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.
My current research interests include 3D Reconstruction and Rendering, Probabilistic Programming, Interpretable and Verifiable Knowledge Representations from Deep Models. In terms of real world applications, I am particularly interested in Conversation agents for Task completion, Machine learning systems for Healthcare and 3D rendering and interaction for augmented and virtual reality.
- Structured Representations for Visual Knowledge and Commonsense
- Low-level vision problems: Image Segmentation, Dense Stereo, Optical Flow
- Object Recognition and Segmentation
- Human Pose Estimation from KINECT
- Localization and Reconstruction using KINECT
- Verifiable and Interpetable Models
- Probablistic Programming
- MAP Inference in Discrete Models (Discrete Optimization)
- Structured Learning
- Learning of Interactive Systems
- Behavioural game theory research using social networks such as Facebook
- Finding Optimal Coalitions in Cooperative Games
- Reconstructing Coalitional Games
- Computing Optimal Coalition Structures
- 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.