[CFAR Outstanding PhD Student Seminar Series]
Perceive and Reason About The Physical World (Hybrid event) by Mr Duan Jiafei
26 Aug 2022 | 2.00pm (Singapore Time)
Research in cognitive science has provided extensive evidence of human cognitive ability in performing physical reasoning of objects from noisy perceptual inputs. Such a cognitive ability is commonly known as intuitive physics. With advancements in deep learning, there is an increasing interest in building intelligent systems capable of performing physical reasoning from a given scene to build better artificial intelligence (AI) systems. As a result, many contemporary approaches to modelling intuitive physics for machine cognition have been inspired by literature from cognitive science. Existing models of intuitive physics based on vision can predict the results of physical interactions. However, they primarily concentrate on end-to-end deep learning methods to infer physical properties (such as mass, friction, and velocity) in latent space for performing physical reasoning.
In this talk, Mr Duan Jiafei will first briefly introduce the recent advancements in machine learning approaches for modelling intuitive physics. Then, he will talk about some of his most recent initiatives to create fresh AI models for physical reasoning via perception using cognitively inspired methods, as well as how these models might further improve explainability and interpretability in learning.
Mr Duan Jiafei received his B.Eng (Highest Distinction) from the School of Electrical and Electronics Engineering, Nanyang Technological University of Singapore, under the A*STAR Undergraduate Scholarship. He is currently a first-year PhD student at the Robotics and State Estimation Lab, University of Washington, under the advisory of Professor Dieter Fox. His research interest lies at the intersection of computer vision and cognitive science for embodied AI. Mr Duan served as the lead author in several embodied AI and machine physical reasoning papers published in top-tier AI conferences and journals (including NeurIPS, IJCAI, ICCV, ECCV, ICIP, and IEEE TETCI). He has also received Singapore's prestigious National Science (PhD) Scholarship for his PhD studies.