Victor Fung

Victor Fung is an Assistant Professor in the School of Computational Science and Engineering (CSE) at Georgia Tech's College of Computing. Previously, he was a Eugene P. Wigner Fellow at Oak Ridge National Laboratory (ORNL) in the Center for Nanophase Materials Sciences. He holds a B.A. in Chemistry from Cornell University and a Ph.D. in Physical Chemistry from the University of California, Riverside. His research focuses on leveraging artificial intelligence, high-performance computing, and machine learning to accelerate materials and chemical discovery, particularly through inverse design and automated data-driven ecosystems.

His work spans developing graph neural networks for quantum chemistry surrogate models, designing novel materials atom-by-atom, and creating chemically-informed machine learning frameworks. He collaborates extensively with experimentalists and computational scientists to bridge theory and application. Key areas of exploration include catalysis for energy storage, carbon capture, and neuromorphic devices.

Dr. Fung leads a multi-disciplinary team at Georgia Tech, mentoring PhD, MS, and undergraduate students. His lab emphasizes open-source software development and high-throughput computational workflows, utilizing supercomputers like Perlmutter and Frontier. Recent achievements include publishing breakthroughs in inverse design methodologies and high-entropy alloy nanocatalysts.

Awards and recognition include his Wigner Fellowship and sustained contributions to computational chemistry. His group actively seeks motivated researchers with backgrounds in machine learning, computational chemistry, and materials science to join ongoing projects in AI-driven scientific discovery.