Event Location: Newell Simon Hall 1507
Bio: Pulkit is a PhD Student in the department of Computer Science at UC Berkeley. His research focuses on computer vision, robotics and computational neuroscience. He is advised by Dr. Jitendra Malik. Pulkit completed his bachelors in Electrical Engineering from IIT Kanpur and was awarded the Director’s Gold Medal. He is a recipient of Fulbright Science and Technology Award, Goldman Sachs Global Leadership Award, OPJEMS, Sridhar Memorial Prize and IIT Kanpur’s Academic Excellence Awards among others. Pulkit served as the General Secretary of Science and Technology Council and vice-captain of water-polo team at IIT-Kanpur. Pulkit holds a “Sangeet Prabhakar” (equivalent to bachelors in Indian classical Music) and occasionally performs in music concerts. 

Abstract: Humans perform a wide range of complex tasks such as navigation, manipulation of diverse objects and planning their interaction with other humans. However, at birth humans are not yet adept at many of these tasks. When observing infants, one might conclude that they perform random actions such as flailing their limbs or manipulating objects without purpose. It is possible that while infants engage in such exploration of their motor abilities they learn a mapping between their sensory and motor systems that enable adults to plan and perform complex sensorimotor tasks. Taking inspiration from this hypothesis, I will present some initial results on how a robotic agent can learn via random interaction with its environment and its intrinsic curiosity to push objects, manipulate ropes and navigate in mazes. I will then show how these basic skills can be combined with imitation to perform more complex tasks. Finally I will touch upon how models similar to object interaction can be used to reason about human behavior in sports games.