </style:list-level-properties>
   </text:list-level-style-number>
  </text:list-style>
  <text:notes-configuration text:note-class="footnote" style:num-format="1" text:start-value="0" text:footnotes-position="page" text:start-numbering-at="document"/>
  <text:notes-configuration text:note-class="endnote" style:num-format="i" text:start-value="0"/>
  <text:linenumbering-configuration text:number-lines="false" text:offset="0.1965in" style:num-format="1" text:number-position="left" text:increment="5"/>
  <style:default-page-layout>
   <style:page-layout-properties style:writing-mode="lr-tb" style:layout-grid-standard-mode="true"/>
  </style:default-page-layout>
  <loext:theme loext:name="Office Theme">
   <loext:theme-colors loext:name="LibreOffice">
    <loext:color loext:name="dark1" loext:color="#000000"/>
    <loext:color loext:name="light1" loext:color="#ffffff"/>
    <loext:color loext:name="dark2" loext:color="#000000"/>
    <loext:color loext:name="light2" loext:color="#ffffff"/>
    <loext:color loext:name="accent1" loext:color="#18a303"/>
    <loext:color loext:name="accent2" loext:color="#0369a3"/>
    <loext:color loext:name="accent3" loext:color="#a33e03"/>
    <loext:color loext:name="accent4" loext:color="#8e03a3"/>
    <loext:color loext:name="accent5" loext:color="#c99c00"/>
    <loext:color loext:name="accent6" loext:color="#c9211e"/>
    <loext:color loext:name="hyperlink" loext:color="#0000ee"/>
    <loext:color loext:name="followed-hyperlink" loext:color="#551a8b"/>
   </loext:theme-colors>
  </loext:theme>
 </office:styles>
 <office:automatic-styles>
  <style:style style:name="P1" style:family="paragraph" style:parent-style-name="normal">
   <style:paragraph-properties fo:margin-top="0in" fo:margin-bottom="1in" style:contextual-spacing="false" fo:text-align="center" style:justify-single-word="false"/>
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  <style:style style:name="P2" style:family="paragraph" style:parent-style-name="normal" style:master-page-name="Standard">
   <style:paragraph-properties fo:text-align="center" style:justify-single-word="false" style:page-number="1"/>
   <style:text-properties fo:font-size="16pt" fo:font-weight="bold" style:font-size-asian="16pt" style:font-weight-asian="bold" style:font-size-complex="16pt" style:font-weight-complex="bold"/>
  </style:style>
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   <style:paragraph-properties fo:text-align="center" style:justify-single-word="false"/>
  </style:style>
  <style:style style:name="P4" style:family="paragraph" style:parent-style-name="normal">
   <style:paragraph-properties fo:text-align="center" style:justify-single-word="false"/>
   <style:text-properties officeooo:paragraph-rsid="008a4c4e"/>
  </style:style>
  <style:style style:name="P5" style:family="paragraph" style:parent-style-name="normal">
   <style:text-properties fo:font-weight="bold" style:font-weight-asian="bold" style:font-weight-complex="bold"/>
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  <style:style style:name="P6" style:family="paragraph" style:parent-style-name="normal">
   <style:paragraph-properties fo:margin-top="0in" fo:margin-bottom="0.0835in" style:contextual-spacing="false"/>
  </style:style>
  <style:style style:name="P7" style:family="paragraph" style:parent-style-name="normal">
   <style:paragraph-properties fo:margin-left="1in" fo:margin-right="0in" fo:margin-top="0in" fo:margin-bottom="0.0835in" style:contextual-spacing="false" fo:text-indent="-1in" style:auto-text-indent="false"/>
   <style:text-properties officeooo:rsid="00a988e1" officeooo:paragraph-rsid="00a988e1"/>
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   <style:text-properties officeooo:rsid="009e8c3a" officeooo:paragraph-rsid="009e8c3a"/>
  </style:style>
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   <style:text-properties officeooo:paragraph-rsid="009e8c3a"/>
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   <style:text-properties officeooo:rsid="0068347a" officeooo:paragraph-rsid="0068347a"/>
  </style:style>
  <style:style style:name="P13" style:family="paragraph" style:parent-style-name="normal">
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  </style:style>
  <style:style style:name="P15" style:family="paragraph" style:parent-style-name="normal">
   <style:text-properties style:text-underline-style="none" fo:font-weight="bold" officeooo:rsid="006e97b7" officeooo:paragraph-rsid="006e97b7" style:font-weight-asian="bold" style:font-weight-complex="bold"/>
  </style:style>
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   <style:text-properties fo:font-weight="bold" officeooo:paragraph-rsid="00487707" style:font-weight-asian="bold" style:font-weight-complex="bold"/>
  </style:style>
  <style:style style:name="P17" style:family="paragraph" style:parent-style-name="normal">
   <style:text-properties officeooo:rsid="006ce31d"/>
  </style:style>
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   <style:text-properties officeooo:paragraph-rsid="00ac6ba7"/>
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   <style:text-properties officeooo:paragraph-rsid="00a67db4"/>
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   <style:text-properties officeooo:paragraph-rsid="009c64a0"/>
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   <text:p text:style-name="P2">MATTEO RIONDATO</text:p>
   <text:p text:style-name="P3">Curriculum vitae</text:p>
   <text:p text:style-name="P3"/>
   <text:p text:style-name="P4">Science Center, <text:span text:style-name="T1">Room C214</text:span></text:p>
   <text:p text:style-name="P4">25 East Drive</text:p>
   <text:p text:style-name="P4">Amherst, MA 01002, <text:span text:style-name="T2">USA</text:span></text:p>
   <text:p text:style-name="P3">rionda@acm.org</text:p>
   <text:p text:style-name="P3">http<text:span text:style-name="T3">s</text:span>://matteo.rionda.to</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">EDUCATION</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P6">Ph.D.<text:tab/><text:tab/><text:tab/><text:tab/>Computer Science, Brown University, 2014</text:p>
   <text:p text:style-name="P6">M.Sc.<text:tab/><text:tab/><text:tab/><text:tab/>Computer Science, Brown University, 2010</text:p>
   <text:p text:style-name="P6">M.Sc. (Laurea Specialistica)<text:tab/>Computer Engineering, University of Padua (Italy), 2009</text:p>
   <text:p text:style-name="normal">B.Sc. (Laurea)<text:tab/><text:tab/><text:tab/>Information Engineering, University of Padua (Italy), 2007</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">ACADEMIC APPOINTMENTS</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P7">2024<text:span text:style-name="T4">–<text:tab/></text:span>Inaugural Director, Data Science Initiative, Amherst College</text:p>
   <text:p text:style-name="P8">2023–<text:tab/>Associate Professor, Department of Computer Science, Amherst College</text:p>
   <text:p text:style-name="P9">201<text:span text:style-name="T5">6</text:span>–<text:tab/><text:span text:style-name="T6">Visiting</text:span> <text:span text:style-name="T5">Faculty (various titles)</text:span>, Department of Computer Science, Brown University</text:p>
   <text:p text:style-name="P10">2019–<text:span text:style-name="T4">2023</text:span><text:tab/>Assistant Professor, Department of Computer Science, Amherst College</text:p>
   <text:p text:style-name="P10">2015<text:tab/>Postdoctoral Research Associate, Department of Computer Science, Brown University</text:p>
   <text:p text:style-name="P11">2014–15<text:tab/>Postdoctoral Researcher, Department of Computer Science, Stanford University</text:p>
   <text:p text:style-name="P5"/>
   <text:p text:style-name="P5"/>
   <text:p text:style-name="P5">INDUSTRY POSITIONS</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P6">2015–<text:span text:style-name="T7">18</text:span><text:tab/>Research Scientist, Labs, Two Sigma Investments LP</text:p>
   <text:p text:style-name="P11">2013<text:tab/>Summer Intern Research Scientist, Web Mining Group, Yahoo Research Barcelona</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">PUBLICATIONS</text:p>
   <text:p text:style-name="normal">Authors in alphabetical order unless marked otherwise (*)</text:p>
   <text:p text:style-name="P12"><text:soft-page-break/>All publications are available from http<text:span text:style-name="T8">s</text:span>://matteo.rionda.to/pubs.php</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P13">Edited Proceedings</text:p>
   <text:p text:style-name="P13"/>
   <text:p text:style-name="P14"><text:span text:style-name="T9">2</text:span><text:span text:style-name="T10">024<text:tab/><text:tab/></text:span>Shashi Shekhar, Vagelis Papalexakis, Jing Gao, Zhe Jiang, <text:span text:style-name="T9">and </text:span><text:span text:style-name="T11">M. Riondato</text:span><text:span text:style-name="T10">. <text:tab/><text:tab/></text:span><text:span text:style-name="T12">Proceedings of the 202</text:span><text:span text:style-name="T13">4</text:span><text:span text:style-name="T12"> SIAM International Conference on Data Mining (SDM)</text:span><text:span text:style-name="T14">, <text:tab/><text:tab/>Society for Industrial and Applied Mathematics</text:span></text:p>
   <text:p text:style-name="P14"><text:span text:style-name="T9">2022<text:tab/><text:tab/></text:span>A. Banerjee, <text:span text:style-name="T15">Z.-H.</text:span> Zhou, E. E. Papalexakis, <text:span text:style-name="T15">and </text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">.</text:span> <text:span text:style-name="T18">Proceedings of the <text:tab/><text:tab/>2022 SIAM International Conference on Data Mining (SDM)</text:span><text:span text:style-name="T19">, Society for <text:tab/><text:tab/><text:tab/>Industrial and Applied Mathematics</text:span></text:p>
   <text:p text:style-name="P15"/>
   <text:p text:style-name="P16">Journal Articles</text:p>
   <text:p text:style-name="P17"/>
   <text:p text:style-name="P18"><text:span text:style-name="T20">2024</text:span><text:span text:style-name="T21"><text:tab/></text:span><text:span text:style-name="T22">* G. Preti, G. De Francisci Morales, and </text:span><text:span text:style-name="T23">M. Riondato</text:span><text:span text:style-name="T22">. Impossibility result for Markov chain Monte Carlo sampling from microcanonical bipartite graph ensembles. </text:span><text:span text:style-name="T24">Physical Review E</text:span><text:span text:style-name="T25">, </text:span><text:span text:style-name="T26">109(5):L053301</text:span></text:p>
   <text:p text:style-name="P19"><text:span text:style-name="T27">202</text:span><text:span text:style-name="T28">4</text:span><text:span text:style-name="T22"><text:tab/>* G. Preti, G. De Francisci Morales, and </text:span><text:span text:style-name="T23">M. Riondato</text:span><text:span text:style-name="T22">. </text:span><text:span text:style-name="T29">A</text:span><text:span text:style-name="T30">lice</text:span><text:span text:style-name="T22"> and the Caterpillar: A More Descriptive Null Model for Assessing Data Mining Results.</text:span><text:span text:style-name="T31"> </text:span><text:span text:style-name="T32">Knowledge and Information Systems,</text:span><text:span text:style-name="T33"> </text:span><text:span text:style-name="T34">66(3):1917</text:span><text:span text:style-name="T35">–</text:span><text:span text:style-name="T34">1954</text:span><text:span text:style-name="T33">. </text:span><text:span text:style-name="T36">Invited article to the special issue of the best papers from </text:span><text:span text:style-name="T37">ICDM 2022</text:span></text:p>
