NVIDIA Awards $60,000 Grants to 10 Ph.D. Students

<header class&equals;"entry-header">&NewLine;<div class&equals;"entry-title img-bg orientation-landscape">For 25 years&comma; the <a href&equals;"https&colon;&sol;&sol;research&period;nvidia&period;com&sol;graduate-fellowships" target&equals;"&lowbar;blank" rel&equals;"noopener">NVIDIA Graduate Fellowship Program<&sol;a> has supported graduate students doing outstanding work relevant to NVIDIA technologies&period; This month&comma; the program announced the latest awards of up to &dollar;60&comma;000 each to 10 Ph&period;D&period; students involved in research that spans all areas of computing innovation&period;<&sol;div>&NewLine;<&sol;header>&NewLine;<div class&equals;"entry-content">&NewLine;<p>Selected from a highly competitive applicant pool&comma; the awardees will participate in a summer internship preceding the fellowship year&period; Their work puts them at the forefront of accelerated computing — tackling projects in autonomous systems&comma; computer architecture&comma; computer graphics&comma; deep learning&comma; programming systems&comma; robotics and security&period;<&sol;p>&NewLine;<p>The NVIDIA Graduate Fellowship Program is open to applicants worldwide&period;<&sol;p>&NewLine;<p>The 2026-2027 fellowship recipients are&colon;<&sol;p>&NewLine;<ul>&NewLine;<li aria-level&equals;"1"><b>Jiageng Mao<&sol;b>&comma; University of Southern California — Solving complex physical AI problems by using diverse priors from internet-scale data to enable robust&comma; generalizable intelligence for embodied agents in the real world&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Liwen Wu<&sol;b>&comma; University of California San Diego — Enriching realism and efficiency in physically based rendering with neural materials and neural rendering&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Manya Bansal<&sol;b>&comma; Massachusetts Institute of Technology — Designing programming languages for modern accelerators that enable developers to write modular&comma; reusable code without sacrificing the low-level control required for peak performance&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Sizhe Chen<&sol;b>&comma; University of California&comma; Berkeley — Securing AI in real-world applications&comma; currently securing AI agents against prompt injection attacks with general and practical defenses that preserve the agent’s utility&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Yunfan Jiang<&sol;b>&comma; Stanford University — Developing scalable approaches to build generalist robots for everyday tasks through hybrid data sources spanning real-world whole-body manipulation&comma; large-scale simulation and internet-scale multimodal supervision&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Yijia Shao<&sol;b>&comma; Stanford University — Researching human-agent collaboration by developing AI agents that can communicate and coordinate with humans during task execution&comma; and designing new human-agent interaction interfaces&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Shangbin Feng<&sol;b>&comma; University of Washington — Advancing model collaboration&colon; multiple machine learning models&comma; trained on different data and by different people&comma; collaborate&comma; compose and complement each other for an open&comma; decentralized and collaborative AI future&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Shvetank Prakash<&sol;b>&comma; Harvard University — Advancing hardware architecture and systems design with AI agents built on new algorithms&comma; curated datasets and agent-first infrastructure&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Irene Wang<&sol;b>&comma; Georgia Institute of Technology — Developing a holistic codesign framework that integrates accelerator architecture&comma; network topology and runtime scheduling to enable energy-efficient and sustainable AI training at scale&period;<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Chen Geng<&sol;b>&comma; Stanford University — Modeling 4D physical worlds with scalable data-driven algorithms and physics-inspired principles&comma; advancing physically grounded 3D and 4D world models for robotics and scientific applications&period;<&sol;li>&NewLine;<&sol;ul>&NewLine;<p>The company also acknowledges the 2026-2027 fellowship finalists&colon;<&sol;p>&NewLine;<ul>&NewLine;<li><b>Zizheng Guo<&sol;b>&comma; Peking University<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Peter Holderrieth<&sol;b>&comma; Massachusetts Institute of Technology<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Xianghui Xie<&sol;b>&comma; Max Planck Institute for Informatics<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Alexander Root<&sol;b>&comma; Stanford University<&sol;li>&NewLine;<li aria-level&equals;"1"><b>Daniel Palenicek<&sol;b>&comma; Technical University of Darmstadt<&sol;li>&NewLine;<&sol;ul>&NewLine;<&sol;div>&NewLine;

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