Abstract: 3D simulators are increasingly being used to develop and evaluate "embodied AI" (agents perceiving and acting in realistic virtual environments). Much of the prior work in this space has treated simulators as "black boxes" within which learning algorithms are to be deployed. However, the system characteristics of the simulation platforms themselves and the datasets that are used with these platforms both greatly impact the feasibility and the outcomes of experiments involving simulation. In this talk, I will describe recent projects that outline emerging challenges and opportunities in the development of 3D simulation for embodied AI.
Bio: Manolis Savva is an Assistant Professor at Simon Fraser University, and a Canada Research Chair in Computer Graphics. His research focuses on analysis, organization and generation of 3D content. Prior to his current position he was a visiting researcher at Facebook AI Research, and a postdoctoral researcher at Princeton University. He received his Ph.D. from Stanford University under the supervision of Pat Hanrahan. His work has been recognized through several awards including an ACM UIST notable paper award (ReVision), an ICCV best paper nomination (Habitat), two SGP dataset awards (ShapeNet in 2018, ScanNet in 2020), and the 2022 Graphics Interface early career researcher award.