   <text:p text:style-name="P20"><text:span text:style-name="T38">2023<text:tab/>* M. Abuissa, A. Lee, </text:span><text:span text:style-name="T39">M. Riondato</text:span><text:span text:style-name="T40">. </text:span><text:span text:style-name="T41">ROhAN</text:span><text:span text:style-name="T40">: Row-order Agnostic Null Models for Statistically-sound Knowledge Discovery. </text:span><text:span text:style-name="T42">Data Mining and Knowledge Discovery</text:span><text:span text:style-name="T43">, </text:span><text:span text:style-name="T44">37(4):1692–1718</text:span></text:p>
   <text:p text:style-name="P21"><text:span text:style-name="T45">2023</text:span><text:tab/><text:span text:style-name="T46">* </text:span><text:span text:style-name="T47">G. Preti, G. De Francisci Morales</text:span><text:span text:style-name="T46">, </text:span><text:span text:style-name="T48">and </text:span><text:span text:style-name="T49">M. Riondato</text:span><text:span text:style-name="T50">. </text:span><text:span text:style-name="T51">MaNIACS</text:span><text:span text:style-name="T52">: Approximate Mining of Frequent Subgraph Patterns through Sampling. </text:span><text:span text:style-name="T53">ACM Transactions on Intelligent Systems </text:span><text:span text:style-name="T54">and Technology</text:span><text:span text:style-name="T55">, </text:span><text:span text:style-name="T56">14(3):54:1</text:span><text:span text:style-name="T57">–</text:span><text:span text:style-name="T58">54</text:span><text:span text:style-name="T56">:29</text:span></text:p>
   <text:p text:style-name="P22"><text:span text:style-name="T59">2023</text:span><text:span text:style-name="T46"><text:tab/>* C. Cousins, C. Wohlgemuth, </text:span><text:span text:style-name="T48">and </text:span><text:span text:style-name="T49">M. Riondato</text:span><text:span text:style-name="T50">. </text:span><text:span text:style-name="T60">Bavarian</text:span><text:span text:style-name="T50">: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages. </text:span><text:span text:style-name="T61">ACM Transactions on Knowledge Discovery from Data</text:span><text:span text:style-name="T62">, </text:span><text:span text:style-name="T63">17(6):78:1</text:span><text:span text:style-name="T57">–</text:span><text:span text:style-name="T63">78:47</text:span></text:p>
   <text:p text:style-name="P22"><text:span text:style-name="T64">2022</text:span><text:span text:style-name="T65"><text:tab/></text:span><text:span text:style-name="T66">S. Haddadan, C. Menghini, </text:span><text:span text:style-name="T67">M. Riondato</text:span><text:span text:style-name="T68">, and E. Upfal. </text:span><text:span text:style-name="T69">Reducing Polarization and Increasing Diverse Navigability in Graph by Inserting Edges and Swapping Edge Weights. </text:span><text:span text:style-name="T70">Data Mining and Knowledge Discovery</text:span><text:span text:style-name="T71">. Special Issue on </text:span><text:span text:style-name="T72">Bias and </text:span><text:span text:style-name="T71">Fairness, </text:span><text:span text:style-name="T73">36(6):2334</text:span><text:span text:style-name="T74">–</text:span><text:span text:style-name="T73">2378</text:span></text:p>
   <text:p text:style-name="P23"><text:span text:style-name="T75">2022</text:span><text:span text:style-name="T76"><text:tab/>* S. Jenkins, S. Walzer-Goldfeld, and </text:span><text:span text:style-name="T77">M. Riondato</text:span><text:span text:style-name="T78">. SPEck: Mining Statistically-significant Sequential Patterns Efficiently with Exact Sampling. </text:span><text:span text:style-name="T79">Data Mining and Knowledge Discovery</text:span><text:span text:style-name="T80">, </text:span><text:span text:style-name="T81">36</text:span><text:span text:style-name="T82">(4)</text:span><text:span text:style-name="T83">:</text:span><text:span text:style-name="T84">1575</text:span><text:span text:style-name="T85">–</text:span><text:span text:style-name="T84">1599</text:span></text:p>
   <text:p text:style-name="P24"><text:span text:style-name="T86">2022</text:span><text:tab/><text:span text:style-name="T87">* L. Pellegrina, C. Cousins, F. Vandin, and </text:span><text:span text:style-name="T88">M. Riondato</text:span><text:span text:style-name="T89">. McRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. </text:span><text:span text:style-name="T61">ACM Transactions on Knowledge Discovery from Data</text:span><text:span text:style-name="T90">, </text:span><text:span text:style-name="T91">16(6):124:1</text:span><text:span text:style-name="T85">–</text:span><text:span text:style-name="T91">124:29</text:span></text:p>
   <text:p text:style-name="P25"><text:soft-page-break/><text:span text:style-name="T92">2021</text:span><text:tab/><text:span text:style-name="T46">* </text:span>M. A. U. Nasir, C. Aslay, G. De Francisci Morales, <text:span text:style-name="T48">and </text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">. </text:span><text:span text:style-name="T93">TipTap</text:span><text:span text:style-name="T17">: Approximate Mining of Frequent k-Subgraph Patterns in Evolving Graphs. </text:span><text:span text:style-name="T53">ACM Transactions on Knowledge Discovery from Data</text:span><text:span text:style-name="T55">, </text:span><text:span text:style-name="T94">15(3):48:1</text:span><text:span text:style-name="T85">–</text:span><text:span text:style-name="T94">48:35</text:span></text:p>
   <text:p text:style-name="P26"><text:span text:style-name="T95">2020<text:tab/></text:span><text:span text:style-name="T96">M. Riondato</text:span><text:span text:style-name="T97"> and F. Vandin. MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. </text:span><text:span text:style-name="T98">ACM Transactions on Knowledge Discovery from Data</text:span><text:span text:style-name="T99">, </text:span><text:span text:style-name="T100">14(5):56:1-56:30.</text:span><text:span text:style-name="T99"> </text:span><text:span text:style-name="T101">Invited article to the special issue of the best papers from KDD 2018</text:span></text:p>
   <text:p text:style-name="P27"><text:span text:style-name="T102">2020</text:span><text:tab/>* S. Servan-Schreiber, <text:span text:style-name="T103">M. Riondato</text:span><text:span text:style-name="T17">,</text:span> and E. Zgraggen. ProSecCo: Progressive Sequence Mining with Convergence Guarantees, <text:span text:style-name="T104">Knowledge and Information Systems</text:span><text:span text:style-name="T105">, </text:span><text:span text:style-name="T106">62(4):1313–1340.</text:span><text:span text:style-name="T105"> </text:span><text:span text:style-name="T107">Invited article to the special issue on the best papers from </text:span><text:span text:style-name="T108">ICDM </text:span><text:span text:style-name="T107">2018</text:span></text:p>
   <text:p text:style-name="P28"><text:span text:style-name="T109">2019<text:tab/>C. Cousins and </text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">. </text:span><text:span text:style-name="T93">CaDET</text:span><text:span text:style-name="T17">: Interpretable Parametric Conditional Density Estimation with Decision Trees and Forests. </text:span><text:span text:style-name="T53">Machine Learning</text:span><text:span text:style-name="T55">, </text:span><text:span text:style-name="T85">108:161</text:span><text:span text:style-name="T110">3</text:span><text:span text:style-name="T85">–1634</text:span></text:p>
   <text:p text:style-name="P10">2018<text:tab/><text:span text:style-name="T103">M. Riondato </text:span>and E. Upfal. ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. <text:span text:style-name="T111">ACM Transactions on Knowledge Discovery from Data</text:span>, 12(5):61:1–61:38</text:p>
   <text:p text:style-name="P29">2017<text:tab/>L. De Stefani, A. Epasto, <text:span text:style-name="T16">M. Riondato</text:span>, and E. Upfal. TRI<text:span text:style-name="T112">È</text:span>ST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size. <text:span text:style-name="T111">ACM Transactions on Knowledge Discovery from Data</text:span>, 11(4):43:1–43:50. <text:span text:style-name="T103">Invited article to the special issue on the best papers from KDD 2016</text:span></text:p>
   <text:p text:style-name="P10">2017<text:span text:style-name="T113"><text:tab/>* </text:span><text:span text:style-name="T16">M. Riondato</text:span>, D. García-Soriano, and F. Bonchi. Graph Summarization with Quality Guarantees. <text:span text:style-name="T114">Data Mining and Knowledge Discovery</text:span>, 31(2):314–349</text:p>
   <text:p text:style-name="P10">2015<text:tab/>* <text:span text:style-name="T16">M. Riondato</text:span> and E. M. Kornaropoulos. Fast Approximation of Betweenness Centrality through Sampling. <text:span text:style-name="T114">Data Mining and Knowledge Discovery</text:span>, 30(2):438–475</text:p>
   <text:p text:style-name="P10">2014<text:tab/><text:span text:style-name="T16">M. Riondato</text:span> and E. Upfal. Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees. <text:span text:style-name="T114">ACM Transactions on Knowledge Discovery from Data</text:span>, 8(4):20:1–20:32</text:p>
   <text:p text:style-name="P30">2010<text:tab/>A. Pietracaprina, <text:span text:style-name="T16">M. Riondato</text:span>, E. Upfal, and F. Vandin. Mining Top-<text:span text:style-name="T115">K</text:span> Frequent Itemsets through Progressive Sampling. <text:span text:style-name="T114">Data Mining and Knowledge Discovery,</text:span> 21(2):310–326. <text:span text:style-name="T116">I</text:span><text:span text:style-name="T103">nvited article to the special issue on the best papers from </text:span><text:span text:style-name="T117">ECML PKDD 2010</text:span></text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">Conference Proceedings</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P31"><text:span text:style-name="T118">2</text:span><text:span text:style-name="T119">024<text:tab/></text:span><text:span text:style-name="Emphasis"><text:span text:style-name="T55">Daniel Flores-Garcia</text:span></text:span><text:span text:style-name="T17">, Hugo Flores Garcia, and </text:span><text:span text:style-name="T16">Matteo Riondato</text:span><text:span text:style-name="T17">. </text:span><text:span text:style-name="Emphasis"><text:span text:style-name="T55">ClaveNet: Generating Afro-Cuban Drum Patterns through Data Augmentation.</text:span></text:span><text:span text:style-name="T17"> </text:span><text:span text:style-name="T53">AM ‘24: Proceedings of the 19th International Audio Mostly Conference: Explorations in </text:span><text:soft-page-break/><text:span text:style-name="T53">Sonic Cultures</text:span><text:span text:style-name="T17">, </text:span><text:span text:style-name="T119">pp. </text:span><text:span text:style-name="T17">355–361.</text:span></text:p>
