Benjamin Recht

Research Expertise and Interest

machine learning, data science, artificial intelligence

Research Description

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.

Featured in the Media

Please note: The views and opinions expressed in these articles are those of the authors and do not necessarily reflect the official policy or positions of UC Berkeley.
May 3, 2024
Derek Robertson

Ben Recht, an EECS professor, discusses "his belief that while 'artificial intelligence' per se is overrated, the underlying statistical technology is deeply underrated."

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