Daniel D. Lee, Ph.D.

Professor

Director, GRASP (General Robotics Automation, Sensing, Perception) Lab

Raymond S Markowitz Faculty Fellow

Evan C Thompson Term Chair for Excellence in Teaching

Dept. of Electrical and Systems Engineering
Dept. of Computer and Information Science (Secondary)

Dept. of Bioengineering (Secondary)
University of Pennsylvania

203B Moore/6314
200 S. 33rd Street
Philadelphia, PA 19104
Office: 215-898-8112
Fax: 215-573-2068

Email: ddlee@seas.upenn.edu

Biography

Daniel Lee is currently the Evan C Thompson Term Chair, Raymond S. Markowitz Faculty Fellow, and Professor in the School of Engineering and Applied Science at the University of Pennsylvania. He received his B.A. in Physics from Harvard University in 1990, and his Ph.D. in Condensed Matter Physics from the Massachusetts Institute of Technology in 1995. Before coming to Penn, he was a researcher at Bell Laboratories, Lucent Technologies, in the Theoretical Physics and Biological Computation departments. He has received the NSF Career award and the University Lindback award for distinguished teaching; he was a fellow of the Hebrew University Institute of Advanced Studies in Jerusalem, an affiliate of the Korea Advanced Institute of Science and Technology, and helped organize the US-Japan National Academy of Engineering Frontiers of Engineering symposium. As director of the GRASP Lab and co-director of the CMU-Penn University Transportation Center, his group focuses on understanding general computational principles in biological systems, and on applying that knowledge to build autonomous systems.

Research

It is ironic that computers excel at logical reasoning that take humans many years of specialized training and education to learn, yet machines are still unable to perform simple everyday tasks that we take for granted. My group’s research focuses on learning representations that enable autonomous systems to efficiently reason about real-time behaviors in an uncertain world. In particular, much of our work has used low-dimensional representations to overcome the curse of dimensionality in perception, planning and control tasks. We use machine learning algorithms and computational neuroscience models, in addition to implementations on a variety of robotic platforms to study how to build better sensorimotor systems that can adapt and learn from experience.

Publications

You can find an updated list of my publications on Google Scholar.

Miscellaneous

My wife, Lisa Park, is an ophthalmologist at NYU Medical School. We live with our son, Jordan, and daughter, Jessica, in Leonia, New Jersey.