   <text:p text:style-name="P32"><text:span text:style-name="T118">2023</text:span><text:span text:style-name="T17"><text:tab/></text:span><text:span text:style-name="T120">M. Riondato</text:span><text:span text:style-name="T121">. Statistically-sound Knowledge Discovery from Data: </text:span><text:span text:style-name="T17">Challenges and Directions</text:span><text:span text:style-name="T121">. </text:span><text:span text:style-name="T122">Proceedings of the </text:span><text:span text:style-name="T53">5th</text:span><text:span text:style-name="T122"> </text:span><text:span text:style-name="T53">IEEE Conference on Cognitive Machine Intelligent</text:span><text:span text:style-name="T55"> </text:span><text:span text:style-name="T123">(CogMI)</text:span><text:span text:style-name="T55">, </text:span><text:span text:style-name="T123">pp. 97</text:span><text:span text:style-name="T124">–</text:span><text:span text:style-name="T123">102</text:span><text:span text:style-name="T55">. </text:span><text:span text:style-name="T125">Invited </text:span><text:span text:style-name="T126">P</text:span><text:span text:style-name="T125">aper</text:span></text:p>
   <text:p text:style-name="P33"><text:span text:style-name="T127">2023</text:span><text:span text:style-name="T17"><text:tab/></text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">. Statistically-sound Knowledge Discovery from Data. </text:span><text:span text:style-name="T53">Proceedings of the 2023 SIAM International Conference on Data Mining</text:span><text:span text:style-name="T55"> </text:span><text:span text:style-name="T123">(SDM)</text:span><text:span text:style-name="T55">, </text:span><text:span text:style-name="T128">pp. 949</text:span><text:span text:style-name="T124">–</text:span><text:span text:style-name="T128">952. </text:span><text:span text:style-name="T129">Blue-sky Track Best Paper Runner-up</text:span></text:p>
   <text:p text:style-name="P34"><text:span text:style-name="T130">2</text:span><text:span text:style-name="T17">022<text:tab/>* G. Preti, G. De Francisci Morales, and </text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">. </text:span><text:span text:style-name="T93">A</text:span><text:span text:style-name="T30">lice</text:span><text:span text:style-name="T17"> and the Caterpillar: A More Descriptive Null Model for Assessing Data Mining Results.</text:span><text:span text:style-name="T53"> Proceedings of the 22</text:span><text:span text:style-name="T131">nd</text:span><text:span text:style-name="T53"> IEEE International Conference on Data Mining</text:span><text:span text:style-name="T55"> (ICDM),</text:span><text:span text:style-name="T53"> </text:span><text:span text:style-name="T132">pp. 418</text:span><text:span text:style-name="T124">–</text:span><text:span text:style-name="T132">427</text:span></text:p>
   <text:p text:style-name="P35"><text:span text:style-name="T130">2</text:span><text:span text:style-name="T133">022<text:tab/></text:span><text:span text:style-name="T50">* </text:span><text:span text:style-name="T133">A. Lee, S. Walzer-Goldfeld, S. Zablah, and </text:span><text:span text:style-name="T134">M. Riondato</text:span><text:span text:style-name="T133">. A Scalable Algorithm for Balanced Sampling </text:span><text:span text:style-name="T135">(Student Abstract)</text:span><text:span text:style-name="T133">. </text:span><text:span text:style-name="T136">Proceedings of the AAAI Conference on Artificial Intelligence </text:span><text:span text:style-name="T137">(AAAI)</text:span><text:span text:style-name="T17">, </text:span><text:span text:style-name="T55">36</text:span><text:span text:style-name="T17">(11), </text:span><text:span text:style-name="T135">pp. </text:span><text:span text:style-name="T17">12991</text:span><text:span text:style-name="T138">–</text:span><text:span text:style-name="T17">12992</text:span></text:p>
   <text:p text:style-name="P36"><text:span text:style-name="T139">2021</text:span><text:span text:style-name="T46"><text:tab/>* </text:span><text:span text:style-name="T47">G. Preti, G. De Francisci Morales</text:span><text:span text:style-name="T46">, </text:span><text:span text:style-name="T48">and </text:span><text:span text:style-name="T49">M. Riondato</text:span><text:span text:style-name="T50">. </text:span><text:span text:style-name="T51">MaNIACS</text:span><text:span text:style-name="T52">: Approximate Mining of Frequent Subgraph Patterns through Sampling.</text:span><text:span text:style-name="T50"> </text:span><text:span text:style-name="T140">Proceedings of the 2</text:span><text:span text:style-name="T141">7</text:span><text:span text:style-name="T142">th</text:span><text:span text:style-name="T140"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span><text:span text:style-name="T143">(KDD), </text:span><text:span text:style-name="T138">pp. 1348–1358</text:span></text:p>
   <text:p text:style-name="P37"><text:span text:style-name="T139">2021</text:span><text:tab/>* C. Cousins, C. Wohlgemuth, <text:span text:style-name="T48">and </text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">. </text:span><text:span text:style-name="T93">Bavarian</text:span><text:span text:style-name="T17">: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages. </text:span><text:span text:style-name="T140">Proceedings of the 2</text:span><text:span text:style-name="T141">7</text:span><text:span text:style-name="T142">th</text:span><text:span text:style-name="T140"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span><text:span text:style-name="T143">(KDD), </text:span><text:span text:style-name="T138">pp. 196–206</text:span></text:p>
   <text:p text:style-name="P38"><text:span text:style-name="T144">2021</text:span><text:tab/>S. Haddadan, C. Menghini, <text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">, and E. Upfal. </text:span><text:span text:style-name="T93">RePBubLik</text:span><text:span text:style-name="T17">: Reducing the Polarized Bubble Radius with Link Insertions. </text:span><text:span text:style-name="T53">Proceedings of the 14</text:span><text:span text:style-name="T131">th</text:span><text:span text:style-name="T53"> ACM International Conference on Web Search and Data Mining </text:span><text:span text:style-name="T55">(WSDM), </text:span><text:span text:style-name="T145">pp. 139–147. </text:span><text:span text:style-name="T146">Best Paper Award </text:span><text:span text:style-name="T147">Honorable Mention</text:span></text:p>
   <text:p text:style-name="P39">2020<text:tab/>C. Cousins <text:span text:style-name="T48">and</text:span> <text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">. Sharp uniform convergence bounds through empirical centralization. </text:span><text:span text:style-name="T53">Proceedings of the 34</text:span><text:span text:style-name="T131">th</text:span><text:span text:style-name="T53"> Conference of Neural Information Processing Systems </text:span><text:span text:style-name="T55">(NeurIPS), </text:span><text:span text:style-name="T148">pp. 15123–15</text:span><text:span text:style-name="T149">1</text:span><text:span text:style-name="T148">32</text:span></text:p>
   <text:p text:style-name="P40"><text:span text:style-name="T87">2020<text:tab/>* L. Pellegrina, C. Cousins, F. Vandin, and </text:span><text:span text:style-name="T88">M. Riondato</text:span><text:span text:style-name="T89">. McRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. </text:span><text:span text:style-name="T140">Proceedings of the 2</text:span><text:span text:style-name="T150">6</text:span><text:span text:style-name="T142">th</text:span><text:span text:style-name="T140"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span><text:span text:style-name="T143">(KDD), </text:span><text:span text:style-name="T151">pp</text:span><text:span text:style-name="T89">. </text:span><text:span text:style-name="T151">2165–2174</text:span></text:p>
   <text:p text:style-name="P40"><text:span text:style-name="T152">2019<text:tab/>L. Pellegrina, </text:span><text:span text:style-name="T153">M. Riondato</text:span><text:span text:style-name="T143">, and F. Vandin. </text:span><text:span text:style-name="T154">SPuManTE</text:span><text:span text:style-name="T143">: Significant Pattern Mining with </text:span><text:span text:style-name="T155">Unconditional</text:span><text:span text:style-name="T143"> Testing. </text:span><text:span text:style-name="T140">Proceedings of the 25</text:span><text:span text:style-name="T142">th</text:span><text:span text:style-name="T140"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span><text:span text:style-name="T143">(KDD), </text:span><text:span text:style-name="T156">pp. </text:span><text:span text:style-name="T17">1528–1538</text:span></text:p>
   <text:p text:style-name="P40"><text:span text:style-name="T156">2019</text:span><text:span text:style-name="T143"><text:tab/>L. Pellegrina, </text:span><text:span text:style-name="T153">M. Riondato</text:span><text:span text:style-name="T143">, and F. Vandin. </text:span><text:span text:style-name="T157">Hypothesis testing and statistically-sound pattern mining.</text:span><text:span text:style-name="T143"> </text:span><text:span text:style-name="T140">Proceedings of the 25</text:span><text:span text:style-name="T142">th</text:span><text:span text:style-name="T140"> ACM SIGKDD International </text:span><text:soft-page-break/><text:span text:style-name="T140">Conference on Knowledge Discovery and Data Mining </text:span><text:span text:style-name="T143">(KDD), </text:span><text:span text:style-name="T156">pp. 3215–3216</text:span></text:p>
   <text:p text:style-name="P41">2018<text:tab/>* S. Servan-Schreiber, <text:span text:style-name="T103">M. Riondato</text:span><text:span text:style-name="T17">,</text:span> and E. Zgraggen. ProSecCo: Progressive Sequence Mining with Convergence Guarantees. <text:span text:style-name="T114">Proceedings of the 18</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> IEEE International Conference on Data Mining</text:span> (ICDM), <text:span text:style-name="T159">pp. </text:span><text:span text:style-name="T160">417–426.</text:span> <text:span text:style-name="T16">Best Student Paper Award runner-up</text:span></text:p>
   <text:p text:style-name="P10">2018<text:tab/><text:span text:style-name="T103">M. Riondato</text:span> and F. Vandin. MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. <text:span text:style-name="T111">Proceedings of the 24</text:span><text:span text:style-name="T161">th</text:span><text:span text:style-name="T111"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span>(KDD), pp. 2130–2139</text:p>
   <text:p text:style-name="P10">2016<text:tab/>L. De Stefani, A. Epasto, <text:span text:style-name="T16">M. Riondato</text:span>, and E. Upfal. TRI<text:span text:style-name="T112">È</text:span>ST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size. <text:span text:style-name="T114">Proceedings of the 22</text:span><text:span text:style-name="T158">nd</text:span><text:span text:style-name="T114"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span>(KDD), pp. 825–834.<text:span text:style-name="T16"> Best Student Paper Award (Research Track)</text:span></text:p>
