bio

I am a Researcher at Apple Machine Intelligence. My interests lie at the intersection of deep learning, computer vision and 3D geometry.

I did my PhD at Max Planck Institute for Intelligent Systems with Michael Black with a thesis on Geometric Understanding of Motion. My work links motion of objects in videos to structure and geometry in the world using deep learning paradigms and self-supervised learning.

I received my Masters degree from the Computer Science Department at The University of British Columbia, Vancouver. I was a research assistant in the Sensorimotor Systems Lab at UBC and I worked with Dinesh Pai on understanding motion of Eyes and Upper Faces. I completed my undergraduate studies at National Institute of Technology Karnataka in the Electronics and Communications Department.

timeline

• 2020 onwards– Researcher, Apple CA
• 2016 - 2019– PhD Student, Max Planck Institute for Intelligent Systems, Tübingen Germany
• Fall 2018 – Research Intern, NVIDIA Research, Boston MA
• Summer 2017 – Research Intern, Facebook Research, Menlo Park CA
• Fall 2015 – Software Developer, Mashup Machine Inc., Vancouver Canada
• 2013 - 2015 – Masters Student, University of British Columbia, Vancouver BC
• Summer 2012 – Research Intern, Ecole Polytechnique de Montreal, Montreal QC
• Summer 2011 – Research Intern, India Innovation Labs, Bangalore India
• 2009 - 2013 – Undergrad, National Institute of Technology, Karnataka India

invited talks

• Towards Grounded Generative Models, Banff International Research Station, 2023.
• Neural Graphics in a Generative World, Max Planck Institute for Intelligent Systems, 2023.
• Towards Neural Graphics, University of Illinois, 2022.
• Competitive Collaboration, Scenes from Videos Workshop, ICCV 2019.
• Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation, NVIDIA GPU Technology Conference 2019.
• Small and Fast Networks for Learning Optical Flow, Scenes from Videos Workshop, ICCV 2017.