NVIDIA Announces 2026-2027 Graduate Fellowship Recipients – Fueling the Future of Accelerated Computing
For a quarter of a century, the NVIDIA Graduate Fellowship Program has been a cornerstone in supporting and nurturing the brightest minds in computing. This prestigious program identifies and invests in extraordinary Ph.D. students whose research directly impacts NVIDIA’s core technologies and the broader landscape of innovation. Today, NVIDIA announced its latest cohort of fellows – ten outstanding students poised too shape the future of accelerated computing.
These fellowships, valued at up to $60,000 each, aren’t just financial support; they represent a vote of confidence in the next generation of researchers tackling some of the most challenging problems in the field. The program is fiercely competitive, attracting applicants from around the globe, and culminates in a summer internship with NVIDIA before the fellowship year begins.
Why is this critically important? NVIDIA’s commitment to graduate research is a key driver of progress in areas like artificial intelligence,robotics,and high-performance computing. By empowering these students, NVIDIA is directly contributing to breakthroughs that will impact industries and lives worldwide.
The Cutting Edge of Research: Meet the 2026-2027 Fellows
This year’s fellows are exploring a diverse range of research areas, all united by the power of accelerated computing. Here’s a closer look at their groundbreaking projects:
* Jiageng Mao (University of Southern california): Developing more robust and adaptable AI for real-world applications by leveraging vast datasets to create intelligent agents capable of navigating complex physical environments. Think robots that can truly understand and interact with the world around them.
* Liwen Wu (University of California San Diego): Pushing the boundaries of visual realism and efficiency in computer graphics through the innovative use of neural materials and rendering techniques. This research promises more lifelike and efficient visuals for gaming, simulations, and beyond.
* Manya Bansal (Massachusetts Institute of Technology): Designing the next generation of programming languages specifically tailored for modern accelerators. Her work aims to simplify development while maintaining the performance needed for demanding applications. This is about making powerful computing accessible to more developers.
* Sizhe Chen (University of California, Berkeley): Addressing a critical challenge in AI security: protecting AI agents from malicious attacks like prompt injection. His research focuses on developing practical and effective defenses that don’t compromise the agent’s functionality.
* Yunfan Jiang (Stanford University): Building truly versatile robots capable of performing everyday tasks. This involves combining data from real-world interactions, large-scale simulations, and internet-based sources to create robots that can learn and adapt.
* Yijia Shao (Stanford University): Improving collaboration between humans and AI agents. Her research focuses on developing AI that can effectively communicate and coordinate with people, leading to more intuitive and productive human-agent interactions.
* Shangbin Feng (University of Washington): Pioneering a future of collaborative AI where multiple machine learning models work together,sharing knowledge and complementing each other’s strengths.This decentralized approach promises more robust and adaptable AI systems.
* Shvetank Prakash (Harvard University): Revolutionizing hardware architecture and systems design by leveraging the power of AI itself. His work explores using AI agents to optimize hardware performance and efficiency.
* Irene Wang (Georgia Institute of Technology): Creating a holistic framework for designing energy-efficient and sustainable AI training systems. This research addresses the growing environmental impact of large-scale AI models.
* Chen Geng (Stanford University): Developing advanced algorithms for modeling and understanding the physical world in 4D. This research has implications for robotics, scientific simulations, and creating more realistic virtual environments.
Recognizing the Future Leaders: 2026-2027 Finalists
NVIDIA also acknowledges the exceptional talent of the fellowship finalists, who demonstrated remarkable 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 Commitment to Innovation
The NVIDIA Graduate fellowship Program is more than just a funding prospect; it’s an investment in the future of computing. By supporting these exceptional students, NVIDIA is fostering a vibrant ecosystem of innovation that will drive progress for years to come.
Learn More:
* NVIDIA Graduate Fellowship Program: [https://researchnvidiacom/graduate[https://researchnvidiacom/graduate[https://researchnvidiacom/graduate[https://researchnvidiacom/graduate