   <text:p text:style-name="P10">2016<text:tab/><text:span text:style-name="T16">M. Riondato</text:span> and E. Upfal. ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. <text:span text:style-name="T114">Proceedings of the 22</text:span><text:span text:style-name="T158">nd</text:span><text:span text:style-name="T114"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span>(KDD), pp. 1145–1154</text:p>
   <text:p text:style-name="P10">2016<text:tab/>F. Bonchi, G. De Francisci Morales, <text:span text:style-name="T48">and </text:span><text:span text:style-name="T16">M. Riondato</text:span>, Centrality Measures on Big Graphs: Exact, Approximated, and Distributed Algorithms. <text:span text:style-name="T114">Proceedings of the 25</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> International World Wide Web Conference </text:span>(WWW), Companion Volume, pp. 1017–1020</text:p>
   <text:p text:style-name="P10">2016<text:tab/>A. Mahmoody, <text:span text:style-name="T16">M. Riondato</text:span>, and E. Upfal. Wiggins: Detecting Valuable Information in Dynamic Networks with Limited Resources. <text:span text:style-name="T114">Proceedings of the 9</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> ACM International Conference on Web Search and Data Mining</text:span> (WSDM), pp. 677–686</text:p>
   <text:p text:style-name="P10">2015<text:tab/><text:span text:style-name="T16">M. Riondato</text:span> and E. Upfal. Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages. <text:span text:style-name="T114">Proceedings of the 21</text:span><text:span text:style-name="T158">st</text:span><text:span text:style-name="T114"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span>(KDD), pp. 1005–1014</text:p>
   <text:p text:style-name="P10">2015<text:tab/><text:span text:style-name="T16">M. Riondato</text:span> and E. Upfal. VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms. <text:span text:style-name="T114">Proceedings of the 21</text:span><text:span text:style-name="T158">st</text:span><text:span text:style-name="T114"> ACM SIGKDD International Conference on Knowledge Discovery and Data Mining </text:span>(KDD), pp. 2321–2322</text:p>
   <text:p text:style-name="P10">2015<text:tab/>A. Anagnastopoulos, L. Becchetti, A. Fazzone, I. Mele, and <text:span text:style-name="T16">M. Riondato</text:span>. The Importance of Being Experts: Efficient Max-Finding in Crowdsourcing. <text:span text:style-name="T114">Proceedings of the 36</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> ACM SIGMOD International Conference on Management of Data </text:span>(SIGMOD), pp. 983–998</text:p>
   <text:p text:style-name="P10">2014<text:tab/>* <text:span text:style-name="T16">M. Riondato</text:span>, D. García-Soriano, and F. Bonchi. Graph Summarization with <text:soft-page-break/>Quality Guarantees. <text:span text:style-name="T114">Proceedings of the 14</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> IEEE International Conference on Data Mining</text:span> (ICDM), pp. 947–952</text:p>
   <text:p text:style-name="P10">2014<text:tab/><text:span text:style-name="T16">M. Riondato</text:span>. Sampling-based Data Mining Algorithms: Modern Techniques and Case Studies. <text:span text:style-name="T114">Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases </text:span>(ECML PKDD), pp. 516–519</text:p>
   <text:p text:style-name="P10">2014<text:tab/><text:span text:style-name="T16">M. Riondato</text:span> and F. Vandin. Finding the True Frequent Itemsets. <text:span text:style-name="T114">Proceedings of the 14</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> SIAM International Conference on Data Mining</text:span> (SDM), pp. 497–505</text:p>
   <text:p text:style-name="P10">2014<text:tab/><text:span text:style-name="T16">* M. Riondato</text:span> and E. M. Kornaropoulos. Fast Approximation of Betweenness Centrality through Sampling. <text:span text:style-name="T114">Proceedings of the 7</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> ACM International Conference on Web Search and Data Mining</text:span> (WSDM), pp. 413–422</text:p>
   <text:p text:style-name="P10">2012<text:tab/><text:span text:style-name="T17">* </text:span><text:span text:style-name="T16">M. Riondato</text:span>, J. A. DeBrabant, R. Fonseca, and E. Upfal. PARMA: A Parallel Randomized Algorithm for Association Rules Mining in MapReduce. <text:span text:style-name="T114">Proceedings of the</text:span> <text:span text:style-name="T114">21</text:span><text:span text:style-name="T158">st</text:span><text:span text:style-name="T114"> ACM International Conference on Information and Knowledge Management</text:span> (CIKM), pp. 85–94</text:p>
   <text:p text:style-name="P10">2012<text:tab/><text:span text:style-name="T16">M. Riondato</text:span> and E. Upfal. Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees. <text:span text:style-name="T114">Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases </text:span>(ECML PKDD), pp. 25–41</text:p>
   <text:p text:style-name="P10">2012<text:tab/>A. Pietracaprina, G. Pucci, <text:span text:style-name="T16">M. Riondato</text:span>, F. Silvestri, and E. Upfal. Space-round Tradeoffs for MapReduce Computations. <text:span text:style-name="T114">Proceedings of the 26</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T162"> </text:span><text:span text:style-name="T114">ACM International Conference on Supercomputing</text:span> (ICS), pp. 235–244</text:p>
   <text:p text:style-name="P10">2012<text:tab/>M. Akdere, U. Çetintemel, <text:span text:style-name="T16">M. Riondato</text:span>, E. Upfal, and S. B. Zdonik. Learning-based Query Performance Modeling and Prediction. <text:span text:style-name="T114">Proceedings of the 28</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> IEEE International Conference on Data Engineering</text:span> (ICDE), pp. 390–401</text:p>
   <text:p text:style-name="P10">2011<text:tab/><text:span text:style-name="T16">*</text:span> <text:span text:style-name="T16">M. Riondato</text:span>, M. Akdere, U. Çetintemel, S. B. Zdonik, and E. Upfal. The VC-dimension of SQL Queries and Selectivity Estimation through Sampling. <text:span text:style-name="T114">Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases</text:span> (ECML PKDD), pp. 661–676</text:p>
   <text:p text:style-name="P11">2011<text:tab/>M. Akdere, U. Çetintemel, <text:span text:style-name="T16">M. Riondato</text:span>, E. Upfal, and S. B. Zdonik. The Case for Predictive Database Systems: Opportunities and Challenges. <text:span text:style-name="T114">Proceedings of the 5</text:span><text:span text:style-name="T158">th</text:span><text:span text:style-name="T114"> Biennial Conference on Innovative Data System Research</text:span> (CIDR), pp. 167–174</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">Technical Reports</text:p>
   <text:p text:style-name="P5"/>
   <text:p text:style-name="P11"><text:span text:style-name="T163">2018<text:tab/></text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T163">.</text:span><text:span text:style-name="T16"> </text:span><text:span text:style-name="T163">Sharpe Ratio: Estimation, Confidence Intervals, and Hypothesis Testing. </text:span><text:span text:style-name="T164">Two Sigma Technical Report Series</text:span><text:span text:style-name="T163">, No. 2018-001</text:span></text:p>
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   <text:p text:style-name="P5"><text:soft-page-break/>Tutorials</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P42">202<text:span text:style-name="T165">1</text:span><text:tab/><text:span text:style-name="T97">L. Pellegrina, </text:span><text:span text:style-name="T16">M. Riondato,</text:span><text:span text:style-name="T97"> and F. Vandin</text:span><text:span text:style-name="T17">. </text:span><text:span text:style-name="T157">Hypothesis testing and statistically-sound pattern mining. </text:span><text:span text:style-name="T17">SIAM SDM’2</text:span><text:span text:style-name="T166">1</text:span></text:p>
   <text:p text:style-name="P43">2020<text:tab/><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T17">. </text:span><text:span text:style-name="T157">Hypothesis testing and statistically-sound pattern mining. </text:span><text:span text:style-name="T17">SIAM SDM’20 </text:span><text:span text:style-name="T97">(co-organized with L. Pellegrina and F. Vandin) </text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T167">(Conference canceled due to COVID-19)</text:span></text:span></text:p>
   <text:p text:style-name="P44">2019<text:tab/>L. Pellegrina, <text:span text:style-name="T16">M. Riondato,</text:span><text:span text:style-name="T17"> </text:span><text:span text:style-name="T133">and </text:span><text:span text:style-name="T17">F. Vandin. Hypothesis testing and statistically-sound pattern mining. ACM KDD‘19</text:span></text:p>
   <text:p text:style-name="P45">2016<text:tab/>F. Bonchi, G. De Francisci Morales, <text:span text:style-name="T48">and </text:span><text:span text:style-name="T16">M. Riondato</text:span><text:span text:style-name="T163">.</text:span> Centrality Measures in Big Graphs: Exact, Approximated, and Distributed Algorithms. WWW‘16</text:p>
   <text:p text:style-name="P45">2015<text:tab/><text:span text:style-name="T16">M. Riondato</text:span> and E. Upfal. VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms. ACM KDD‘15, ECML PKDD‘15, ACM CIKM‘15</text:p>
   <text:p text:style-name="P45"/>
   <text:p text:style-name="P46">Abstracts</text:p>
   <text:p text:style-name="P46"/>
   <text:p text:style-name="P47"><text:span text:style-name="T130">202</text:span><text:span text:style-name="T168">2</text:span><text:span text:style-name="T130"><text:tab/></text:span><text:span text:style-name="T169">M. Riondato</text:span><text:span text:style-name="T130">. </text:span><text:span text:style-name="T168">Scalable </text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T130">Algorithms for S</text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T168">tatistical</text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T130"> Hypothesis Testing. SIAM Conference on Mathematics of Data Science</text:span></text:span></text:p>
   <text:p text:style-name="P48"><text:span text:style-name="T130">2020<text:tab/></text:span><text:span text:style-name="T169">M. Riondato</text:span><text:span text:style-name="T130">. </text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T17">Algorithms for Scalable Hypothesis Testing. </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T130">SIAM Conference on Mathematics of Data Science </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T167">(Conference postponed due to COVID-19)</text:span></text:span></text:p>
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   <text:p text:style-name="P5">AWARDS</text:p>
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   <text:p text:style-name="P50">2023<text:tab/>Blue-sky Track Best Paper Award Runner-up at SIAM International Conference on Data Mining (SDM<text:span text:style-name="T170">‘</text:span>23)</text:p>
   <text:p text:style-name="P51">20<text:span text:style-name="T171">22</text:span><text:tab/>Invited <text:span text:style-name="T172">article</text:span> to the special issue of <text:span text:style-name="T170">Knowledge and Information Systems </text:span>for the best papers of <text:span text:style-name="T170">IEEE ICDM‘</text:span><text:span text:style-name="T171">22</text:span></text:p>
