The Penn Gold Coast Alumni Club
is pleased to invite you to our
Annual Banquet For Club Members and New Penn Admits
Join us for our annual banquet as we welcome our newly accepted Penn students. We had over 100 people attend last year and expect more than 100 folks to come out for our biggest event of the year.
MONDAY, MAY 21, 2012
6:30 PM - 7:00 PM: Cocktail Reception
7:00 PM - 8:30 PM: Dinner
8:30 PM - 9:30 PM: Dessert and Speaker
500 S. Federal Highway
Deerfield Beach, FL 33441
Click here for directions
Incoming Freshmen are our guests
Family members and other guests of Incoming Freshmen:
$49 per person
Includes appetizers, main course, dessert, wine, and soda.
Other beverages may be purchased at the cash bar.
Brooks Chopped Caesar Salad
Fall off the Bone Baby Back Ribs
Escargot ForestiereCaesar Salad, Classic Dressing
Tournedos of Beef
Chicken Breast Oscar
Profiteroles Au Chocolat
Granny Smith Apple Tart
Coffee / Gourmet Tea / Soda
Pre-registration is required no later than Friday, May 18, 2012 at 12:00pm. Due to limited seating, we will not be able to accept any registrations at the door. If you have any questions or encounter any difficulties registering, please contact us at (786) 866-9765 or email@example.com.
Daniel D. Lee, Ph.D.
Associate Professor in the Department of Electrical and Systems Engineering
Professor Lee is currently an Associate Professor in the School of Engineering and Applied Science at the University of Pennsylvania. He studied physics, receiving his A.B. from Harvard in 1990, and his Ph.D. in condensed matter physics from MIT in 1995. After completing his studies, he joined Bell Labs, the research and development arm of Lucent Technologies, where he was a researcher in the Theoretical Physics and Biological Computation departments. After six years in industrial research, he joined the faculty at Penn in 2001 where he is currently doing research and teaching in the Electrical and Systems Engineering Department and at the GRASP Lab.
Why is it that if computers have gotten so much faster and cheaper, they have not become any better at understanding what we want them to do? Some of the tasks we take for granted in vision and language are still too difficult for the fastest supercomputers to handle. To us, a picture may be worth a thousand words, but to a machine both are just seemingly random jumbles of numbers. How can we get machines to intelligently process this kind of information? Professor Lee believes that we can learn much from the way biological systems compute and learn. His research focuses on applying knowledge about biological information processing systems to building better artificial sensorimotor systems that can adapt and learn from experience. Thus, research in his lab looks at computational neuroscience models, theoretical foundations of machine learning algorithms, as well as constructing real-time intelligent robotic systems.