Artificial Intelligence

Recreating Nature with High-fidelity Physics-based Visual Computing

Friday, February 14, 2020, 11:00am - 12:00pm PSTiCal
10th floor conference room: CR#1016
This event is open to the public.
AI Seminar
Chenfanfu Jiang (University of Pennsylvania)


High-fidelity physics-based simulation of 3D materials and natural phenomena has become a critical component in motion pictures, visual effects (VFX), animation, and video games over the past few decades.  As modern architecture progressed towards exascale systems supporting exaFLOPS and accessible hundred-teraFLOP consumer level workstations, numerical simulations have further found an increasing breadth of new applications such as real-time VFX previews, virtual reality games, interactive surgical training, predictive soft robotics, and computational fabrication. While theoretical computation capacity is now less of an impediment, a timely opportunity emerges for innovations in designing new numerical algorithms that mathematically resolve complex geometry and multi-physics with high accuracy, and can best utilize new computational platforms with plausible scalability. This talk focuses on my recent work concerning novel algorithmic and modeling innovations in computational solids, computational fluids, multi-material interactions and multi-physics modeling. I believe that the ultimate goal of physics-based simulation is to model and recreate the entire physical reality in a virtual world to the extent that humans cannot distinguish between the two.


Chenfanfu Jiang is an Assistant Professor in Computer and Information Science at the University of Pennsylvania. He received his Ph.D. in Computer Science at UCLA in 2015, awarded UCLA Engineering School Edward K. Rice Outstanding Doctoral Student. He is a co-founder of the visual effect software company JixieFX inc. and a recipient of NSF CRII award in 2018. His primary research focus is physics-based modeling and simulation for computer graphics and computational engineering science. His research threads in Particle-In-Cell methods and Material Point Methods have been widely adopted in VFX, animations, and other fields in computational science and engineering.

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