NVIDIA Awards $50,000 Fellowships to Ph.D. Students for GPU Computing Research

Now in its 20th year, the NVIDIA Graduate Fellowship Program has to date awarded more than $5 million to support nearly 175 students’ work spanning deep learning, robotics and programming systems.
December 4, 2020 by Sylvia Chanak

For 20 years running, NVIDIA has supported graduate students doing GPU-based work through the NVIDIA Graduate Fellowship Program. Today we’re announcing the latest awards of up to $50,000 each to five Ph.D. students involved in GPU computing research.

Selected from more than 350 applicants from a host of countries, the five awardees will participate in a summer internship preceding the fellowship year. The work they’re doing puts them at the forefront of GPU computing, with fellows tackling projects in machine learning, computer vision, robotics and programming systems.

“Our fellowship recipients are among the most talented graduate students in the world,” said NVIDIA Chief Scientist Bill Dally. “They’re working on some of the most important problems in computer science, and we’re delighted to support their research.”

The NVIDIA Graduate Fellowship Program is open to applicants worldwide.

Our 2021-2022 fellows are:

  • Krishna Murthy Jatavallabhula, Université de Montréal — Deeply intertwining “classical” approaches to computer vision and robotics with modern machine learning.
  • Rohan Sawhney, Carnegie Mellon University — Designing algorithms for geometric computing, taking inspiration from fields such as differential geometry, stochastic calculus and control theory.
  • Sana Damani, Georgia Institute of Technology — Using compiler optimizations to help programmers of parallel machines exploit GPU hardware features to automatically obtain the best performance for their applications.
  • Thierry Tambe, Harvard University — Optimizing natural language processing at the algorithm, hardware architecture and solid-state layers.
  • Ye Yuan, Carnegie Mellon University — Creating next-generation perception systems capable of accurately modeling the physical world and reasoning about the behavior and interaction of various agents such as humans, robots and vehicles.

Our 2021-2022 finalists are:

  • Alexander Sax, University of California, Berkeley
  • Hanrui Wang, Massachusetts Institute of Technology
  • Ji Lin, Massachusetts Institute of Technology
  • Yunzhu Li, Massachusetts Institute of Technology
  • Zhiqin Chen, Simon Fraser University