Deepak Narayanan Sridharan

About

I am a second year PhD student at ETH Zurich, fortunate to be advised by Professor David Steurer.

I am broadly interested in problems arising at the intersection of statistics and theoretical computer science. More recently, I have been thinking about robust and private statistics.

Publications

Author order follows each paper's published version. \((\alpha\text{-}\beta)\) indicates alphabetical author order; \(*\) indicates equal contribution.

• Outlier-robust Mean Estimation near the Breakdown Point via Sum-of-Squares Hongjie Chen, Deepak Narayanan Sridharan, and David Steurer SODA 2025 \((\alpha\text{-}\beta)\) • arXiv • SIAM
  Awarded ETH Medal for Outstanding Master's Thesis
• IGLU: Efficient GCN Training via Lazy Updates S. Deepak Narayanan^*, Aditya Sinha^*, Prateek Jain, Purushottam Kar, and Sundararajan Sellamanickam ICLR 2022 • arXiv • OpenReview
• A Toolkit for Spatial Interpolation and Sensor Placement S. Deepak Narayanan, Zeel B. Patel, Apoorv Agnihotri, and Nipun Batra SenSys 2020 poster • ACM
• [Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers Varun Gohil^*, S. Deepak Narayanan^*, and Atishay Jain^* ReScience C 2020 • ReScience C • OpenReview
• Active Learning for Air Quality Station Location Recommendation S. Deepak Narayanan, Apoorv Agnihotri, and Nipun Batra CoDS-COMAD 2020 • ACM

Teaching

Courses at ETH Zurich.

• Algorithms and Probability (S25, S26)
• Algorithms and Data Structures (F24, F25)
• Algorithmic Foundations of Data Science (S23, S24)
• Deep Learning (F23)
• Computational Intelligence Lab (S23)