Scholar
Syamantak Kumar
Google Scholar ID: lNVTz20AAAAJ
CS PhD, UT Austin
Citations & Impact
Citations
84
H-index
4
i10-index
2
Publications
13
Co-authors
16
list available
Publications
Resume (English only)
Academic Achievements
- 1. September 2025, selected for the Amazon AI PhD Fellowship
- 2. Sept 2023, paper 'Streaming PCA for Markovian Data' accepted as a Spotlight (Top ~3%) at NeurIPS 2023
- 3. Jan 2021, paper 'From Machine Translation to Code-Switching : Generating High-Quality Code-Switched Text' accepted in ACL-IJCNLP 2021
- 4. Feb 2019, paper 'A comparison of open source libraries ready for 3D reconstruction of wounds' accepted in SPIE Medical Imaging 2019
- 5. Multiple papers published in top conferences such as NeurIPS 2025, COLT 2025, UAI 2025, NeurIPS 2024
Research Experience
- 1. Summer 2024, research intern at Google Deepmind, Bengaluru, working with Dheeraj on Score Matching for Diffusion models
- 2. 2018, worked with Prof. Thomas Deserno on Medical Informatics and Imaging
Education
- 1. PhD (Computer Science), UT Austin, Advisors: Prof. Purnamrita Sarkar and Prof. Kevin Tian
- 2. MS (Computer Science), UT Austin
- 3. Undergraduate, IIT Bombay, Computer Science and Engineering Department, worked with Prof. Suyash Awate on Medical Imaging and with Prof. Preethi Jyothi on NLP for Code-switching
Background
- Research interests lie at the intersection of statistics and machine learning, designing machine learning algorithms with provable guarantees of convergence and correctness, and quantifying the computational and statistical aspects of state-of-the-art deep learning methods. Enjoys studying the applications of high-dimensional statistics, optimization, and probability theory to real-world problems.
Miscellany
- Worked as a software engineer in the Google Maps team; personal interests not mentioned
