Ph.D. Fellowship Recipients
The UT Austin-Amazon Science Hub would like to congratulate all past Ph.D. fellowship recipients on their awards.
Past Ph.D. Fellowship Recipients
2025 Fellow Parikshit Bansal
Parikshit Bansal is a Ph.D. student in Computer Science, advised by Sujay Sanghavi (ECE). His research focuses on developing principled algorithms for general machine learning problems. His current work centers on diffusion models for language, with a particular emphasis on improving their efficiency.
2025 Fellow Rohit Dwivedula
Rohit Dwivedula is a Ph.D. student in the Networked Systems group in Computer Science, advised by Aditya Akella and Daehyeok Kim. His research interests are at the intersection of systems and machine learning, where he focuses on developing ML-driven techniques for improving decision-making in operating systems and cloud infrastructure.
2025 Fellow Siddhartha Jain
Siddhartha Jain is a Ph.D. student in Computer Science, advised by Scott Aaronson. He works on quantum algorithms and complexity, with a focus on finding applications of quantum computing with provable advantage over classical computation.
2025 Fellow Avinash Kumar
Avinash Kumar is a Ph.D. student in Electrical and Computer Engineering, advised by Poulami Das. His research focuses on improving the efficiency of ML models, specifically LLMs, through system-level optimizations. His recent work explores correlation-aware KV cache compression strategies and adaptive methods for serving early-exit models. Before his graduate studies, he was a GPU architect at NVIDIA and later a Research Associate at AMD RAD.
2025 Fellow Sateesh Kumar
Sateesh Kumar is a Ph.D. student in Computer Science, advised by Georgios Pavlakos and Roberto Martín-Martín. His research focuses on improving the data efficiency and robustness of robot learning algorithms by leveraging large-scale robotics datasets and structured 3D representations. He earned an M.S. from UC San Diego, working with Xiaolong Wang, and was previously a researcher at ByteDance Seed and Retrocausal.
2025 Fellow Syamantak Kumar
Syamantak Kumar is a Ph.D. student in Computer Science, advised by Purnamrita Sarkar and Kevin Tian. His research lies at the intersection of statistics, optimization and machine learning, with a focus on developing principled algorithms for high-dimensional data analysis. His interests include, but are not limited to, sparse PCA, differential privacy, robust statistics and sampling methods for complex probabilistic models.
2025 Fellow Haoyu Li
Haoyu Li is a Ph.D. student in Computer Science in the Networked Systems (UTNS) group, advised by Aditya Akella and Venkat Arun. His research leverages AI techniques to improve the performance and usability of modern systems, with a focus on data analytics pipelines, LLM cache management, and scheduling for edge computing and autonomous vehicle systems.
2025 Fellow Junbo Li
Junbo Li is a Ph.D. student in Computer Science, advised by Atlas Wang and Qiang Liu. His research focuses on advancing reasoning-driven, agentic large language models and reinforcement learning, with an emphasis on building self-evolving pipelines that can interpret instructions while dynamically leveraging external tools, environments and reasoning to solve complex, real-world problems.
2025 Fellow Kiazhao Liang
Kiazhao Liang is a Ph.D. student in Computer Science, advised by Qiang Liu. He previously worked as a Principal Engineer at SambaNova Systems. His research focuses on efficient training methods, sparse neural networks and large language models. He received a B.S. in Computer Science from the University of Illinois at Urbana-Champaign.
2025 Fellow Zeping Liu
Zeping Liu is a Ph.D. student in Geography and the Environment, advised by Gengchen Mai. His research focuses on advancing Geospatial AI, with particular emphasis on geo-foundation models and spatial representation learning. He has published 14 papers in conferences/journals, including NeurIPS, RSE, ESSD and IEEE TGRS, and serves as a reviewer for eight journals. He is also a student technician at Esri.
2025 Fellow Mohammad Omama
Mohammad Omama is a Ph.D. student in Electrical and Computer Engineering, advised by Sandeep Chinchali in the Swarm Robotics Lab. He focuses on making machine learning for robots more efficient and adaptive. His research explores visual localization, map compression and multimodal representations, and his work has been published in top research venues. In addition, he served as an Applied Scientist Intern at Amazon, where he mentored students, reviewed papers and pursued startup-style research ideas.
2025 Fellow Litu Rout
Litu Rout is a Ph.D. student in Electrical and Computer Engineering, advised by Constantine Caramanis and Sanjay Shakkottai. His research develops theory for generative models—diffusion, rectified flows and optimal transport—and applies them to conditional sampling, including inverse problems, image/video editing and personalization. He currently studies discrete diffusion for multimodal (image–text) generation and understanding.
2025 Fellow Haoran Xu
Haoran Xu is a Ph.D. student in Electrical and Computer Engineering, advised by Amy Zhang. His work focuses on scaling reinforcement learning methods and integrating generative AI to push toward superhuman AGI, particularly for applications in robotics and large language models. He spent a summer as a research intern at Microsoft Research.
2025 Fellow Chutong Yang
Chutong Yang is a Ph.D. student in Computer Science, advised by Kevin Tian. He has a broad interest in the design and analysis of algorithms in theoretical computer science and trustworthy machine learning. His interests include, but are not limited to, solving problems in learning theory, differential privacy and algorithmic fairness using tools in optimization and statistics.
2025 Fellow Xiao Zhang
Xiao Zhang is a Ph.D. student in Computer Science in the Networked Systems (UTNS) group, advised by Daehyeok Kim. His research focuses on networked and distributed systems, with a current emphasis on enabling predictable AI performance at the 5G edge through cross-layer telemetry and resource management. He aims to build practical systems that bridge real-world deployment challenges and core AI infrastructure needs.
2024 Fellow Amitayush Thakur
Amitayush Thakur is a Ph.D. student in the Department of Computer Science. His research interests intersect “AI for Mathematics” and “AI for Code”, including automated mathematical reasoning through LLMs and its implications in fully verified program synthesis essential for generating industry-grade code from AI.
2024 Fellow Yunhao Yang
Yunhao Yang is a Ph.D. student in the Department of Computer Science and the Oden Institute. His research interests include integrating large language models and formal methods for autonomy, AI safety and privacy.
2023 Inaugural Fellow Ajay Jaiswal
Ajay Jaiswal is a Ph.D. student from the School of Information. His work focuses on addressing fundamental bottlenecks for modern-day neural networks like training, transfer, inference efficiency, scalability and more. Through this fellowship, Jaiswal will take a “big-little” approach to making large foundational models that are highly expensive and compute-heavy, more accessible.