Kunal Gupta

I am a PhD candidate in the CSE department at UC San Diego advised by Manmohan Chandraker. I work primarily in 3D computer vision.

In the past, I have twice interned at Adobe w/ Kalyan Sunkavalli, Vladimir Kim and at NVIDIA Research w/ Stan Birchfield . I have also worked as a staff researcher at UC San Diego School of Medicine with Fransisco Contijoch and was a visiting researcher in the Bio Robotics Lab with YU Haoyong at National University of Singapore.

I received my M.S. degree in Computer Science from UC San Diego and B.Eng. degree in Electrical and Electronics Engineering from BITS Pilani, where I was advised by Surekha Bhanot.

My research is supported by the Qualcomm Innovation Fellowship 2023.

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I'm interested in 3D Computer Vision, particularly in inverse rendering, shape deformation, and representation learning with applications to autonomous driving, robotics, augmented reality, and medical imaging. Lately, I have been exploring the applications of LLMs in inverse rendering. Read an overview of my research here.

A general Monte Carlo-based method to accelerate the rendering of any NeRF representation.

A framework for learning to deform meshes in a highly detail-preserving manner, without being tied to a specific mesh

Motion resolved computed tomography by combining neural implicit representations and differentiable rendering

A network that generates manifold meshes enabling photo-realistic physically based renderings and physics simulation

Novel Stable Gait Criteria (SGC) is proposed for safe and intuitive human-robot interaction and rehabilitation.