   <text:p text:style-name="P52">2021<text:tab/>Best Paper Award <text:span text:style-name="T173">Honorable Mention </text:span>at ACM International Conference on Web <text:tab/>Search and Data Mining (ACM WSDM<text:span text:style-name="T170">‘</text:span>21)</text:p>
   <text:p text:style-name="P53">2020<text:tab/>Best reviewer award for the journal track of ECML PKDD<text:span text:style-name="T170">‘</text:span>20</text:p>
   <text:p text:style-name="P54">201<text:span text:style-name="T170">8</text:span><text:tab/>Invited <text:span text:style-name="T172">article</text:span> to the special issue of <text:span text:style-name="T170">Knowledge and Information Systems </text:span>for the best papers of <text:span text:style-name="T170">IEEE ICDM‘</text:span>18</text:p>
   <text:p text:style-name="P55">2018<text:tab/>Best Student Paper Award runner-up at IEEE International Conference on Data Mining (IEEE ICDM‘18)</text:p>
   <text:p text:style-name="P54">2018<text:tab/>Invited <text:span text:style-name="T172">article</text:span> to the special issue of ACM Transactions on Knowledge Discovery <text:soft-page-break/>from Data for the best papers of ACM KDD‘18</text:p>
   <text:p text:style-name="P55">2018<text:tab/>Invited Young Researcher to the 6<text:span text:style-name="T174">th</text:span> Heidelberg Laureate Forum</text:p>
   <text:p text:style-name="P56">2016<text:tab/>Best Student Paper Award (Research Track) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD‘16)</text:p>
   <text:p text:style-name="P56">2014<text:tab/>Nominated for the ACM SIGKDD Doctoral Dissertation Award</text:p>
   <text:p text:style-name="P56">2014<text:tab/>Best Student Poster Award at SIAM International Conference on Data Mining (SDM‘14)</text:p>
   <text:p text:style-name="P56">201<text:span text:style-name="T170">0</text:span><text:tab/><text:span text:style-name="T172">Article</text:span> <text:span text:style-name="T170">selected for </text:span>the special issue of <text:span text:style-name="T170">Data Mining and Knowledge Discovery</text:span> for the best papers of <text:span text:style-name="T170">ECML PKDD’10</text:span></text:p>
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   <text:p text:style-name="P5">GRANTS AND FELLOWSHIPS</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P57"><text:span text:style-name="T87">202</text:span><text:span text:style-name="T4">3</text:span><text:span text:style-name="T87">-</text:span><text:span text:style-name="T175">2</text:span><text:span text:style-name="T4">8</text:span><text:span text:style-name="T175"><text:tab/></text:span><text:span text:style-name="T87">PI on NSF Award #</text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T151">2238693</text:span></text:span><text:span text:style-name="T151">: </text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T151">CAREER: Statistically-Sound Knowledge <text:tab/><text:tab/><text:tab/>Discovery from Data </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T176">(USD 600k, no co-PI)</text:span></text:span></text:p>
   <text:p text:style-name="P58"><text:span text:style-name="T87">2020-</text:span><text:span text:style-name="T175">2</text:span><text:span text:style-name="T4">4</text:span><text:span text:style-name="T175"><text:tab/></text:span><text:span text:style-name="T87">PI on NSF Award #2006765</text:span><text:span text:style-name="T151">: </text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T17">III: Small: RUI: Scalable and Iterative Statistical <text:tab/><text:tab/>Testing of Multiple Hypotheses on Massive Datasets </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T151">(USD 373k, </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T177">no co-PI</text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T151">)</text:span></text:span></text:p>
   <text:p text:style-name="P58"><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T178">2021-22<text:tab/>Amherst College </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T151">Provost’s Research Fellowship </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T178">(100% of 9 months salary)</text:span></text:span></text:p>
   <text:p text:style-name="P59"><text:span text:style-name="T179">2019<text:tab/>PI on NSF Award #</text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T17">1918446:</text:span></text:span><text:span text:style-name="Strong_20_Emphasis"> </text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T17">NSF Student Travel Grant for 2019 SIAM International Conference on Data Mining (SDM) </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T89">(USD 25k)</text:span></text:span></text:p>
   <text:p text:style-name="P56">2015<text:tab/>SIAM/NSF Early Career Travel Award to SIAM Intl. Conference on Data Mining</text:p>
   <text:p text:style-name="P56">2014<text:tab/>SIAM Travel Award to SIAM Intl. Conference on Data Mining</text:p>
   <text:p text:style-name="P56">2014<text:tab/>Brown University Dissertation Fellowship</text:p>
   <text:p text:style-name="P56">2013<text:tab/>Yahoo Research Barcelona Summer Internship</text:p>
   <text:p text:style-name="P56">2011<text:tab/>Italy MIUR Research Fellowship</text:p>
   <text:p text:style-name="P56">2009<text:tab/>Brown University Graduate Fellowship</text:p>
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   <text:p text:style-name="P5">INVITED TALKS</text:p>
   <text:p text:style-name="P6"/>
   <text:p text:style-name="P60"><text:span text:style-name="T180">2024<text:tab/><text:tab/></text:span><text:bookmark text:name="docs-internal-guid-ded4a341-7fff-7bf8-345f-360d68c934fa"/><text:span text:style-name="T181">Sampling Binary Matrices  with Hard Constraints: Algorithms and Impossibility <text:tab/><text:tab/>Results</text:span><text:span text:style-name="T182">, Statiustics and Data Science Colloquium, Amherst College, February 22</text:span></text:p>
   <text:p text:style-name="P61">2022<text:tab/>Statistical Learning Theory meets Data Mining: Fast, High-quality, Sampling-based Approximation Algorithms, CS Department Talk, Williams College, over Zoom, January 12</text:p>
   <text:p text:style-name="P62"><text:soft-page-break/>2021<text:tab/>Communication in Science Panel, Summer Research Undergraduate Fellows Program, Amherst College, Amherst (MA, USA), June 24</text:p>
   <text:p text:style-name="P62"><text:span text:style-name="T165">2021<text:tab/></text:span><text:span text:style-name="T68">RePBubLik: Reducing the Polarized Bubble Radius with Link Insertions. </text:span><text:span text:style-name="T166">Aris Gionis’ Research Group Meeting, KTH Royal Institute of Technology, over Zoom, February 18</text:span></text:p>
   <text:p text:style-name="P62"><text:span text:style-name="T183">2020<text:tab/></text:span><text:span text:style-name="T89">McRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining, </text:span><text:span text:style-name="T184">AI Seminar,</text:span><text:span text:style-name="T185"> </text:span><text:span text:style-name="T184">Fidelity, over Zoom</text:span><text:span text:style-name="T185">, October </text:span><text:span text:style-name="T184">28</text:span></text:p>
   <text:p text:style-name="P62"><text:span text:style-name="T183">2020<text:tab/></text:span><text:span text:style-name="T89">McRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining, </text:span><text:span text:style-name="T185">Theory Seminar, UMass Amherst, Amherst (MA, USA), October 6</text:span></text:p>
   <text:p text:style-name="P63">2020<text:tab/>Advancing Science by (not) Testing Billions of Hypotheses, Faculty Colloquium, Amherst College, Amherst (MA, USA), September 25</text:p>
   <text:p text:style-name="P56"><text:span text:style-name="T186">2020<text:tab/>Algorithms for Centrality Measures, </text:span>CS59<text:span text:style-name="T186">1 – </text:span>Large-Scale Graph Mining,<text:span text:style-name="T186"> Boston University, Boston (MA, USA), April 13</text:span></text:p>
   <text:p text:style-name="P64">2019<text:tab/>SPuManTE: Significant Pattern Mining with Unconditional Testing, Network Science Institute, Northeastern University, Boston (MA, USA), November 8</text:p>
   <text:p text:style-name="P56"><text:span text:style-name="T187">2019<text:tab/>Making </text:span><text:span text:style-name="T188">B</text:span><text:span text:style-name="T187">etter </text:span><text:span text:style-name="T188">U</text:span><text:span text:style-name="T187">se of </text:span><text:span text:style-name="T188">D</text:span><text:span text:style-name="T187">ata, MassMutual Research Bytes series, Amherst (MA, USA), November 5</text:span></text:p>
   <text:p text:style-name="P56"><text:span text:style-name="T189">2019<text:tab/>Making </text:span><text:span text:style-name="T188">B</text:span><text:span text:style-name="T189">etter </text:span><text:span text:style-name="T188">U</text:span><text:span text:style-name="T189">se of </text:span><text:span text:style-name="T188">D</text:span><text:span text:style-name="T189">ata, </text:span><text:span text:style-name="T190">Data Management Lab, </text:span><text:span text:style-name="T189">Boston University, Boston (MA, <text:tab/>USA), October 25</text:span></text:p>
   <text:p text:style-name="P56"><text:span text:style-name="T189">2019<text:tab/>Making </text:span><text:span text:style-name="T188">B</text:span><text:span text:style-name="T189">etter </text:span><text:span text:style-name="T188">U</text:span><text:span text:style-name="T189">se of </text:span><text:span text:style-name="T188">D</text:span><text:span text:style-name="T189">ata, </text:span><text:span text:style-name="T190">Department of Computer Science, </text:span><text:span text:style-name="T189">Mount Holyoke College, South Hadley (MA, USA), October 16</text:span></text:p>
   <text:p text:style-name="P56"><text:span text:style-name="T187">2019<text:tab/>CaDET: Interpretable Parametric Conditional Density Estimation with Decision Trees, Workshop on Computation and Statistics in Data Science (CaStleD’1</text:span><text:span text:style-name="T186">9</text:span><text:span text:style-name="T187">), Bertinoro (FC, Italy), October 1</text:span></text:p>
   <text:p text:style-name="P56"><text:span text:style-name="T191">2019<text:tab/>Pseudodimension for Data Analysis, </text:span><text:span text:style-name="T192">Workshop on </text:span><text:span text:style-name="T191">Data Science in Low-dimensional Spaces, </text:span><text:span text:style-name="T190">ICERM, Brown University, </text:span><text:span text:style-name="T191">Providence (RI, USA), May 17</text:span></text:p>
   <text:p text:style-name="P56">2018<text:tab/>MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension, Google Research NY, New York (NY, USA), December 4</text:p>
   <text:p text:style-name="P56">2018<text:tab/><text:span text:style-name="T5">Approximation Algorithms for Betweenness Centrality</text:span>, COMPSCI 134 – Networks, Harvard University, Cambridge (MA, USA), November 26</text:p>
   <text:p text:style-name="P56">2018<text:tab/>Data Mining: <text:span text:style-name="T189">T</text:span>asks, <text:span text:style-name="T189">S</text:span>ystems, <text:span text:style-name="T189">C</text:span>hallenges, and <text:span text:style-name="T189">R</text:span>esearch <text:span text:style-name="T189">D</text:span>irections, Amherst College, Amherst (MA, USA), November 5</text:p>
