Model reduction for elasticity problems in computer graphics and animation
In nature, there are many dynamical systems that are reasonably well-understood from the viewpoint of physics, but are computationally slow to simulate with detailed models. The observed transients in many simulations are, however, often not very rich, but exhibit primarily simple, low-dimensional dynamics. Such observations form the cornerstone of model reduction, an interdisciplinary technique used in electrical and aerospace engineering, as well as solid and fluid mechanics, and computer graphics. In my career, I have studied how model reduction can be applied to elasticity problems in computer graphics and animation. I will present my work on model reduction applied to fast simulation, optimal control, optimization, collision detection, sound simulation and interactive design of geometrically and materially complex models undergoing large deformations.
Jernej Barbic is an assistant professor of computer science at USC, working in the field of computer graphics and animation. In 2014, he was named a Sloan Research Fellow. In 2011, MIT Technology Review named him of the Top 35 Innovators under the age of 35 in the world (TR35). Jernej is the author of Vega FEM, an free C/C++ software physics library for deformable object simulation. He received his Ph.D. from CMU, and did postdoctoral research at MIT CSAIL. His research interests include computer graphics, animation, fast physics, special effects for film, medical simulation, FEM deformable objects, haptics, sound simulation, and model reduction and control of nonlinear systems. Jernej is a NSF CAREER Award winner and holds a Viterbi Early Career Chair position at USC.
Prof. Dr. Andreas Weber
Exponential integrators - a silver bullet for physics-based simulation?
Particle systems have been very popular for physics-based modeling in computer animation. However, for many problems those lead to very stiff initial value problems that traditionally have been solved by implicit methods. Nevertheless, implicit methods have several drawbacks ranging from the addition of artificial damping to relatively high computational costs. In contrast, exponential integrators that solve the linear part of a problem by computing matrix exponentials combining those with the non-linear part using appropriate filter functions can use efficient methods to compute matrix exponentials and are very efficient in general, as very often the stiff parts of the problems are linear. We will exemplify our methods and results - which are part of the PhD thesis of Dominik Michels that was supervised by the author - on a wide variety of examples including challenging dynamics simulations of interacting (hair-)fibers.
Andreas Weber studied mathematics and computer science at the Universities of Tübingen, Germany and Boulder, Colorado, U.S.A. From the University of Tübingen he received his MS in Mathematics (Dipl.-Math) in 1990 and his PhD (Dr. rer. nat.) in computer science in 1993. From 1995 to 1997 he was working with a scholarship from Deutsche Forschungsgemeinschaft as a postdoctoral fellow at the Computer Science Department of Cornell University. From 1997 to 1999 he was a member of the Symbolic Computation Group at the University of Tübingen, Germany. From 1999 to 2001 he was a member of the research group Animation and Image Communication at the Fraunhofer Institut for Computer Graphics. Since April 2001 he has been professor of computer science at the University of Bonn, Germany.
His research interests include physics-based modeling and data driven methods for motion synthesis, analysis, and reconstruction. He has supervised 4 PhD thesis in the context of human hair modeling covering aspects from physics-based rendering and inverse rendering over hair-style reconstruction from (thermal) images to the dynamics simulation of interacting hair fibers.