Our Team

Dr. Chen is a tenure-track Assistant Professor in the Walker Department of Mechanical Engineering at The University of Texas at Austin (UT). He is also affiliated with the Texas Materials Institute and the Oden Institute for Computational Engineering & Sciences. Before joining UT, he was a Research Associate at SLAC National Accelerator Laboratory (2022-2025).

Tong is a postdoctoral fellow with a background in experimental materials science, computational modeling, and data science. During his Ph.D. at Brown University, he studied structure–process–property relationships in thin films by combining physical vapor deposition, materials characterization, physics-based modeling, and machine learning. His current research focuses on developing AI architectures for autonomous materials laboratories, including scientific agents that integrate multimodal experimental data, digital twins, and laboratory automation to enable closed-loop materials discovery.

Tianyu (Tyler) is a Ph.D. Student with a background in computational materials science and machine learning. He previously worked on structure–property relationships using machine-learning interatomic potentials and was a research intern at the Shanghai Artificial Intelligence Laboratory (2025). Now, he is developing agentic workflows that integrate simulation, characterization, and active experimental design to accelerate materials discovery. Outside of research, he enjoys traveling and live music.

Venu is a Ph.D. student with a background in computational science and machine learning. He previously worked on developing frameworks for large-scale Bayesian inverse problems, reduced-order modeling for fluid-flow problems and phonon transport simulation. Currently, he is developing agentic workflows for Bayesian optimal experimental design in neutron scattering.

Jed is a Ph.D. Student with a background in experimental condensed-matter physics and mechatronics. He is currently working on building an agentic Transmission Electron Microscope. This is part of a broader research goal of designing generalizable, closed-loop, autonomous laboratories.

Antony is a Ph.D. Student with a background in heterogeneous catalysis and electrochemistry. His work focuses on combining his interests in ML and AI with his background in materials science to improve the efficiency and efficacy of materials discovery.

Ian is studying for a masters in Artificial Intelligence. His research focuses on a multi-agent coordination framework for orchestrating experimental workflows.

David is studying for a Master's in Computer Science. His research focuses on fine-tuning and reinforcement learning of small parameter models for experimental workflows.

Roy is interested in Bayesian methods and agentic AI systems for scientific problems. His current research focuses on active learning and surrogate-model parameter inversion for complex neutron scattering measurements.