My current primary interest is to build a household robot that helps me with all kinds of chores. To help this robot reason well with little data, I want to build a world simulator (so that it can rollout scenarios in it’s head and pick the best ones). To build this world simulator, I’ve been interested in multi-modal models (that combine vision, speech, text, robots), generative models (for vision and speech) and efficient representations for encoding the human-centric world.

My secondary interests are in research that intersects between Computer Systems and Machine Learning, partly motivated by my work on Machine Learning Platforms.

I often try to avoid toy or hypothetical problems, even as proxies and ground my research towards applications with obvious benefits. I am not a theoretician for the lack of aptitude or focus, I respect those who make progress in theory.

I’ve made some progress on exploring my research interests.

In the past, I’ve worked on robotics, object and human detection, generative modeling of {images, videos}, AI for video games, ML systems research. Some of my most cited work is on Generative Adversarial networks (GANs), where I co-authored three well-cited papers: LAPGAN (demo), DCGAN (code/demo) and Wasserstein GAN.