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<!DOCTYPE HTML>
<html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Sri Anumakonda</title>
<meta name="author" content="Sri Anumakonda">
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link rel="icon" href="images/sri_circle.png">
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<body>
<table style="width:100%;max-width:800px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
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<p style="text-align:center">
<name>Sri Anumakonda</name>
</p>
<p>I'm an autonomous vehicle researcher building in the intersection between computer vision and self-driving cars.
</p>
<p><strong>Current: </strong> studying robotics @cmu, member <a href="https://masason-foundation.org/en/">@Masason Foundation</a>, creating SLAM-based systems for long-term data association. updates coming soon!</p>
<p>
Prev slam research @ut austin and @<a href="tks.world">tks.world</a> where I worked with <a href="https://drive.google.com/file/d/1d69kVASHabK-QgBsqs6PCC0DvZmAf1pT/view?usp=sharing">Shell</a>, the <a href="https://drive.google.com/file/d/10uzAQPKv29LnMhb4ambhqwxYEYJBpd1o/view?usp=sharing">United Nations</a>, and <a href="https://docs.google.com/presentation/d/1U_cYppfCh1bwoDLMeSunpzHI8vO-qphlPx6Jmo-dO_s/edit?usp=sharing">Instacart</a>. Also am one of the youngest certified self-driving car engineers in the world, was <a href="https://www.youtube.com/watch?v=5JTAta6ZIb8">featured on Udacity</a> for the work I'm doing.
</p>
<p style="text-align:center">
<a href="mailto:[email protected]">Email</a>  / 
<a href="https://www.linkedin.com/in/srianumakonda/">Linkedin</a>  / 
<a href="https://twitter.com/srianumakonda">Twitter</a>  / 
<a href="https://github.com/srianumakonda/">Github</a>  / 
<a href="https://srianumakonda.medium.com/">Medium</a> / 
<a href="data/Resume - Sri Anumakonda.pdf">CV</a> / 
<a href="https://srianumakonda.substack.com/p/what-does-fulfillment-really-mean">2yr life update</a>
<!-- <a href="data/CV.pdf">CV</a>  /  -->
</p>
</td>
<td style="padding:2.5%;width:40%;max-width:40%">
<img style="width:100%;max-width:100%" alt="profile photo" src="images/sri_circle.png" class="hoverZoomLink">
</td>
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</tbody></table>
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<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Research</heading>
<p>
My primary research interests are in the field of autonomous vehicles and robotics, more specifically towards computer vision for vision-based autonomy. You can find some of my projects in this space below. This is just an overview of the work I'm doing. For a full list, please check my <a href="https://github.com/srianumakonda/">Github</a>.
</p>
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<a href="https://arxiv.org/abs/2112.03288">
<papertitle>Dense Depth Priors for Neural Radiance Fields from Sparse Input Views</papertitle>
</a>
<br>
<a href="https://niessnerlab.org/members/barbara_roessle/profile.html">Barbara Roessle</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<a href="https://www.niessnerlab.org/">Matthias Nießner</a>
<br>
<em>CVPR</em>, 2022
<br>
<a href="https://arxiv.org/abs/2112.03288">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=zzkvvdcvksc">video</a>
<p></p>
<p>
Dense depth completion techniques applied to freely-available sparse stereo data can improve NeRF reconstructions in low-data regimes.
