Pushmeet Kohli
	Researcher Machine Learning and Perception Microsoft Research Cambridge pkohli [@] microsoft.com Associate Psychometrics Centre University of Cambridge Home | Research | Publications | Collaborators | Press Coverage | Professional Duties | Tutorials | Bio | CV | Resources

Research

My research concerns the development of intelligent machines, with the particular aim of “teaching” computers to (1) understand the behaviour and intent of human users, and (2) to correctly interpret (or “See”) objects and scenes depicted in colour/depth images or videos. I work and publish in the fields of Computer Vision, Machine Learning, Discrete Optimization, Game Theory and Human-Computer Interaction.

I am currently working on (1) the use of online social networks such as Facebook for conducting behavioural game theory experiments, and (2) the development of robust systems for human pose estimation and gesture recognition, and scene understanding using new depth sensors such as XBox KINECT. A more detailed list of research interests can be found below.


Computer Vision
• Low-level vision problems: Image Segmentation, Dense Stereo, Optical Flow
• Object Recognition
• Human Pose Estimation from KINECT
• Localization and Reconstruction using KINECT
Machine Learning
• MAP Inference in Discrete Models (Discrete Optimization)
• Structured Learning
• Learning of Interactive Systems
Game Theory
• Behavioural game theory research using social networks such as Facebook
• Finding Optimal Coalitions in Cooperative Games
• Reconstructing Coalitional Games
• Computing Optimal Coalition Structures
Information Retrieval
• Personalizing Search
• Psycho-metric profiles for capturing user intent

In past life, I have also dabbled a bit in model based checking of non-deterministic software systems. Some of my work can be found in Spec Explorer.