Bartlett W. Mel
Associate Professor of Biomedical Engineering
- 1982, Bachelor's Degree, Electrical Engineering and Computer Science, University of California - Berkeley
- Doctoral Degree, Computer Science, University of Illinois at Urbana-Champaign
Prof. Mel received his B.S. in Electrical Engineering and Computer Science at the University of California at Berkeley in 1983, and his Ph.D. in Computer Science at the University of Illinois at Champaign-Urbana in 1989. He spent 5 years as a post-doctoral fellow at Caltech working in the laboratory of Professor Christof Koch. Dr. Mel joined the Biomedical Engineering Department at USC in the Fall of 1994, and established the Laboratory for Neural Computation. He is a member of the Neuroscience Graduate Program and has a joint appointment in the Department of Psychology.
Our research interests lie in the areas of Computational Neuroscience and Neural Engineering. Most of the work in my lab involves the use of computer models to study brain function. Some of our goals are of a primarily scientific nature. For example, we use detailed biophysiical modeling studies to study synaptic integration in active dendritic trees, and explore how dendritic trees could contribute to the sensory and memory-related functions of nerve cells. To do this work, we use simulation packages such as NEURON and a variety of custom software developed by members of the lab.
Some of our work combines scientific and engineering goals. For example, we are interested in the massively parallel computations carried out in the visual cortex which allow us to recognize objects with a speed, accuracy, and robustness that are far beyond the technical state of the art. How does this amazing neural technology work? We have developed a number of models of this process, and have applied them to various types of visual recognition problems. In one of our ongoing projects, we are attempting to understand the mechanisms used by the brain to learn which features are best for recognizing objects and scenes. Our hope is to someday be able to construct high performance artificial vision systems which could be used to power intelligent machines.
- 2010 Computatational and Systems Neuroscience Conference co-Chair of COSYNE conference
- 1998 NSF NSF Career Award
- 1992 McDonnell Pew McDonnell Pew Fellowship
- 1990 NIH National Research Service Award
- 1987 University of Illinois Cognitive Science/AI Fellowship
- 1983 Hewlett-Packard Hewlett-Packard Faculty Development Fellowship