Post-Graduation:
[Jul 2025] Attending ICML in Vancouver. Come say Hi at our poster session!
[Apr 2025] Presenting a talk at PORTAL (Stanford Center for Portable Accelerated Learning) titled "Compressing LLMs for Efficient Inference: Recent Advances in Low-Rank Methods, Quantization, and Structured Sparsity" [Link]
[Nov 2024] Releasing our latest work on compressing LLMs using low-precision and low-rank decomposition! Check out our new algorithm CALDERA here. Featuring on [Princeton Engineering News] and Stanford EE News.
[Oct 2024] Our recent work on privacy-preserving distributed mean estimation over intermittently-connected networks is published in IEEE TSP! Check it out here.
[July 2024] Joined Amazon Web Services (AWS), Santa Clara as an Applied Scientist II. Looking forward to exploring and pushing the limits for resource-efficient usage of Large Language Models.
Graduate:
[June 2024] Graduated with PhD degree from Stanford Electrical Engineering. Does it mean I can think now? 🤔 Check out my thesis on Algorithmic strategies for learning and inference in resource-constrained environments and let me know the answer!
[Dec 2023] Presenting our work "Matrix Compression via Randomized Low Rank and Low Precision Factorization" at NeurIPS 2023, New Orleans.
[June 2023] Presenting our work "Collaborative Mean Estimation over Intermittently Connected Networks with Peer-To-Peer Privacy" at ISIT 2023, Taipei, Taiwan.
[June 2023] Presenting our work "Low Precision Representations for High Dimensional Models" at ICASSP 2023, Rhodes Island, Greece.
[Dec 2022] Presenting our work "ColRel: Collaborative Relaying for Federated Learning over Intermittently Connected Networks" at FL-NeurIPS: Workshop on Federated Learning: Recent Advances and New Challenges (in Conjunction with NeurIPS 2022). [Link]
[Nov 2022] Giving a short presentation at IEEE Information Theory Workshop (ITW), 2022. (Student Research Presentations at the themed session: Communication-efficient gradient compression and coding in distributed learning ). [Video]
[Oct 2022] Will be spending a week at the lovely Carnegie Mellon University and giving a talk on our recent work: Collaborative Relaying for Federated Learning over Intermittently Connected Networks. [Preprint]
[Aug 2022] Will be attending the North American School in Information Theory at UCLA. Come say Hi! at the poster session if you're here!
[Aug 2022] Our work on "Efficient Randomized Subspace Embeddings for Distributed Optimization under a Communication Budget" with Mert Pilanci and Andrea Goldsmith will appear in the IEEE Journal on Selected Areas in Information Theory. [IEEE Xplore] [Full paper]
[Aug 2022] Will be spending the next few weeks at the beautiful Princeton University.
[July 2022] Got recognized for the (fun) IEEE Information Theoretic Duets competition at ISIT, 2022 with Arpan Mukherjee. Presented a teaser video on Active Learning based on the work of Shekhar et al.
[June 2022] Our work on "Semi-Decentralized Federated Learning with Collaborative Relaying" with Michal Yemini, Emre Özfatura, Deniz Gündüz, and Andrea Goldsmith is being presented at IEEE International Symposium on Information Theory (ISIT). [Paper] [Full version]
[May 2022] Giving a talk on "Mitigating Connectivity Failures in Federated Learning via Collaborative Relaying" at Air Force Center of Excellence, Rhodes Information Initiative at Duke, Duke University. [Link] [Slides]
[Feb 2022] Our work on "Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams" with Erdem Bıyık, Anusha Lalitha, Andrea Goldsmith, and Dorsa Sadigh is being presented at 36th AAAI Conference on Artificial Intelligence. [Website] [Video]
[Jan 2022] Giving a talk on "Randomized Subspace Embeddings for Learning Under Resource Constraints" at Air Force Center of Excellence, Rhodes Information Initiative at Duke, Duke University. [Link] [Slides]
[Nov 2021] Presenting a poster of our work on "Fundamental Limits and Efficient Algorithms for Distributed Optimization under Communication Constraints" at Stanford SystemX Alliance Fall Conference, Stanford University, Nov 2021 [Link] [Video] [Poster]
[Sep 2021] Our work on "Decentralized Optimization over Noisy, Rate-Constrained Networks" with Stefano Rini, Milind Rao, and Andrea Goldsmith got accepted to the IEEE Journal on Selected Areas in Communications. [IEEE Xplore]
[Jun 2021] Joined Amazon Alexa AI as an Applied Science Intern.
[Jun 2021] Presented our work on "Decentralized Optimization over Noisy, Rate-Constrained Networks" virtually at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). [Paper]
[Aug 2020] Completed Stanford EE Quals. Officially a Ph.D. candidate now.
[Sep 2019] Received the Irving T. Ho and Oswald G. Villard Jr. Engineering Graduate Fellowships.
[Sep 2019] Excited to be a part of Wireless Systems Lab and Information Systems Lab at Stanford.
Undergraduate:
[Aug 2019] Graduated from IIT Kharagpur with the Prime Minister of India Gold Medal and Best Undergraduate Thesis Award.
[Oct 2018] Presented our work on Sparsity-Aware MIMO Radar Imaging at SiPS, 2018 held in Cape Town, South Africa. [Paper]
[May 2018] Interned at Carnegie Mellon University hosted at WiTech Lab by Prof. Swarun Kumar.
[Feb 2018] Was offered the IIT Kharagpur Foundation of USA Scholarship for pursuing a summer internship.
[Jan 2018] Was awarded the Technology Alumni Association scholarship by IIT Kharagpur for maintaining top department rank in E&ECE.
[Jun 2017] Selected to be a part of the youth delegation from Ministry of Youth Affairs and Sports, Govt. of India, to China.
[May 2017] Interned at Texas Instruments R&D, Bengaluru.
[May 2016] Interned at Indian Institute of Science (IISc) hosted at Centre for Nano Science and Engineering (CeNSE) by Prof. Digbijoy N. Nath .
Others:
[Aug 2013] Received Kishore Vaigyanik Protsahan Yojana (KVPY) (Young Scientist Incentive Plan) Fellowship, Govt. of India.
[Dec 2012] Qualified (top-1%) Regional Mathematics Olympiad (RMO) , National Board of Higher Mathematics, Govt. of India.
[May 2010] Qualified for National Talent Search Examination (NTSE) Fellowship, Govt. of India.