In the realm of technological advancement, the NVIDIA Graduate Fellowship Program has been a beacon of support for graduate students dedicated to groundbreaking research in fields relevant to NVIDIA’s cutting-edge technologies. Celebrating its 25th year, the program has once again demonstrated its commitment to fostering innovation by announcing the recipients of its latest awards. This year’s fellowship offers up to $60,000 each to 10 exceptional Ph.D. students whose research spans the vast expanse of computing innovation.
These awardees, chosen from an exceptionally competitive pool of applicants, are set to embark on a summer internship preceding the fellowship year. Their research places them at the vanguard of accelerated computing, addressing intricate challenges in areas such as autonomous systems, computer architecture, computer graphics, deep learning, programming systems, robotics, and security. The NVIDIA Graduate Fellowship Program is renowned for its global reach, welcoming applicants from all corners of the world.
The Esteemed Fellowship Recipients for 2026-2027
- Jiageng Mao, University of Southern California
- Jiageng’s research focuses on solving complex physical AI problems. By leveraging diverse priors from internet-scale data, he aims to develop robust and generalizable intelligence for embodied agents operating in real-world environments.
- Liwen Wu, University of California San Diego
- Liwen is working on enhancing realism and efficiency in physically based rendering. Her research utilizes neural materials and neural rendering to push the boundaries of what is possible in computer graphics.
- Manya Bansal, Massachusetts Institute of Technology
- Manya is designing innovative programming languages specifically tailored for modern accelerators. Her work allows developers to write modular and reusable code without compromising on the low-level control necessary for optimal performance.
- Sizhe Chen, University of California, Berkeley
- Sizhe’s research is centered on securing AI applications in real-world scenarios. He is developing general and practical defenses to protect AI agents against prompt injection attacks, ensuring the agents maintain their utility.
- Yunfan Jiang, Stanford University
- Yunfan is focused on creating scalable methods to build generalist robots capable of performing everyday tasks. His approach involves integrating hybrid data sources, including whole-body manipulation, large-scale simulation, and internet-scale multimodal supervision.
- Yijia Shao, Stanford University
- Yijia’s research explores human-agent collaboration. She is developing AI agents capable of effective communication and coordination with humans during task execution, as well as designing innovative human-agent interaction interfaces.
- Shangbin Feng, University of Washington
- Shangbin is advancing model collaboration by enabling multiple machine learning models to work together. Trained on different data by different people, these models collaborate, compose, and complement each other, paving the way for an open, decentralized, and collaborative AI future.
- Shvetank Prakash, Harvard University
- Shvetank’s research is pushing the boundaries of hardware architecture and systems design. He is creating AI agents based on new algorithms, curated datasets, and agent-first infrastructure to enhance computational capabilities.
- Irene Wang, Georgia Institute of Technology
- Irene is developing a holistic codesign framework that integrates accelerator architecture, network topology, and runtime scheduling. Her goal is to enable energy-efficient and sustainable AI training at scale.
- Chen Geng, Stanford University
- Chen is modeling 4D physical worlds using scalable data-driven algorithms and physics-inspired principles. His work advances physically grounded 3D and 4D world models, which are crucial for robotics and scientific applications.
Recognizing the Fellowship Finalists
In addition to the awardees, the program also acknowledges the finalists who have demonstrated exceptional potential:
- Zizheng Guo, Peking University
- Peter Holderrieth, Massachusetts Institute of Technology
- Xianghui Xie, Max Planck Institute for Informatics
- Alexander Root, Stanford University
- Daniel Palenicek, Technical University of Darmstadt
A Legacy of Innovation and Support
Since its inception, the NVIDIA Graduate Fellowship Program has played a pivotal role in nurturing the next generation of innovators. By providing financial support and invaluable internship opportunities, the program empowers students to push the boundaries of what is possible in the world of computing.
NVIDIA’s commitment to fostering talent and innovation is evident not only through the fellowship program but also through its ongoing investment in research and development. The company continues to lead the charge in developing technologies that shape the future of computing, from AI and machine learning to graphics and autonomous systems.
The Broader Impact of the Fellowship
The impact of the NVIDIA Graduate Fellowship extends beyond the immediate benefits to the recipients. By supporting cutting-edge research, the program contributes to the broader advancement of technology and its applications in various fields. The work of the fellows has the potential to drive innovation in industries ranging from healthcare and automotive to entertainment and beyond.
Moreover, the program fosters a global community of researchers who collaborate, share knowledge, and inspire one another. This collaborative spirit is essential for addressing the complex challenges facing the world today and for driving technological progress that benefits society as a whole.
In conclusion, the NVIDIA Graduate Fellowship Program continues to be a cornerstone of innovation, providing talented researchers with the resources and opportunities they need to make significant contributions to the field of computing. As the 2026-2027 awardees embark on their fellowship journey, the world eagerly anticipates the groundbreaking discoveries and advancements that will emerge from their work.
For more information on the NVIDIA Graduate Fellowship Program, visit the official NVIDIA Graduate Fellowship Program website.
- Chen is modeling 4D physical worlds using scalable data-driven algorithms and physics-inspired principles. His work advances physically grounded 3D and 4D world models, which are crucial for robotics and scientific applications.
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