Third-year doctoral student, Jiaheng Hu is one of two recipients selected for a Ph.D. fellowship with Two Sigma, a New York-based hedge fund dedicated to research and development in science, technology, engineering and mathematics.
The fellowship is meant to foster new leaders “expanding frontiers in a STEM field such as statistics, applied mathematics, computer science, and physics,” according to the company’s website. Hu, who researches robotic learning and reinforcement learning, previously studied Carnegie Mellon University and Columbia University before coming to the University of Texas.
“UTCS is the place I grew from a student to a researcher—that requires a very different mindset,” Hu said. “UTCS taught me to think about the right questions, approach them scientifically, and write about them professionally.”
Hu is advised by Peter Stone, a computer science professor and director of Texas Robotics, as well as machine learning and robotics professor Roberto Martín-Martín. During his time at UT, Hu has produced 11 research papers. His most recent publication, “FLaRe: Achieving Masterful and Adaptive Robot Policies with Large-Scale Reinforcement Learning Fine-Tuning,” dives into a new method of robotic training that showcases efficient learning adaptability with potential use across robotic disciplines.
“My ultimate goal is to enable robots and other intelligent agents to continuously self-improve from their experiences of interacting with the world,” Hu said. “While this might not give us a cool robot demo right off, I firmly believe that it will be incredibly important in the long run. Getting this fellowship is a great encouragement for me to continue the pursuit of fundamental research and long-term impact.”