I'm a software engineer and AI researcher passionate about building intelligent systems and meaningful technology. My experience spans computer vision, reinforcement learning, generative AI, and more recently, music/audio. I enjoy collaborating on research, developing real-world applications, and occasionally making robots smarter (or at least funnier).

• BetterSearch
  Desktop app integrating LLMs, advanced RAG, and native OS functionality for file search and content indexing. Features text-to-SQL with osquery, device management, and both local/cloud LLM options.

• VidTune
  Generative AI web app for tailored music creation for videos, with genre, tempo, keyword, and mixing customization.

• Unified Local-Cloud Decision-Making
  Research codebase for residual reinforcement learning in embodied vision systems, balancing energy, latency, and safety by dynamic cloud-edge offloading. Presented at ECCV 2024.

• Autonomous Underwater Vehicle
  Led team to Singapore AUV Challenge finals. Developed navigation, vision, and electronics, and integrated the Sea-Thru water-removal algorithm for underwater object detection.

• ECCV 2024: Unified Local-Cloud Decision-Making via Residual Reinforcement Learning
• ETCCS 2020: Person Re-Identification by Analyzing Dynamic Variations in Gait Sequences

• LossFunk — Independent Researcher (June 2025 – Present, Bangalore, India)
  Pursuing original research in AI and music (source separation).

• Human-to-Everything (H2X) Lab, Boston University — Visiting Researcher / Graduate Research Assistant (Mar 2023 – Mar 2025, Boston, MA)
  Enhanced vision-language models for autonomous driving, cloud-edge collaboration, state-of-the-art navigation metrics, crowd navigation environments, and multi-robot visual servoing.

• Boston University — Teaching Assistant (Jan 2024 – May 2024, Boston, MA)
  Assisted with courses on cyber-physical and IoT systems.

• Robert Bosch GmbH — Research Intern (Jan 2020 – June 2020, Bangalore, India)
  Open-set classification for rare objects, predictive maintenance algorithms.

• Center for Development of Advanced Computing (CDAC) — Research Intern (May 2019 – Oct 2019, Kolkata, India)
  Person re-identification via dynamic gait analysis; best accuracy on CASIA-B dataset.

• Ottometric Inc. — Software Engineering Intern (June 2023 – Aug 2023, Waltham, MA)
  Data summarization algorithms for Ottoviz platform, submodular optimization.

• Ignitarium Technology Solutions — Software Engineer (AI & ML) (Jan 2022 – July 2022, Bangalore, India)
  Inference optimization on accelerator chips, kernel development, workflow streamlining.

• Synopsys India — Software Engineer (Jan 2021 – Jan 2022, Bangalore, India)
  Data pipelines (Apache Spark), anomaly detection (BERT), log analysis systems.

• Thermo Fisher Scientific India Pvt. Ltd. — Summer Intern (May 2018 – July 2018, Hyderabad, India)
  ARM hardware upgrades, embedded C++, UI with Qt5 and Linux Yocto.

• Boston University
  M.S. in Computer Science (Sep 2022 – May 2024)

• IIITDM Kancheepuram
  B.Tech. + M.Tech. in Electronics and Communication Engineering (July 2015 – June 2020)

• Website: tensorsofthewall.com
• GitHub: github.com/tensorsofthewall
• LinkedIn: linkedin.com/in/sandeshbharadwaj97

“Hurricane Sandy” wasn’t a weather event — it was me, my spiky hair, and a guitar solo on stage.

Always curious. Occasionally sarcastic. Building the future, one line of code at a time.