   <text:p text:style-name="P56">2018<text:tab/>Statistical Learning Theory meets Data Mining: Fast, High-quality, Sampling-based Approximation Algorithm, ISI Foundation, Turin (Italy), September 8</text:p>
   <text:p text:style-name="P56">2018<text:tab/>Sampling-based Approximation Algorithms for Data Analysis using Rademacher <text:soft-page-break/>Averages, Theory of Computation Seminar, Harvard University, Cambridge (MA, USA), May 7</text:p>
   <text:p text:style-name="P56">2018<text:tab/>Statistical Learning Theory meets Data Mining: Fast, High-quality, Sampling-based Approximation Algorithms, Boston College, Chestnut Hill (MA, USA), January 31</text:p>
   <text:p text:style-name="P56">2018<text:tab/>Statistical Learning Theory meets Data Mining: Fast, High-quality, Sampling-based Approximation Algorithms, Amherst College, Amherst (MA, USA), January 25</text:p>
   <text:p text:style-name="P56">2017<text:tab/>Betweenness Centrality Estimation with Rademacher Averages, National Institute of Informatics, Tokyo (Japan), November 16</text:p>
   <text:p text:style-name="P56">2017<text:tab/>Betweenness Centrality Estimation with Rademacher Averages, Center for Data Science, New York University, New York (NY, USA), May 17</text:p>
   <text:p text:style-name="P56">2017<text:tab/>Rademacher Averages: Theory and Practice, Dagstuhl Seminar 17141, Schloss Dagstuhl (Germany), April 6</text:p>
   <text:p text:style-name="P56">2017<text:tab/>Random Sampling for Data Mining: The Case of Triangles in Dynamic Streams, School of Computer Science, McGill University, Montreal (QB, Canada), February 21</text:p>
   <text:p text:style-name="P56">2017<text:tab/>Random Sampling for Data Mining: The Case of Triangles in Dynamic Streams, College of Computer and Information Science, Northeastern University, Boston (MA, USA), February 15</text:p>
   <text:p text:style-name="P56">2017<text:tab/>The Neverending Data – Streaming, Sampling, and Triangle Counting, Department of Computer Science, Amherst College, Amherst (MA, USA), January 27</text:p>
   <text:p text:style-name="P56">2016<text:tab/>Approximating Betweenness Centrality through Sampling with the Rademacher Averages, <text:span text:style-name="T190">Data Management Lab, </text:span>Boston University, Boston (MA, USA), November 18</text:p>
   <text:p text:style-name="P56">2016<text:tab/>Algorithmic Data Science = Theory + Practice, IEEE MIT Undergraduate Technology Research Conference, Massachusetts Institute of Technology, Cambridge (MA, USA), November 5</text:p>
   <text:p text:style-name="P56">2016<text:tab/>TRIÉST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size, Database Group, Carnegie Mellon University, Pittsburgh (PA, USA), October 24</text:p>
   <text:p text:style-name="P56">2016<text:tab/>Approximating Betweenness Centrality through Sampling with the Rademacher Averages, Network Science Institute, Northeastern University, Boston (MA, USA), October 17</text:p>
   <text:p text:style-name="P56">2016<text:tab/>Graph Summarization with Quality Guarantees, Department of Information Engineering, University of Padua, Padua (Italy), September 26</text:p>
   <text:p text:style-name="P56"><text:soft-page-break/>2016<text:tab/>ABRA: Venice, Sampling, and Betweenness Centrality Estimation, Social Impact through Network Science (SINS), Venice (Italy), June 8</text:p>
   <text:p text:style-name="P56">2015<text:tab/>Data is …, Stevens Institute of Technology, Hoboken (NJ, USA), December 12</text:p>
   <text:p text:style-name="P56">2015<text:tab/>Travel Pictures from Another World: Statistical Learning Theory Meets Data Mining, Monash University, Melbourne (Australia), October 28</text:p>
   <text:p text:style-name="P56">2015<text:tab/>Modern Sampling for Modern Data: The Case of Frequent Itemsets Mining, Two Sigma Investments, New York (NY, USA), March 5</text:p>
   <text:p text:style-name="P56">2014<text:tab/>Statistical Learning and Data Mining: A Lasting Marriage, Data Mining: Beyond The Horizon Workshop, University of Bristol, Bristol (UK), November 20</text:p>
   <text:p text:style-name="P56">2014<text:tab/>Efficient Frequent Itemsets Mining through Sampling, Database Research Group, University of Waterloo, Waterloo (ON, Canada), May 7</text:p>
   <text:p text:style-name="P56">2014<text:tab/>Efficient Frequent Itemsets Mining through Sampling, Database Group, MIT CSAIL, Cambridge (MA, USA), April 10</text:p>
   <text:p text:style-name="P56">2014<text:tab/>Taming the Challenges of Big Data with Statistical Data Analytics, Department of Computer Science, Boston College, Boston (MA, USA), February 7</text:p>
   <text:p text:style-name="P56">2013<text:tab/>Fast Betweenness Estimation through Sampling, Data Management <text:span text:style-name="T190">Lab</text:span>, Boston University, Boston (MA, USA), October 17</text:p>
   <text:p text:style-name="P56">2013<text:tab/>Fast Betweenness Estimation through Sampling, Yahoo! Labs Barcelona, Barcelona (Spain), June 13</text:p>
   <text:p text:style-name="P56">2013<text:tab/>Fast Betweenness Estimation through Sampling, Advanced Computing Group, University of Padua, Padua (Italy), May 30</text:p>
   <text:p text:style-name="P56">2013<text:tab/>Statistical Learning Theory meets Knowledge Discovery, Brown CS Industrial Partners Program Symposium, Providence (RI, USA), April 2</text:p>
   <text:p text:style-name="P56">2011<text:tab/>Statistical Learning Theory meets Databases, Advanced Computing Group, <text:tab/>University of Padua, Padua (Italy), June 24</text:p>
   <text:p text:style-name="P56">2010<text:tab/>Top-k Frequent Itemsets Mining through Sampling, Advanced Computing Group, University of Padua, Padua (Italy), September 16</text:p>
   <text:p text:style-name="P56">2010<text:tab/>Mining Top-K Frequent Itemsets Through Progressive Sampling, <text:span text:style-name="T190">Department of Computer Science, </text:span>Chalmers University of Technology, Gothenburg (Sweden), August 5</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">ADDITIONAL RESEARCH EXPERIENCE AND VISITS</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P65">2017<text:tab/>National Institute of Informatics (Tokyo, Japan) – Visiting Researcher, November</text:p>
   <text:p text:style-name="P65">2015<text:tab/>Monash University (Melbourne, Australia) – Visiting Researcher, October</text:p>
   <text:p text:style-name="P65"><text:soft-page-break/>2012<text:tab/>Sapienza University of Rome (Rome, Italy) – Visiting Ph.D. Student, June–September</text:p>
   <text:p text:style-name="P66">2011<text:tab/><text:tab/>University of Padua (Padua, Italy) – Research Fellow, June–September</text:p>
   <text:p text:style-name="P65">2010<text:tab/>Chalmers University of Technology (Gothenburg, Sweden) – Visiting Ph.D. Student, August</text:p>
   <text:p text:style-name="P67">2008–9<text:tab/>Brown University (Providence, RI, USA) – Visiting Student, October–June</text:p>
   <text:p text:style-name="P68"/>
   <text:p text:style-name="P69"/>
   <text:p text:style-name="P70">TEACHING EXPERIENCE</text:p>
   <text:p text:style-name="P71"/>
   <text:p text:style-name="P72">Amherst College</text:p>
   <text:p text:style-name="P72"/>
   <text:p text:style-name="P73">Spring <text:span text:style-name="T193">‘2</text:span>5<text:tab/>COSC-254 Data Mining</text:p>
   <text:p text:style-name="P73"><text:tab/><text:tab/>COSC-401 Theory of Computation</text:p>
   <text:p text:style-name="P73">Fall <text:span text:style-name="T193">‘2</text:span>4<text:tab/><text:span text:style-name="T193">COSC-111 Introduction to Computer Science 1</text:span></text:p>
   <text:p text:style-name="P73"><text:tab/><text:tab/>COSC-223 Probability and Computing</text:p>
   <text:p text:style-name="P73"><text:tab/><text:tab/>COLQ-390U Learning by Doing: Internship and Fieldwork Reflection</text:p>
   <text:p text:style-name="P73">Spring <text:span text:style-name="T193">‘2</text:span>4<text:tab/><text:span text:style-name="T193">COSC-111 Introduction to Computer Science 1 </text:span>(2 sections)</text:p>
   <text:p text:style-name="P74">Fall <text:span text:style-name="T193">‘2</text:span>3<text:tab/><text:span text:style-name="T193">COSC-111 Introduction to Computer Science 1</text:span></text:p>
   <text:p text:style-name="P74"><text:tab/><text:tab/>COSC-257 Databases</text:p>
   <text:p text:style-name="P74"><text:tab/><text:tab/><text:span text:style-name="T194">COLQ-390H Learning by Doing: Internship and Fieldwork Reflection</text:span></text:p>
   <text:p text:style-name="P75">Spring ‘2<text:span text:style-name="T195">3</text:span><text:tab/>COSC-111 Introduction to Computer Science 1</text:p>
   <text:p text:style-name="P76"><text:tab/><text:tab/>COSC-351 Information Theory</text:p>
   <text:p text:style-name="P77"><text:tab/><text:tab/><text:span text:style-name="T194">COSC-490 Database Implementation (special topics, </text:span><text:span text:style-name="T196">1</text:span><text:span text:style-name="T194"> student)</text:span></text:p>
   <text:p text:style-name="P76">Fall ‘22<text:tab/><text:span text:style-name="T194">COSC-111 Introduction to Computer Science 1</text:span></text:p>
   <text:p text:style-name="P76"><text:tab/><text:tab/><text:span text:style-name="T194">COSC-355 Network Science</text:span></text:p>
   <text:p text:style-name="P78"><text:tab/><text:tab/>COLQ-390H Learning by Doing: Internship and Fieldwork Reflection</text:p>
   <text:p text:style-name="P79">Spring <text:span text:style-name="T194">‘2</text:span>1<text:tab/><text:span text:style-name="T194">COSC-111 Introduction to Computer Science 1</text:span></text:p>
   <text:p text:style-name="P79"><text:tab/><text:tab/>COSC-254 Data Mining</text:p>
   <text:p text:style-name="P79"><text:tab/><text:tab/>COSC-490 Topics in Data Science (special topics, 1 student)</text:p>
   <text:p text:style-name="P80">Fall ‘20<text:tab/>COSC-111 Introduction to Computer Science 1 (<text:span text:style-name="T197">2</text:span> sections)</text:p>
   <text:p text:style-name="P80"><text:tab/><text:tab/>COLQ-390H Learning by Doing: Internship and Fieldwork Reflection</text:p>
   <text:p text:style-name="P80">Spring ‘20<text:tab/>COSC-111 Introduction to Computer Science 1</text:p>
   <text:p text:style-name="P80"><text:soft-page-break/><text:tab/><text:tab/>COSC-355 Network Science</text:p>
   <text:p text:style-name="P80"><text:tab/><text:tab/>COSC-490 Database Implementation (special topics, 2 students)</text:p>
   <text:p text:style-name="P80"><text:tab/><text:tab/>COSC-490 Advanced Analytics (special topics, 1 student)</text:p>
   <text:p text:style-name="P80">Fall ‘19<text:tab/>COSC-111 Introduction to Computer Science 1</text:p>
   <text:p text:style-name="P80"><text:tab/><text:tab/>COSC-257 Databases</text:p>
   <text:p text:style-name="P80"><text:tab/><text:tab/>COSC-490 Regression and Time Series (special topics, 1 student)</text:p>
   <text:p text:style-name="P80"><text:tab/><text:tab/>STAT-490H Theory meets Practice (co-taught)</text:p>
   <text:p text:style-name="P80">Spring ‘19<text:tab/>COSC-111 Introduction to Computer Science 1</text:p>
   <text:p text:style-name="P80"><text:tab/><text:tab/>COSC-254 Data Mining</text:p>
