Faculty Profiles

Greg Anderson works at the intersection of programming languages and machine learning, focusing on techniques for improving the safety and robustness of deep learning systems. Greg is especially interested in neurosymbolic learning, a field of research based on blending deep neural networks with traditional, structured programs to get the best aspects of both worlds. In addition, he also works on algorithms for verifying neural networks directly as well as synthesizing traditional programs. Prior to joining the faculty at Reed, Greg earned a B.S. in Computer Engineering and Mathematics from the University of Virginia and a Ph. D. in Computer Science from the University of Texas at Austin.