Scholar
Akash Kumar
Google Scholar ID: WFiCe9QAAAAJ
PhD student at University of California San Diego
Citations & Impact
Citations
30
H-index
3
i10-index
1
Publications
9
Co-authors
13
list available
Contact
Publications
Resume (English only)
Academic Achievements
- 1. One paper to appear in JMLR 2025; 2. Two papers accepted, one each in ICML 2025 and COLT 2025; 3. Presented work at Princeton University and Yale University (Theory Seminar); 4. Recipient of several fellowships, including Jacobs School of Engineering Fellowship, Crerar Fellowship (awarded as the strongest admit to the PhD program at UChicago CS, declined), Max Planck Institute Fellowship, and Chennai Mathematical Institute Scholastic Fellowship.
Research Experience
- 1. Research Scientist Intern/Fellow at Adobe Research (San Jose, CA, USA); 2. Fellow at Max Planck Institute for Software Systems (Saarbrücken, Germany); 3. Research Scientist Intern/Fellow at IBM Research (Bengaluru, IN).
Education
- 1. Ph.D. in Computer Science at UCSD, co-advised by Prof. Sanjoy Dasgupta and Prof. Misha Belkin; 2. MSc in Computer Science from Chennai Mathematical Institute (CMI, India); 3. BSc in Mathematics and Computer Science from CMI, India.
Background
- A doctoral candidate in the Computer Science department, with a focus on advancing both the theoretical foundations and practical applications of machine learning. His interests include statistical machine learning, algorithm design, interactive learning, optimization, and the theoretical aspects of deep learning. He aims to leverage tools from probability theory, analysis, differential geometry, and statistics to rigorously study the computational and statistical efficiency of learning algorithms.
Miscellany
- Interested in exploring problems such as learning distance functions, kernel machines, emergent behavior in neural models, and generalization with non-parametric models.
