I explore human social perception and cognition, with a special focus on aspects of human mind that can inspire the development of artificial intelligence that is communicative and trustworthy. I am jointly appointed in the department of communication and the department of statistics at UCLA. I obtained my Ph.D. in cognitive psychology from Yale. I then worked as a post-doctoral fellow in the Center of Brain, Mind and Machine at MIT. Prior to joining UCLA, I was a research scientist in the Computer Vision and Machine Learning labs at GE Global Research.
My research is highly inter-disciplinary, drawing tools from cognitive science, statistics, artificial intelligence, robotics and computer vision. One major theme of my research is to reverse engineer human intuitive social commonsense. By merely seeing static images or a short video, humans can spontaneously perceive a rich set of social concepts, including animacy, intentions, beliefs, desires, emotions, personality and even morality. The goals of my research are to (a) reveal the nature of human social commonsense through cognitive modeling and psychophysical experiments; (b) implement human-like social commonsense in artificial intelligence and robots, so that they can seamlessly communicate to and collaborate with humans in safe and trustworthy ways.
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