Nvidia announced that it will award research scholarships of up to US $50,000 each to five doctoral students.
CTOnews.com, May 10, according to the official WeChat account of NVIDIA, the NVIDIA Graduate Scholarship Program has so far awarded US $6 million (CTOnews.com Note: about RMB 41.52 million) to nearly 200 students to promote research in the fields of machine learning, computer vision, robotics and system programming. NVIDIA announced that it will award scholarships of up to US $50, 000 each (currently about RMB 346000) to five doctoral students participating in the study, covering all areas of computing innovation.
The five winners will take part in a summer internship before the scholarship year, and their research work puts them at the forefront of accelerated calculation. projects involved include deep learning, robotics, computer vision, computer graphics, circuits, self-driving cars, system programming, and so on.
The NVIDIA Graduate Fellowship is open to applicants from all over the world.
The winners of the 2023-2024 Graduate Fellowship are as follows:
Eric Chan of Stanford University: generate models for 3D object and scene design. This research work enables AI to synthesize objects and scenes for content creation or to reconstruct real environments for 3D perception. Specific applications include realistic 3D avatars, text-object generation, computer vision robots and so on.
Cornell University's Katie Luo: focus on the perception of self-driving cars, the goal is to bring self-driving technology to different end users; explore more channels of information to adapt to a variety of real scenarios in an efficient way to use data.
Rohan Yadav of Stanford University: speed up the software development of distributed and accelerated computing platforms by building parallel programming languages and systems, focusing on dense and sparse tensor computing systems on distributed machines.
Yicheng Zhu of the University of California, Berkeley: explore ultra-high performance hybrid switched capacitor voltage regulating modules for ultra-high power GPU. The module can achieve efficient, ultra-compact vertical power supply and fast transient response.
Zongyi Li of the California Institute of Technology: dedicated to the development of deep learning methods (neural operators) for partial differential equations and scientific applications.
The finalists for the 2023-2024 Graduate Fellowship are as follows:
Bobbi Yogatama, University of Wisconsin
Charles Gouert, University of Delaware
Chen Wang, Stanford University
Cheng Chi, Columbia University
Ethan Tseng, Princeton University
Hong-Xing (Koven) Yu, Stanford University
Jiarui Xu, University of California, San Diego
Kaidi Cao, Stanford University
Shikhar Bahl, Carnegie Mellon University
Songwei Ge, University of Maryland
