Thursday, June 9, 2016
10:00am to 11:00amAdd to Cal
Powell-Booth 100 (Seminar Room)
Computational Rediscovery of Some Classical Force Laws
Mark Stalzer, Principal Computational Scientist, CD3, Caltech,
Abstract: The goal of this work is to computationally rediscover the Maxwell Equations based on data from virtual experiments. As a step in this direction, recent work has focused on rediscovering a general force law composed of Newton¹s Universal Law of Gravitation, Coulomb¹s Law, and the force generated by a magnetic dipole. The basic approach is essentially a combinatorial optimization over a language that adapts as new partial theories are discovered: essentially finding linguistic patterns in theories. Some promising initial results are presented, and future plans sketched. Short Bio: Dr. Mark Stalzer is a Principal Computational Scientist in the Center for Data-Driven Discovery at the California Institute of Technology. He led two high-profile research labs in computing/information sciences at Hughes (1999-2004) and then Caltech (2005-2013). Mark was the Fellow of Data Science at the Moore Foundation (2013-2015) where he was a senior advisor to their Data-Driven Discovery initiative. He is trained in physics and computer science, receiving his PhD from USC in 1993. Mark is an ACM Distinguished Scientist and an AAAS Fellow.
For more information, please contact Tracy Sheffer by phone at 4116 or by email at [email protected].