This Talk has been postponed due to inclement weather.

Nancy Amato ACM Distinguished Speaker Based in TX, USA COLLOQUIUM Department of Computer Science and Engineering University of South Carolina Sampling-Based Motion Planning: From Intelligent CAD to Crowd Simulation to Protein Folding Nancy Amato Department of Computer Science and Engineering Texas A&M University Date: February 11, 2014 Time: 1700-1800 (4:00pm-5:00pm) Place: Swearingen 1A03 (Faculty Lounge) Abstract Motion planning arises in many application domains such as computer animation (digital actors), mixed reality systems and intelligent CAD (virtual prototyping and training), and even computational biology and chemistry (protein folding and drug design). Surprisingly, one type of sampling-based planner, the probabilistic roadmap method (PRM), has proven effective on problems from all these domains. In this talk, we describe the PRM framework and give an overview of some PRM variants developed in our group. We describe in more detail our work related to virtual prototyping, crowd simulation, and protein folding. For virtual prototyping, we show that in some cases a hybrid system incorporating both an automatic planner and haptic user input leads to superior results. For crowd simulation, we describe PRM-based techniques for pursuit evasion, evacuation planning and architectural design. Finally, we describe our application of PRMs to simulate molecular motions, such as protein and RNA folding. More information regarding our work, including movies, can be found at http://parasol.tamu.edu/~amato/. Nancy M. Amato is Unocal Professor and Interim Department Head of the Department of Computer Science and Engineering at Texas A&M University where she co-directs the Parasol Lab. Her main areas of research focus are motion planning and robotics, computational biology and geometry, and parallel and distributed computing. She received undergraduate degrees in Mathematical Sciences and Economics from Stanford University, and M.S. and Ph.D. degrees in Computer Science from UC Berkeley and the University of Illinois at Urbana-Champaign, respectively. She was an AT&T Bell Laboratories PhD Scholar, received an NSF CAREER Award, is a Distinguished Speaker for the ACM Distinguished Speakers Program, and was a Distinguished Lecturer for the IEEE Robotics and Automation Society. She served as the Editor-in-Chief of the IEEE/RSJ IROS Conference Paper Review Board and will be program chair for IEEE ICRA 2015. She was co-Chair of the National Center for Women in Information Technology (NCWIT) Academic Alliance, and currently serves on the CRA-W, CRA-E, and CDC committees. She is a Fellow of the American Association for the Advancement of Science (AAAS), a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), a Fellow of the World Technology Network (WTN). She served as the Editor-in-Chief of the IROS Conference Paper Review Board (2011-2013), as an Editor for the IEEE Robotics and Automation Society Conference Editorial Board (2006-2010), and as an Associate Editor for the IEEE Transactions on Robotics and Automation and of the IEEE Transactions on Parallel and Distributed Computing. She is an elected member of the IEEE Robotics and Automation Society Administrative Committee (AdCom), She was co-Chair of the National Center for Women in Information Technology (NCWIT) Academic Alliance (2009-2011), is a member of the Computing Research Association's Committees on the Status of Women in Computing Research (CRA-W) and Education (CRA-E), and of the Coalition to Diversity Computing (CDC). She has directed or co-directed the CRA-W/CDC Distributed Research Experiences for Undergraduates (DREU, formally known as the DMP) since 2000; DREU is a national program that matches undergraduate women and students from underrepresented groups, including ethnic minorities and persons with disabilities, with a faculty mentor for a summer research experience at the faculty member's home institution. Her main areas of research focus are motion planning and robotics, computational biology and geometry, and parallel and distributed computing. She has graduated 14 PhD students, with most of them going on to careers in academia (7) and government or industry research labs (5), 18 master's students, and has worked with more than 100 Texas A&M undergraduate researchers and non-Texas A&M student interns, with the majority being students from groups underrepresented in computing. She currently supervises 13 PhD students, 2 masters students, and more than 10 undergraduate and high school researchers.