   <text:p text:style-name="P81"/>
   <text:p text:style-name="P70">Brown University</text:p>
   <text:p text:style-name="P71"/>
   <text:p text:style-name="P82"><text:span text:style-name="T194">Spring ‘18<text:tab/>CSCI-1951-G </text:span>Optimization Methods in Finance</text:p>
   <text:p text:style-name="P83">Spring ‘16<text:tab/>CSCI-1951-G Optimization Methods in Finance</text:p>
   <text:p text:style-name="P84"/>
   <text:p text:style-name="P84"/>
   <text:p text:style-name="P85"><text:span text:style-name="T76">SUPERVISION OF </text:span><text:span text:style-name="T194">THESES </text:span><text:span text:style-name="T76">AND OF </text:span>STUDENT<text:span text:style-name="T76">S OR</text:span><text:span text:style-name="T198"> INTERN</text:span><text:span text:style-name="T76">S</text:span></text:p>
   <text:p text:style-name="P86"/>
   <text:p text:style-name="P87">PhD Students</text:p>
   <text:p text:style-name="P87"/>
   <text:p text:style-name="P88">2024-<text:tab/><text:tab/>Maryam Abuissa, PhD Student in Computer Science, Brown University (Co-<text:tab/><text:tab/>Advised with Eli Upfal)</text:p>
   <text:p text:style-name="P89"/>
   <text:p text:style-name="P89">Honors Theses</text:p>
   <text:p text:style-name="P90"/>
   <text:p text:style-name="P91"><text:span text:style-name="T178">2</text:span><text:span text:style-name="T17">022-23<text:tab/>Shengdi Li, </text:span><text:span text:style-name="T53">The CurveBall Algorithm for Significant Pattern Mining</text:span></text:p>
   <text:p text:style-name="P92"><text:span text:style-name="T17"><text:tab/><text:tab/>Sarah Park, </text:span><text:span text:style-name="T53">Finding the True Frequent Itemsets with Hypothesis Testing</text:span></text:p>
   <text:p text:style-name="P92"><text:span text:style-name="T17"><text:tab/><text:tab/>Stefan Walzer-Goldfeld, </text:span><text:span text:style-name="T53">Mining Statistically Significant High-Utility Itemsets</text:span></text:p>
   <text:p text:style-name="P93"><text:span text:style-name="T178">2021-22<text:tab/>Alexander Lee,</text:span><text:span text:style-name="T199"> </text:span><text:span text:style-name="T200">DiFfuSR: Distortion-free Swap-randomization for Statistically-<text:tab/><text:tab/>testing Data Mining Results </text:span><text:span text:style-name="T80">(Computer Science Prize))</text:span></text:p>
   <text:p text:style-name="P94"><text:span text:style-name="T201"><text:tab/><text:tab/></text:span><text:span text:style-name="T202">Adam Gibbs, </text:span><text:span text:style-name="T114">Efficient Subgraph Matching with Security Applications </text:span><text:span text:style-name="T201">(not <text:tab/><text:tab/>completed)</text:span></text:p>
   <text:p text:style-name="P95"><text:span text:style-name="T194">2020-21<text:tab/></text:span>Isaac Caruso, <text:span text:style-name="T203">Modeling Biological Species Presence with Gaussian Processes</text:span></text:p>
   <text:p text:style-name="P96"><text:span text:style-name="T194">2019-20<text:tab/></text:span>Kathleen Isenegger, <text:span text:style-name="T203">Approximate Mining of High-Utility Itemsets throug</text:span><text:span text:style-name="T18">h <text:tab/></text:span><text:soft-page-break/><text:span text:style-name="T18"><text:tab/><text:tab/></text:span><text:span text:style-name="T203">Sampling</text:span></text:p>
   <text:p text:style-name="P97"><text:span text:style-name="T194"><text:tab/><text:tab/>S</text:span>hukry Zablah, <text:span text:style-name="T203">A Parallel Algorithm for Balanced Sampling </text:span><text:span text:style-name="T201">(Computer Science <text:tab/><text:tab/>Prize)</text:span></text:p>
   <text:p text:style-name="P98"/>
   <text:p text:style-name="P99"><text:span text:style-name="T204">Student </text:span><text:span text:style-name="T205">and Intern </text:span><text:span text:style-name="T204">Supervision </text:span><text:span text:style-name="T206">(not including T</text:span><text:span text:style-name="T205">eaching </text:span><text:span text:style-name="T206">As</text:span><text:span text:style-name="T205">sistants </text:span><text:span text:style-name="T77">and Honors Students</text:span><text:span text:style-name="T206">)</text:span></text:p>
   <text:p text:style-name="P100"/>
   <text:p text:style-name="P101"><text:span text:style-name="T207">Amherst College, research assistant (alphabetical order): </text:span><text:span text:style-name="T208">Maryam Abuissa, </text:span><text:span text:style-name="T209">M</text:span><text:span text:style-name="T210">ichelle Contreras Catalan, </text:span><text:span text:style-name="T211">Daniel Flores García, </text:span><text:span text:style-name="T212">Conrad Kuklinsky, </text:span><text:span text:style-name="T213">Steedman Jenkins, </text:span><text:span text:style-name="T214">Zhiyuan Jia, </text:span><text:span text:style-name="T215">Wanting Jiang, </text:span><text:span text:style-name="T216">Hailin Kim, </text:span><text:span text:style-name="T217">Alexander Lee, </text:span><text:span text:style-name="T218">Holden Lee, </text:span><text:span text:style-name="T219">Sergei Leonov, Megan Li, </text:span><text:span text:style-name="T220">Dhyey Mavani, </text:span><text:span text:style-name="T219">Ris Paulino, </text:span><text:span text:style-name="T221">Sriyash Singhania, </text:span><text:span text:style-name="T222">Stefan Walzer-</text:span><text:span text:style-name="T223">Goldfeld, </text:span><text:span text:style-name="T224">Chloe Wohlgemuth, </text:span><text:span text:style-name="T221">Hewan Worku, Sarah Wu</text:span></text:p>
   <text:p text:style-name="P102">Amherst College, student intern:<text:span text:style-name="T202"> </text:span><text:span text:style-name="T225">Margaret Drew, </text:span><text:span text:style-name="T226">Vaibhav Shah</text:span></text:p>
   <text:p text:style-name="P103"><text:span text:style-name="T114">Two Sigma Investments, Labs Team, research intern:</text:span> <text:span text:style-name="T227">Cyrus Cousins</text:span></text:p>
   <text:p text:style-name="P104"><text:span text:style-name="T114">Brown University, </text:span><text:span text:style-name="T228">research assistant:</text:span><text:span text:style-name="T229"> </text:span>Sacha Servan-Schreibe<text:span text:style-name="T229">r</text:span></text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">SERVICE TO THE SCIENTIFIC COMMUNITY</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">Editorial Boards</text:p>
   <text:p text:style-name="P5"/>
   <text:p text:style-name="P105">Data Mining and Knowledge Discovery <text:span text:style-name="T230">(Action Editor)</text:span></text:p>
   <text:p text:style-name="P106"><text:span text:style-name="T231">Machine Learning </text:span>(Guest editorial board for ECML PKDD <text:span text:style-name="T187">‘</text:span>19-<text:span text:style-name="T187">‘</text:span><text:span text:style-name="T180">24</text:span>)</text:p>
   <text:p text:style-name="P107"/>
   <text:p text:style-name="P5">Organizing Committees</text:p>
   <text:p text:style-name="P108"/>
   <text:p text:style-name="P109">SIAM SDM <text:span text:style-name="T232">‘</text:span><text:span text:style-name="T233">2</text:span>5 (General Co-Chair)</text:p>
   <text:p text:style-name="P109">ACM CIKM <text:span text:style-name="T232">‘</text:span><text:span text:style-name="T233">2</text:span>5 (Tutorials Chair)</text:p>
   <text:p text:style-name="P110">Statistical and Probabilistic Methods in Algorithmic Data Analysis (Dagsthul, Germany, September 2024) (Co-Organizer)</text:p>
   <text:p text:style-name="P111">ACM KDD <text:span text:style-name="T232">‘</text:span><text:span text:style-name="T233">2</text:span><text:span text:style-name="T234">4 </text:span><text:span text:style-name="T233">(</text:span>PhD<text:span text:style-name="T233"> </text:span>Consortium<text:span text:style-name="T233"> Co-Chair)</text:span></text:p>
   <text:p text:style-name="P112">SIAM SDM <text:span text:style-name="T232">‘</text:span><text:span text:style-name="T233">2</text:span>4 (Blue-sky-ideas Track Program Chair)</text:p>
   <text:p text:style-name="P113">ECML PKDD <text:span text:style-name="T232">‘</text:span>23 (Doctoral Forum Co-Chair)</text:p>
   <text:p text:style-name="P114">SIAM SDM <text:span text:style-name="T232">‘</text:span>22 (Program Committee <text:span text:style-name="T235">Co-</text:span>Chair)</text:p>
   <text:p text:style-name="P115"><text:soft-page-break/>SIAM SDM ‘<text:span text:style-name="T187">2</text:span>1 (Tutorial Chair)</text:p>
   <text:p text:style-name="P116">SIAM SDM ‘<text:span text:style-name="T187">20</text:span>, ‘<text:span text:style-name="T187">19</text:span> (Doctoral Forum Co-chair)</text:p>
   <text:p text:style-name="P117">SIAM SDM <text:span text:style-name="T232">‘</text:span>18 (Sponsorship Co-chair)</text:p>
   <text:p text:style-name="P116">Foundations of Learning from Data Workshop (Bertinoro, Italy, September 2018)(Co-Organizer)</text:p>
   <text:p text:style-name="P118"/>
   <text:p text:style-name="P5">Program Committees</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P119">AAAI ‘<text:span text:style-name="T236">23-</text:span>‘<text:span text:style-name="T187">2</text:span><text:span text:style-name="T195">4</text:span><text:span text:style-name="T237"> (Senior PC), </text:span>‘<text:span text:style-name="T187">19-‘</text:span><text:span text:style-name="T236">20</text:span></text:p>
   <text:p text:style-name="P119">ACM CIKM ‘<text:span text:style-name="T187">2</text:span><text:span text:style-name="T195">4</text:span><text:span text:style-name="T237"> (Senior PC), ‘</text:span><text:span text:style-name="T236">14-</text:span>‘<text:span text:style-name="T238">21</text:span></text:p>
   <text:p text:style-name="P119">ACM KDD ‘<text:span text:style-name="T236">21-</text:span>‘<text:span text:style-name="T238">2</text:span><text:span text:style-name="T236">5</text:span><text:span text:style-name="T238"> (</text:span><text:span text:style-name="T236">Senior PC / </text:span><text:span text:style-name="T180">Area Chair</text:span><text:span text:style-name="T238">), </text:span>‘15-‘<text:span text:style-name="T236">20</text:span></text:p>
   <text:p text:style-name="P119">ACM WSDM ‘<text:span text:style-name="T75">2</text:span><text:span text:style-name="T236">2-‘</text:span><text:span text:style-name="T75">2</text:span><text:span text:style-name="T236">5</text:span><text:span text:style-name="T75"> (Senior PC), ‘</text:span>17-‘<text:span text:style-name="T236">21</text:span></text:p>
   <text:p text:style-name="P119">ECML PKDD ‘<text:span text:style-name="T236">16-</text:span>‘<text:span text:style-name="T75">2</text:span><text:span text:style-name="T180">4</text:span></text:p>
   <text:p text:style-name="P120">Grace Hopper ‘18, ‘16</text:p>
   <text:p text:style-name="P120">ICML ‘19</text:p>
   <text:p text:style-name="P119">IEEE ICDE ‘17-‘18</text:p>
   <text:p text:style-name="P119">IEEE ICDM ‘<text:span text:style-name="T189">2</text:span><text:span text:style-name="T239">1 (Area Chair), </text:span>‘1<text:span text:style-name="T236">6-</text:span>‘<text:span text:style-name="T75">2</text:span><text:span text:style-name="T240">3</text:span></text:p>
