NVIDIA Graduate Fellowship Program Supports Future AI Innovators

2024-12-18

NVIDIA’s Graduate Fellowship Program continues to nurture the next generation of AI researchers. This year, ten exceptional Ph.D. students from around the world have been awarded up to $60,000 each to pursue groundbreaking research in various fields of computing innovation.

The selected fellows will spend the summer interning at NVIDIA before embarking on their fellowship year. Their research will focus on cutting-edge topics such as autonomous systems, computer architecture, computer graphics, deep learning, programming systems, robotics, and security.

The 2025-2026 fellowship recipients are:

Anish Saxena (Georgia Institute of Technology): Improving the efficiency of large language model training and inference through innovative data movement techniques.
Jiawei Yang (University of Southern California): Developing scalable and generalizable foundation models for autonomous systems using self-supervised learning and neural reconstruction.
Jiayi (Eris) Zhang (Stanford University): Enhancing user creativity and productivity in design, animation, and simulation through intelligent algorithms and tools.
Ruisi Cai (University of Texas at Austin): Advancing the efficiency, security, and privacy of large foundation models.
Seul Lee (Korea Advanced Institute of Science and Technology): Developing generative models for molecules and exploring chemical space for drug discovery.
Sreyan Ghosh (University of Maryland, College Park): Improving audio processing and reasoning through resource-efficient models and advanced training techniques.
Tairan He (Carnegie Mellon University): Advancing humanoid robotics, particularly in whole-body loco-manipulation through simulation-to-real learning.
Xiaogeng Liu (University of Wisconsin-Madison): Developing robust and trustworthy AI systems by evaluating and enhancing machine learning models to ensure resilience against attacks and unforeseen inputs.
Yunze Man (University of Illinois Urbana-Champaign): Developing vision-centric reasoning models for multimodal and embodied AI agents, focusing on object-centric perception, open-world scene understanding, and large multimodal models.
Zhiqiang Xie (Stanford University): Building infrastructures to enable more efficient, scalable, and complex compound AI systems, while improving their observability and reliability.

What Undercode Says:

NVIDIA’s continued investment in graduate research through its fellowship program highlights the importance of fostering innovation in AI and related fields. By supporting talented students from diverse backgrounds, NVIDIA aims to accelerate the development of groundbreaking technologies that will shape the future of computing.

The selected fellows are working on critical challenges in AI, such as improving the efficiency and scalability of large language models, advancing autonomous systems, enhancing human-computer interaction, and ensuring the security and reliability of AI systems. Their research has the potential to revolutionize various industries and positively impact society.

It’s encouraging to see NVIDIA’s commitment to nurturing the next generation of AI researchers. By providing financial support, mentorship, and access to cutting-edge resources, NVIDIA is empowering these young minds to push the boundaries of AI and create a brighter future.