Computer Science Building, Rooms 150 & 151
The field of computing is increasingly expected to solve complex geometric problems arising in the physical world. Such problems can be found in applications ranging from robotics planning for industrial automation to molecular modeling for studying biological processes. This talk will first describe the development of a set of algorithmic tools for robot motion planning which are often grouped under the name sampling-based algorithms. Emphasis will be placed on recent results for systems with increased physical realism and complex dynamics. The talk will then discuss how the experience gained through sampling-based methods in robotics has led to algorithms for characterizing the flexibility of biomolecules for drug discovery. A new trend in Computer Science is presented in this talk. It concerns the development of algorithmic frameworks for addressing complex high-dimensional geometric problems arising, at different scales, in the physical world. The challenges of physical computing will be highlighted as well as the opportunities to impact molecular biology and medicine.
Refreshments at 3:40 p.m. in the atrium, outside the presentation room.