</p>
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<img src="images/hackprinceton.gif" alt="clean-usnob" width="160" height="160">
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<td width="75%" valign="middle">
<a href="https://prakash-shekhar.github.io/Bartimaeus/">
<papertitle>Bartimaeus: Stealing Vision Back - <b style="color:red;">HACKPRINCETON 2024 FINALIST + HEALTHCARE TRACK WINNER</b></papertitle>
</a>
<br>
October 2024
<br>
<a href="https://github.com/prakash-shekhar/Bartimaeus">Github</a>
/
<a href="https://prakash-shekhar.github.io/Bartimaeus/">Website</a>
<br>
<p>Created state-of-the-art pre-trained computer vision models + greedy-based path planning algorithm to navigate indoor enviroments for the visually impaired.</p>
</td>
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<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/hackcmu.gif" alt="clean-usnob" width="160" height="160">
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<td width="75%" valign="middle">
<a href="https://github.com/srianumakonda/DebateZero">
<papertitle>DebateZero: The Future of Debate Analysis - <b style="color:red;">HACKCMU 2024 OVERALL WINNER</b></papertitle>
</a>
<br>
October 2024
<br>
<a href="https://github.com/srianumakonda/DebateZero">Github</a>
<!-- /
<a href="https://twitter.com/srianumakonda/status/1488263295924682754">Tweet</a> -->
<br>
<p>Used spectral analysis, landmark detection, mathematical modelling, and eye tracking to gain insights on debates and identify misinformation and bias.</p>
</td>
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<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/semseg.gif" alt="clean-usnob" width="160" height="160">
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<td width="75%" valign="middle">
<a href="https://github.com/srianumakonda/Semantic-Segmentation-CUDA">
<papertitle>CUDA-Optimized Semantic Segmentation for Autonomous Vehicles</papertitle>
</a>
<br>
February 2023 - May 2023
<br>
<a href="https://github.com/srianumakonda/Semantic-Segmentation-CUDA">Github</a>
<!-- /
<a href="https://twitter.com/srianumakonda/status/1488263295924682754">Tweet</a> -->
<br>
<p>Leveraging CUDA + OpenCV + PyTorch's C++ API (LibTorch) using TorchScript to run semantic segmentation at the highest FPS possible</p>
</td>
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<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/rl.gif" alt="clean-usnob" width="160" height="160">
</td>
<td width="75%" valign="middle">
<a href="https://srianumakonda.medium.com/everything-you-need-to-know-about-reinforcement-learning-in-80minutes-4cd5a365e340">
<papertitle>Creating Autonomous Vehicles with Deep-Q Networks</papertitle>
</a>
<br>
January 2022 - February 2022
<br>
<a href="https://srianumakonda.medium.com/everything-you-need-to-know-about-reinforcement-learning-in-80minutes-4cd5a365e340">RL Article</a>
/
<a href="https://twitter.com/srianumakonda/status/1488263295924682754">Tweet</a>
<br>
<p>Leveraged Reinforcement Learning algorithms to help train a self-driving agent to drive in a highway environment [using discrete controls].</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/end2end.gif" alt="clean-usnob" width="160" height="160">
</td>
<td width="75%" valign="middle">
<a href="https://srianumakonda.notion.site/End2End-Self-Driving-a3e063810d164ea982a4157b0fc8e403">
<papertitle>End2End Learning for Lateral Control</papertitle>
</a>
<br>
November 2021 - January 2022
<br>
<a href="End2End Learning for Lateral Control">Research Proposal</a>
/
<a href="https://twitter.com/srianumakonda/status/1460799908848582656">Tweet</a>
<br>
<p>Used Deep Convolutional Networks to control self-driving steering, read more than 60 papers in the space, and met some really smart people from the <a href="https://wayve.ai">wayve.ai</a> + <a href="https://comma.ai">comma.ai</a> team!</p>
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<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/datagan.gif" alt="clean-usnob" width="160" height="160">
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<td width="75%" valign="middle">
<a href="https://srianumakonda.medium.com/datagan-leveraging-synthetic-data-for-self-driving-vehicles-6e629968a567">
<papertitle>DataGAN: Leveraging Synthetic Data for Self-Driving Vehicles</papertitle>
