About
I’m pursuing a Ph.D. in Computer Science at the University of Massachusetts Amherst, under the guidance of Prof. Prashant Shenoy. As part of the Laboratory for Advanced System Software (LASS), I am currently working on the design of failure-aware model serving system for Foundation Models. More broadly, my research interests include Machine Learning and Artifical Intelligence, Distributed Inference and training, fault-tolerance and resource management on the Edge/IoT.
Prior to this, I have a 2.5+ years of experience as a Software Engineer at multiple firms including Deskera, Publicis Sapient and Boeing. I earned my Bachelors degree from the Indian Institute of Technology Madras (IITM) in 2020.
News
| May 2026 | Artifact Evaluator for OSDI 2026, Reviewer for * |
| Mar 2026 | Artifact Evaluator for MLSys 2026 |
| Jan 2026 | Reviewer for AISTATS 2026 |
| Oct 2025 | Presented our work on Edge ML resilience at IEEE Milcom 2025, Los Angeles |
| Sep 2025 | Considerations for Edge ML resilience accepted to IEEE Milcom 2025 |
| Jun 2025 | Multi-level ensemble Learning (MEL) is available on arXiv |
| Jul 2024 | Started my phd at UMass Amherst under Dr. Prashant Shenoy! |
| May 2024 | Received my Masters degree from UMass Amherst! |
Publications
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Gudipaty, Krishna Praneet, W. A. Hanafy, L. Wu, et al., “Practical considerations for failure resilient ml systems at the edge,” in MILCOM 2025 - 2025 IEEE Military Communications Conference (MILCOM)
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Gudipaty, Krishna Praneet, W. A. Hanafy, K. Ozkara, et al., “Mel: Multi-level ensemble learning for resource-constrained environments,” arXiv preprint arXiv:2506.20094, 2025
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A. Micciche, Gudipaty, Krishna Praneet, and S. Krastanov, “Quantum ldpc error correcting codes for use on 1d quantum dot arrays,” in APS March Meeting Abstracts, vol. 2024, S46–010
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