Announcing the 2026 NVIDIA Graduate Fellowship Recipients
The prestigious NVIDIA Scholarship has recognized ten doctoral students for their exceptional contributions to computational innovation, marking another milestone in the 25-year history of the NVIDIA Graduate Fellowship Program. Each recipient will receive up to $60,000 to support their groundbreaking research across various areas, including deep learning, robotics, and accelerated computing.
This year, for the first time, the program features a significant representation of Chinese scholars among the awardees. Let’s explore the impressive achievements and research focuses of this year’s winners.
Announcing the 2026 NVIDIA Graduate Fellowship Winners: Investing in the Future of Computational Innovation
The NVIDIA Graduate Fellowship Program has long been a beacon for aspiring innovators in the field of computational technologies. For 25 years, it has provided crucial support to graduate students dedicated to advancing research related to NVIDIA’s cutting-edge technologies. Today, we celebrate the announcement of the 2026 fellowship winners—ten exceptional doctoral students who are pushing the frontiers of accelerated computing.
Vital Support for Pioneering Research
Each awarded fellowship comes with a grant of up to $60,000, aimed at supporting groundbreaking research in various areas, including autonomous systems, computer architecture, computer graphics, deep learning, robotics, programming systems, and security. This year’s cohort stands out, with eight of the ten winners hailing from China, echoing a trend from previous years that showcases the increasing prominence of Chinese researchers in this field.
Meet the 2026 Fellowship Winners
Jiageng Mao – University of Southern California
Research Focus: Physical Artificial Intelligence
Jiageng aims to solve complex problems by leveraging Internet-scale data to create robust, generalizable intelligence for real-world applications. His work integrates robotics, computer vision, and natural language processing.
Liwen Wu – University of California, San Diego
Research Focus: Neural Rendering
Liwen’s research improves the realism and efficiency of physically based rendering through innovative neural materials, building on his foundations in computer graphics and 3D vision.
Sizhe Chen – University of California, Berkeley
Research Focus: AI Security
Sizhe is addressing the pressing issue of prompt injection attacks in AI systems. His practical defense mechanisms aim to secure AI agents without compromising functionality.
Yunfan Jiang – Stanford University
Research Focus: General-Purpose Robotics
Yunfan is working on scalable methods for building robots that can perform daily tasks, leveraging a blend of real-world data, simulations, and multimodal supervision.
Yijia Shao – Stanford University
Research Focus: Human-Machine Collaboration
Yijia is developing AI agents that improve human-machine interactions and collaboration during task execution, drawing on her expertise in natural language processing.
Shangbin Feng – University of Washington
Research Focus: Model Collaboration
Shangbin is exploring how diverse machine learning models can collaborate to create a decentralized and open future for AI, focusing on NLP and social networks.
Irene Wang – Georgia Institute of Technology
Research Focus: Energy-Efficient AI Training
Irene’s framework integrates various aspects of architecture and scheduling to promote sustainable and efficient AI training, reflecting her expansive research interests.
Chen Geng – Stanford University
Research Focus: Modeling the Physical World
Chen is modeling 4D physical environments, merging computer vision, graphics, and machine learning to create robust frameworks for robotics and scientific applications.
Shvetank Prakash – Harvard University
Research Focus: AI Agents
Shvetank is building advanced AI agents with a focus on algorithm development and hardware architecture, laying the foundation for future computing systems.
Manya Bansal – MIT
Research Focus: Programming for Modern Accelerators
Manya’s work lies in designing versatile programming languages that help developers optimize performance while maintaining control over complex systems.
Finalists for the 2026 Fellowship
In addition to the ten winners, five finalists have also been recognized for their promising research, highlighting the depth of talent in the field:
- Zizheng Guo, Peking University
- Peter Holderrieth, MIT
- Xianghui Xie, Max Planck Institute for Informatics
- Alexander Root, Stanford University
- Daniel Palenicek, Technische Universität Darmstadt
Moving Forward
The 2026 NVIDIA Graduate Fellowship winners embody a diverse range of research interests that are shaping the future of AI and computational innovation. Their groundbreaking projects will inevitably push the boundaries of what technology can achieve, ensuring a dynamic evolution in this rapidly changing field.
To dive deeper into the fellowship and its impact, visit the official NVIDIA blog post.
This coverage is courtesy of the WeChat official account “Almost Human” (ID: almosthuman2014) and published by 36Kr with authorization. Stay tuned for more updates on the incredible advancements in AI and computational research!