Rishi Sharma
Scholar

Rishi Sharma

Google Scholar ID: jUfDXOsAAAAJ
PhD Student, École Polytechnique Fédérale de Lausanne (EPFL)
Distributed SystemsMachine LearningPrivacyDecentralized LearningFederated Learning
Citations & Impact
All-time
Citations
116
 
H-index
5
 
i10-index
3
 
Publications
20
 
Co-authors
0
 
Resume (English only)
Academic Achievements
  • Papers Published: 'Low-Cost Privacy-Aware Decentralized Learning' accepted for publication in Proceedings on Privacy Enhancing Technologies 2025.3; 'Boosting Asynchronous Decentralized Learning with Model Fragmentation' accepted for oral presentation at ACM Web Conference 2025; 'Fair Decentralized Learning' accepted for IEEE SaTML 2025; 'Revisiting Ensembling in One-Shot Federated Learning' accepted as a poster at NeurIPS 2024; 'Noiseless Privacy-Preserving Decentralized Learning' accepted for publication in Proceedings on Privacy Enhancing Technologies 2025.1; Received Doc.Mobility Grant 2024 from EPFL.
Research Experience
  • Summer 2025 Research Intern at Microsoft Research Cambridge, working on deterministic security guardrails for autonomous AI agents; Recently completed a research visit at the Camera Culture Group of the MIT Media Lab, supervised by Prof. Ramesh Raskar, focusing on enabling collaborative AI in open decentralized networks.
Education
  • Ph.D. in Computer Science, École Polytechnique Fédérale de Lausanne (EPFL); Visiting Ph.D. in Computer Science, Massachusetts Institute of Technology (MIT); B.Tech. in Computer Science and Engineering, Indian Institute of Technology (IIT) Mandi; Exchange Student in Computer Science, RWTH Aachen University.
Background
  • Research Interests: Distributed Systems, Artificial Intelligence, Machine Learning, Decentralized Learning, Privacy and Security. Professional Field: Computer Science. Bio: Rishi Sharma is a Ph.D. candidate at the Scalable Computing Systems Lab at EPFL, under the supervision of Prof. Anne-Marie Kermarrec. His research focuses on designing efficient and privacy-preserving systems for Decentralized and Federated Learning.
Miscellany
  • Personal Interests: Not explicitly mentioned.
Co-authors
0 total
Co-authors: 0 (list not available)