Model the physics
Start with how light, sound, or radio waves interact with the world—then turn that image-formation model into something differentiable.
About my research
Physics, rendering, and signals.
I’m a Ph.D. student in computational imaging at Arizona State University. My work combines physics-based differentiable rendering and neural scene representations with unconventional sensing modalities, including time-of-flight and Schlieren imaging.
Research philosophy
Full-stack computational imaging.
I develop the full pipeline—from custom CUDA and OptiX renderers and adjoint solvers to calibrated multi-camera capture hardware.
I’m especially interested in systems that recover information that is hidden, too fast, or too subtle for conventional cameras: megahertz depth and vibration, complex acoustic scattering, and dynamic 3D refractive-index fields.
Own the system
Move comfortably from calibrated capture hardware and signal processing to CUDA kernels, inverse solvers, and neural representations.
Reveal the invisible
Build practical imaging systems for depth, motion, acoustic structure, refractive fields, and phenomena that RGB cameras cannot directly observe.
Education
Academic path
Arizona State University
Ph.D. · Electrical and Computer Engineering
Imaging Lyceum Lab · Advisor: Dr. Suren Jayasuriya · Expected Fall 2028
May 2024 — Present
Arizona State University
M.S. · Robotics and Artificial Intelligence
GPA 3.91 / 4.00
August 2022 — May 2024
University of Pune
B.Tech. · Electronics and Telecommunication
GPA 3.8 / 4.00
August 2016 — May 2020