Scholar
Ramchandran Muthukumar
Google Scholar ID: XgswG9cAAAAJ
University of Chicago, Data Science Institute
Citations & Impact
Citations
71
H-index
4
i10-index
3
Publications
8
Co-authors
6
list available
Publications
Resume (English only)
Academic Achievements
- Featured Publications: 'Sparsity-aware generalization theory for deep neural networks', 'Adversarial robustness of sparse local Lipschitz predictors', and 'Randomized sketching algorithms for low-memory dynamic optimization'.
Research Experience
- Before starting his graduate studies, he was a research assistant at Cornell University supervised by Dr. Madeleine Udell, working on developing low-memory algorithms for PDE-optimization based on randomized sketching.
Education
- PhD in Computer Science (2019 - present), Johns Hopkins University; MSc in Mathematics (2018), BITS Pilani; B.E. in Computer Science (2018), BITS Pilani.
Background
- Interests: Learning Theory, Adversarial Robustness, High-dimensional Statistics, Optimization. Background: A fifth-year PhD Student in the Computer Science Department at Johns Hopkins University, advised by Dr. Jeremias Sulam. His work explores theoretical questions in evaluating machine learning models, focusing on generalization and robustness.
