Satyam Srivastava
Researcher | Engineer | Curious Human
I’m currently pursuing my MS in Computer Science at UC San Diego, focusing on machine learning, computer vision, and cognition-inspired AI.
Previously at Cohesity, I built scalable distributed infrastructure, implemented REST APIs, enhanced system reliability through cross-functional collaboration, and developed a cutting-edge backup adapter with CI/CD integration, achieving high scalability, resilience, and maintainability.
My journey has taken me from BITS Pilani, to a DAAD Scholarship at TU Braunschweig where I developed a multimodal cECG dataset and deep learning reliability model, and to UC San Diego as a Khorana Scholar for my undergraduate thesis, where I built C-Shenron, a realistic radar simulation framework for autonomous driving research.
I'm passionate about building reliable systems and solving problems at the intersection of software engineering and intelligent decision-making — from designing scalable infrastructure to making AI models more interpretable, scalable, and human-aligned.
Domains I work in:
🧠 Cognitive-Inspired RL with Episodic Memory (Texas State University)
Enhanced Deep Q-Networks by integrating working memory and episodic replay, improving learning efficiency and stability in complex environments.
💻 Compiler for ERPLAG Programming Language (CS F363)
Built a compiler with efficient lexer, memory-optimized AST (80% compression), and a type-checker detecting 95% of errors.
📚 Library Management System (CS F212)
Designed a MySQL-based system simulating BITS library operations with seamless book tracking and inventory management.
🏥 Detecting Multi-Drug Resistant TB from Chest X-rays
Developed a CNN model classifying drug-sensitive and drug-resistant TB strains, improving benchmark accuracy from 66% to 98%.
🏎️ C-Shenron: A Realistic Radar Simulation Framework for CARLA (VTC 2025)
Developed a radar simulation framework enabling multimodal fusion for autonomous driving.
Link
🏎️ Demo Abstract: C-Shenron, ACM SenSys 2025
Demonstrated CARLA-based radar simulation for research and benchmarking. Link
🧠 CEMDQN: Cognitive-inspired Episodic Memory in DQNs, IJCNN 2023
Presented in-person in Queensland, Australia, introducing episodic memory improvements in reinforcement learning. Link
🏥 Reliability Estimation of Armchair-Based Capacitive ECG, SPIE Medical Imaging 2023
Developed deep learning model to assess cECG signal reliability using video-based pose estimation. Link
🎓 Khorana Scholarship
Awarded by DBT, IUSSTF, and WINStep Forward to undertake research at leading U.S. universities.
🎓 BITSAA Udaan Scholarship
Supported participation in IJCNN conference by covering travel and registration expenses.
🎓 IEEE CIS Travel Grant
Received for presenting at an IEEE Computational Intelligence Society-sponsored IJCNN conference.
🎓 DAAD-WISE Scholarship
Awarded by DAAD for a research internship at Technical University of Braunschweig, Germany.
🎓 Mitacs GRI Award
Globalink Research Internship award for summer research at University of Toronto, Canada.
🎓 Birla Institute of Technology and Science Best Paper Award
Recognized for research rigor and academic excellence.
🎓 BITS Merit-cum-Need Scholarship
Consistently awarded for academic excellence across all semesters.
International Joint Conference on Neural Networks (IJCNN) 2023
Organized by IEEE CIS & INNS | Queensland, Australia.
Presented research on cognitive-inspired episodic memory in Deep Q-Networks and engaged with experts in neural network developments.
🌟 BITS2Research Alumni Mentorship Program (Nov 2023 – Ongoing)
Mentoring undergraduate students in research exploration, project development, and career pathways while fostering collaboration and impactful learning.
👨🏫 CS F213: Object Oriented Programming (Jan 2023 – May 2023)
Undergraduate Teaching Assistant – Prof. Avinash Gautam.
Designed weekly lab sheets and guided students during lab hours, assisting with problem-solving and concept clarification.
👨🏫 CS F222: Discrete Structures for Computer Science (Aug 2022 – Dec 2022)
Undergraduate Teaching Assistant – Prof. Sundaresan Raman.
Prepared weekly practice sheets and helped students understand course concepts during tutorials.
👨🏫 CS F111: Computer Programming (Aug 2022 – Dec 2022)
Undergraduate Teaching Assistant – Prof. Jagat Sesh Challa.
Assisted in designing lab sheets and guided students through exercises and concept clarification.
🤝 Peer Mentorship Program (Aug 2020 – May 2021)
Led a peer mentorship initiative, supporting fellow students academically and personally through one-on-one sessions and group discussions.
Always open to conversations about ideas, collaborations, or just interesting questions. Best way to reach me? Email me or connect on LinkedIn.