Research Bio
Benjamin Recht's research group studies how to make machine learning systems more robust to interactions with a dynamic and uncertain world. They are particularly interested in making machine learning more scientific and safe by recognizing where conventional wisdom is incorrect and by establishing reliable benchmarks and baselines to measure performance. For example, they have published papers showing that conventional machine learning theory mischaracterizes how deep networks work and how many results in personalized medicine are overstating their utility. Their work is enriched by collaborations with researchers from applied fields including computational imaging and robotics.
Research Expertise and Interest
machine learning, data science, artificial intelligence
Featured in the Media
Ben Recht, an EECS professor, discusses "his belief that while 'artificial intelligence' per se is overrated, the underlying statistical technology is deeply underrated."
Teaching
Supervised Independent Study [COMPSCI 199]
Special Topics [COMPSCI 294]
Individual Research [COMPSCI 299]
Individual Research [ELENG 299]
Supervised Independent Study [COMPSCI 199]
Individual Research [COMPSCI 299]
Professional Preparation: Supervised Teaching of Computer Science [COMPSCI 399]
Statistical Learning Theory [COMPSCI C281A]
Individual Research [ELENG 299]
Statistical Learning Theory [STAT C241A]
Individual Research [COMPSCI 299]
Field Studies in Electrical Engineering [ELENG 297]
Individual Research [ELENG 299]
Supervised Independent Study [COMPSCI 199]
Individual Research [COMPSCI 299]
Advanced Topics in Learning and Decision Making [COMPSCI C281B]
Individual Research [ELENG 299]
Advanced Topics in Learning and Decision Making [STAT C241B]