Scholar
Vinod Raman
Google Scholar ID: Wn5QzOgAAAAJ
University of Michigan
Citations & Impact
Citations
94
H-index
5
i10-index
2
Publications
20
Co-authors
19
list available
Publications
Cited
0
Resume (English only)
Academic Achievements
- Supported by the National Science Foundation Graduate Research Fellowship (NSF GRFP) and the 2025 Apple Scholars in AI/ML PhD Fellowship. Published or submitted several papers, including 'Estimating the (Un)seen: Sample-dependent Mass Estimation' and 'Online Boosting for Multilabel Ranking with Top-k Feedback'.
Research Experience
- Interned at Apple in summer 2024 with Kunal Talwar and Hilal Asi, working on differentially private online learning. Returned to Apple early 2025, working on test-time alignment and efficient missing mass estimation with Kunal Talwar, Hilal Asi, and Satyen Kale. Research intern at Google Research in summer 2025, working on differential privacy, LLM evaluation, and synthetic data generation with Matthew Joseph, Travis Dick, and Umar Syed.
Education
- Ph.D. student in Statistics at the University of Michigan, advised by Ambuj Tewari; previously studied Computer Science and Chemical Engineering at UM, working with Mahdi Cheraghchi, Sindhu Kutty, and Andrej Lenert.
Background
- Research interests: Foundations of Machine Learning and Generative AI. Previously worked on online learning/bandits, adversarial robustness, and beyond-worst-case analysis for learning algorithms. Currently interested in all aspects of post-training for LLMs, particularly inference-time methods, differential privacy, and synthetic data generation.
Miscellany
- Email: vkraman [at] umich.edu. On the industry job market. Feel free to reach out if you think I might be a good fit!