   <text:p text:style-name="P121"><text:span text:style-name="T241">IJCAI</text:span> ‘19</text:p>
   <text:p text:style-name="P122">NetSci ‘19-‘<text:span text:style-name="T189">20</text:span></text:p>
   <text:p text:style-name="P119"><text:span text:style-name="T241">Ne</text:span><text:span text:style-name="T242">urIPS</text:span><text:span text:style-name="T241"> ‘</text:span><text:span text:style-name="T236">19-</text:span><text:span text:style-name="T241">‘</text:span><text:span text:style-name="T75">2</text:span><text:span text:style-name="T236">4</text:span></text:p>
   <text:p text:style-name="P123">SIAM SDM ‘<text:span text:style-name="T189">21-</text:span>‘<text:span text:style-name="T75">2</text:span><text:span text:style-name="T195">4</text:span><text:span text:style-name="T237"> (Senior PC), </text:span>‘19-‘<text:span text:style-name="T229">20</text:span></text:p>
   <text:p text:style-name="P123">WWW ‘<text:span text:style-name="T189">2</text:span><text:span text:style-name="T229">1</text:span><text:span text:style-name="T243">-</text:span>‘<text:span text:style-name="T189">2</text:span><text:span text:style-name="T243">3</text:span><text:span text:style-name="T189"> (Senior PC)</text:span>, ‘16-‘<text:span text:style-name="T229">20</text:span></text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">Journal Reviewing</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P6"><text:span text:style-name="T114">ACM Transactions on Database Systems </text:span><text:span text:style-name="T113">(TODS)</text:span></text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">ACM Transactions on Information Systems </text:span>(TOIS)</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">ACM Transactions on Knowledge Discovery from Data </text:span>(TKDD)</text:p>
   <text:p text:style-name="P124">Algorithmica</text:p>
   <text:p text:style-name="P125"><text:span text:style-name="T114">Data Mining and Knowledge Discovery </text:span>(DMKD/DAMI)</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T111">Discrete Applied Mathematics</text:span> (DAM)</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">Engineering Applications of Artificial Intelligence </text:span>(EAAI)</text:p>
   <text:p text:style-name="P6"><text:soft-page-break/><text:span text:style-name="T114">Expert Systems with Applications</text:span> (ESWA)</text:p>
   <text:p text:style-name="P126">Journal of Machine Learning Research <text:span text:style-name="T55">(JMLR)</text:span></text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T111">Journal of Parallel and Distributed Computing</text:span> (JPDC)</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">Knowledge and Information Systems</text:span> (KAIS)</text:p>
   <text:p text:style-name="P127">IEEE Access</text:p>
   <text:p text:style-name="P128">IEEE Open Access Journal of the Computer Society <text:span text:style-name="T202">(OJCS)</text:span></text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">IEEE Transactions on Knowledge and Data Engineering</text:span> (TKDE)</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">IEEE Transactions on Network Science and Engineering</text:span> (TNSE)</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">IEEE Transactions on Parallel and Distributed Systems</text:span> (TPDS)</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">IEEE Transactions on Services Computing</text:span> (TSC)</text:p>
   <text:p text:style-name="P129">Information Science <text:span text:style-name="T202">(INS)</text:span></text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">Machine Learning</text:span> (Mach. Learn.)</text:p>
   <text:p text:style-name="P130">PeerJ Computer Science</text:p>
   <text:p text:style-name="P131">PLOS ONE</text:p>
   <text:p text:style-name="P132">The Computer Journal</text:p>
   <text:p text:style-name="P6"><text:span text:style-name="T114">VLDB Journal</text:span> (VLDBJ)</text:p>
   <text:p text:style-name="P133">The World Wide Web Journal <text:span text:style-name="T202">(WWWJ)</text:span></text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5"><text:span text:style-name="T229">Additional </text:span>Conference Reviewing </text:p>
   <text:p text:style-name="P118">The list does not include reviews done as Program Committee member</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P134"><text:span text:style-name="T244">LATIN‘20, STACS‘20, </text:span>MFCS‘17, SODA’17, ISAAC‘15, SIAM SDM‘15, IEEE ICDE‘15, DISC‘14, ACM WSDM‘14, WWW‘14, ICALP‘14, IEEE BigData‘13, MFCS‘13, ACM WSDM‘13, IEEE IPDPS‘12, ACM ICS‘12, RANDOM‘11</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">Conference Research Session Chair</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P123"><text:span text:style-name="T229">ACM KDD</text:span><text:span text:style-name="T195"> </text:span><text:span text:style-name="T245">‘</text:span><text:span text:style-name="T237">2</text:span><text:span text:style-name="T229">4 </text:span><text:span text:style-name="T237">– </text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T17">Probabilistic &amp; Statistical </text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T246">M</text:span></text:span><text:span text:style-name="Strong_20_Emphasis"><text:span text:style-name="T17">ethods</text:span></text:span></text:p>
   <text:p text:style-name="P135">ACM KDD <text:span text:style-name="T245">‘</text:span><text:span text:style-name="T237">2</text:span>3<text:span text:style-name="T237"> – </text:span>Graph Mining I</text:p>
   <text:p text:style-name="P136"><text:span text:style-name="T247">SIAM MDS </text:span><text:span text:style-name="T245">‘</text:span><text:span text:style-name="T237">22 – </text:span><text:span text:style-name="T247">Algorithms</text:span></text:p>
   <text:p text:style-name="P136"><text:span text:style-name="T237">ACM KDD </text:span><text:span text:style-name="T245">‘</text:span><text:span text:style-name="T237">22 – Classification and Clustering</text:span></text:p>
   <text:p text:style-name="P137">ACM WSDM <text:span text:style-name="T245">‘2</text:span>2<text:span text:style-name="T245"> – </text:span>Web Search</text:p>
   <text:p text:style-name="P138">ACM KDD ‘2<text:span text:style-name="T248">1</text:span> – <text:span text:style-name="T248">Theory: Learning and Generalization</text:span></text:p>
   <text:p text:style-name="P139"><text:soft-page-break/><text:span text:style-name="T247">SIAM </text:span>SDM <text:span text:style-name="T249">‘</text:span>21<text:span text:style-name="T249"> – </text:span>Foundations II</text:p>
   <text:p text:style-name="P140">IEEE ICDM ‘20 – Graph Mining II</text:p>
   <text:p text:style-name="P141">ACM KDD ‘20 – Data Mining Methods</text:p>
   <text:p text:style-name="P142">WWW’20 – Social Network Analysis III</text:p>
   <text:p text:style-name="P143"><text:span text:style-name="T247">SIAM </text:span>SDM ‘19 – Patterns</text:p>
   <text:p text:style-name="P120">ACM KDD ‘18 – Unsupervised Learning II</text:p>
   <text:p text:style-name="P120">ACM KDD ‘17 – Graphs I</text:p>
   <text:p text:style-name="P120">ACM KDD ‘16 – Graphs I</text:p>
   <text:p text:style-name="P120">IEEE ICDM ‘16 – Theory</text:p>
   <text:p text:style-name="P120">ECML PKDD ‘16 – Graphs and Social Networks 1</text:p>
   <text:p text:style-name="P120">WWW ‘16 – Social Networks and Graph Analysis 1</text:p>
   <text:p text:style-name="P144">ACM KDD ‘15 – Social and Graphs 4</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">Grant Reviewing</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P120">NSF <text:span text:style-name="T250">Panelist 2017, 2023</text:span></text:p>
   <text:p text:style-name="P120">Sigma Delta Epsilon (Graduate Women in Science) National Fellowship</text:p>
   <text:p text:style-name="P120">Grace Hopper Conference Scholarship 2016, 2017</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">DEPARTMENTAL / UNIVERSITY SERVICE</text:p>
   <text:p text:style-name="P145"/>
   <text:p text:style-name="P146">Data Science Initiative, Amherst College <text:span text:style-name="T251">– </text:span>Inaugural Director, 1/2024 <text:span text:style-name="T251">– </text:span>Ongoing</text:p>
   <text:p text:style-name="P147">Faculty Committee on Student Fellowships, Amherst <text:span text:style-name="T252">C</text:span>ollege – Faculty Representative, 7/2022 – Ongoing</text:p>
   <text:p text:style-name="P148">Data Science Initiative Working Group, Amherst College – Dept. Representative, 1/201<text:span text:style-name="T253">9</text:span> – <text:span text:style-name="T254">O</text:span>ngoing</text:p>
   <text:p text:style-name="P149">Amherst College Association for Computing Machinery (ACM) Student Chapter – Sponsoring Faculty, <text:span text:style-name="T237">10/2019 – </text:span><text:span text:style-name="T255">O</text:span><text:span text:style-name="T237">ngoing</text:span></text:p>
   <text:p text:style-name="P150">Untenured Faculty Consultative Group, <text:span text:style-name="T253">Amherst College – Faculty Representative, 10/2021 – </text:span><text:span text:style-name="T251">6/2022</text:span></text:p>
   <text:p text:style-name="P151">Graduate Student Council, Brown University – President, 4/2011 – 12/2012</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"><text:soft-page-break/></text:p>
   <text:p text:style-name="P5">ADDITIONAL TRAINING</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P152">2014<text:tab/>Brown University Harriet W. Sheridan Center for Teaching and Learning</text:p>
   <text:p text:style-name="P153"><text:tab/>Teaching Certificate I: Reflective Teaching</text:p>
   <text:p text:style-name="P153">2012<text:tab/>Summer School on Massive Data Mining, IT University, Copenhagen, Denmark</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="P5">PROFESSIONAL MEMBERSHIPS</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal">Association for Computing Machinery (ACM), 2012 – present</text:p>
   <text:p text:style-name="normal"><text:tab/>Special Interest Group on Knowledge Discovery from Data (SIGKDD)</text:p>
   <text:p text:style-name="P154">Special Interest Group on Management of Data (SIGMOD)</text:p>
   <text:p text:style-name="P6"><text:tab/>Special Interest Group on Algorithms and Computation Theory (SIGACT)</text:p>
   <text:p text:style-name="normal">Institute of Electrical and Electronic Engineers (IEEE), 2012 – present</text:p>
   <text:p text:style-name="P6"><text:tab/>IEEE Computer Society</text:p>
   <text:p text:style-name="normal">Society for Industrial and Applied Mathematics (SIAM), 2012 – present</text:p>
   <text:p text:style-name="normal"><text:tab/>SIAM Activity Group on Data <text:span text:style-name="T8">Science</text:span> (SIAG/<text:span text:style-name="T180">DS</text:span>)</text:p>
   <text:p text:style-name="normal"/>
   <text:p text:style-name="normal">The latest revision of this CV is available from http<text:span text:style-name="T8">s</text:span>://matteo.rionda.to/MatteoRiondato-CV.pdf</text:p>
   <text:p text:style-name="normal">This revision was created on <text:time style:data-style-name="N10041" text:time-value="2024-10-04T10:15:31.576925469">October 4, 2024</text:time></text:p>
  </office:text>
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