</a>
<br>
September 2021 - October 2021
<br>
<a href="https://srianumakonda.medium.com/datagan-leveraging-synthetic-data-for-self-driving-vehicles-6e629968a567">Medium article</a>
/
<a href="https://github.com/srianumakonda/DataGAN">Github</a>
<br>
<br>
<p>Using DC-GANs to create synthetic data that can be used to train + validate the robustness of autonomous vehicles. End goal is to apply to extrapolate the data pool we have for adverse driving scenarios/any situations where limited data is available.</p>
</td>
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<img src="images/lanedetection.png" alt="clean-usnob" width="160" height="160">
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<td width="75%" valign="middle">
<a href="https://docs.google.com/document/d/1OuxaXQpUpcLNjtkKfwoKxoGowcQBLdpPBIVTuhTsvDs/edit?usp=sharing">
<papertitle>Convolutional-LSTMs for Lane Detection</papertitle>
</a>
<br>
July 2021 - August 2021
<br>
<a href="https://docs.google.com/document/d/1OuxaXQpUpcLNjtkKfwoKxoGowcQBLdpPBIVTuhTsvDs/edit?usp=sharing">Project abstract</a>
/
<a href="https://github.com/srianumakonda/ConvLSTMs-Lane-Detection">Github</a>
<br>
<br>
<p>Implemented <a href="https://arxiv.org/pdf/1903.02193.pdf">this paper</a> from scratch with just my knowledge of Python and stackoverflow. Focusing on managing spatio-temporal image data for successful training of lane detection. Lanes don't change every single frame, so why can't we take in a few input frames and be able to successfully predict lane lines? Note: Github repository is not up to date as I have been unable to locate some of the files as part of training but the ConvLSTM model and training loop is created (and formatted nicely!).</p>
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<img src="images/sdcar.gif" alt="clean-usnob" width="160" height="160">
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<a href="https://docs.google.com/document/d/1OuxaXQpUpcLNjtkKfwoKxoGowcQBLdpPBIVTuhTsvDs/edit?usp=sharing">
<papertitle>Building a self-driving car!</papertitle>
</a>
<br>
May 2021
<br>
<a href="https://srianumakonda.medium.com/building-a-real-self-driving-car-1fc4c5fd2395">Medium article</a>
/
<a href="data/sdengineer.pdf">Certificate</a>
/
<a href="https://github.com/srianumakonda/CarND-Capstone-Master">Github</a>
<br>
<br>
<p>Used my knowledge throughout the Udacity Self-Driving Nanodegree [from perception and sensor fusion of LiDAR and radar sensors to polynomial trajectory generation] to create my capstone project; an autonomous vehicle capable of driving in simulation (using waypoitns). I built <a href="https://srianumakonda.medium.com/learning-to-drive-from-a-self-driving-car-a4dda9eb2307">trajectory algorithms</a>, <a href="https://medium.com/mlearning-ai/who-and-where-are-we-in-this-world-d5636f58455c">localization algorithnms</a>, and <a href="https://medium.com/analytics-vidhya/the-true-beauty-of-extended-kalman-filters-32e0c08d9258">kalman filters</a> to name a few of the projects I built!</p>
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<a href="https://srianumakonda.medium.com/pairing-lane-detection-with-object-detection-665b30462952">
<papertitle>Pairing Lane Detection with Object Detection</papertitle>
</a>
<br>
March 2021
<br>
<a href="https://srianumakonda.medium.com/pairing-lane-detection-with-object-detection-665b30462952">Medium article</a>
/
<a href="https://github.com/srianumakonda/Advanced-Lane-Detection-and-Object-Detection">Github</a>
<br>
<br>
<p>Creating a custom lane detection pipeline w/ Gaussian Filters + Polynomial fitting along with object detection using sliding windows w/ SVMs with the use of pure Machine Learning.</p>
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<heading>Updates</heading>
<p>
Want them in your inbox? Add your email <a href="https://srianumakonda.substack.com/p/coming-soon?s=w">here</a>.
<ul>
<li>
<a href="https://srianumakonda.substack.com/p/becoming-a-free-bird?s=w">January 2022</a>
</li>
<li><a href="https://srianumakonda.substack.com/p/2021-annual-letter-sri-anumakonda?s=w">December 2021</a></li>
</ul>
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Template from <a href="https://jonbarron.info/">Jon Barron</a>
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