Erik Learned-Miller

Background:  Ph.D., Electrical Engineering and Computer Science, Massachusetts Institute of Technology (2002), M.S., Electrical Engineering and Computer Science, Massachusetts Institute of Technology (1997), B.A., Psychology, Computer Science Track, Yale University (1988). Professor Learned-Miller joined the faculty in the University of Massachusetts Amherst Department of Computer Science in 2004 as an Assistant Professor. His most recent position was a post-doctoral research engineer in the Electronics Research Laboratory at the University of California-Berkeley. Previously, Professor Learned-Miller was the Chief Executive Officer and Co-founder of CORITechs, Inc., a company that designed virtual reality software for use in neurosurgery operating rooms.

Research:  Professor Learned-Miller’s interests can be broadly categorized as applying ideas and methods from machine learning to problems in machine vision. Problems he has worked on include learning from a small number of examples, independent component analysis, learned color constancy, developing probability models of shape deformation, and mathematical expression recognition. His Ph.D. thesis focuses on using learned statistical knowledge from one visual task to speed learning of a new, related task. The two major types of statistical knowledge used are distributions over shape variability and distributions over joint color variability. He describes a handwritten digit classifier that gets about 90% accuracy using only a single example of each handwritten digit.

Activities and awards:  Professor Learned-Miller received the Microsoft-MIT graduate student fellowship and the Morris Joseph Levin Award (best MasterWorks oral thesis). He holds a patent for “apparatus for neurosurgical stereotactic procedures.” Professor Learned-Miller is the Production Editor for the Journal of Machine Learning Research. He received an NSF CAREER Award in 2006.
 

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