I'm a first second third fourth year CSE Ph.D. student at UC San Diego, advised by Professor Ravi Ramamoorthi (and previously also by Hao Su).
I received my bachelor's degree from IIT Madras.
I was fortunate to have spent several summers at Adobe, Nvidia, Apple, and Google with amazing mentors and colleagues. I have also had the opportunity to collaborate with folks from the VITA Group at UT Austin. During my undergrad, I was also associated with the Advanced Geometric Computing Lab, and the Computational Imaging Lab.
I was lucky to be a recipient of the Jacobs School of Engineering Fellowship.
My current research interests lie at the intersection of computer vision, computer graphics and machine learning, specifically to facilitate high quality 3D reconstructions and semantic understanding from multiple view points.
SIGGRAPH 2026
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A framework to learn a generalizable 3D light transport embedding that approximates global illumination from 3D scene configurations.
ICCP 2025
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A framework to reconstruct 3D scenes from SPAD binary images, supporting colorization using a single reference blurry image or generative priors.
A framework that converts handwritten strokes of a variable-length prefix-based abbreviation (e.g. "ho a y" as handwritten strokes) into the intended full phrase (e.g., "how are you" in the digital format) based on the preceding context.
ECCV 2024
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A generalizable framework for novel view synthesis using degraded input captures containing any imperfection type.
SIGGRAPH 2024
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A camera-free novel view synthesis technique from sparse input views (as few as 3 images of large-scale scenes).
CVPR 2024
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General framework to lift any pretrained 2D vision model to generate 3D consistent outputs with no additional optimization.
ICLR Tiny Papers 2024
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An unsupervised learning pipeline for generalizable novel view synthesis and restoration of underwater scenes by disentangling into individual image formation components.
We scale up generalizable NeRF training by borrowing the concept of mixture of experts from language models.
ICLR 2023
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We propose a generalizable neural scene representation and rendering pipeline that achieves superior quality compared to previous methods.
NeurIPS 2022 (Spotlight)
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Sparse networks identified using iterative magnitude pruning showcase improved data-efficiency and robustness compared to their dense counterparts.
NEJLT 2023 (GEM Workshop, IJCNLP 2021)
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Collaborative repository of natural language transformations.
TMLR 2023 (WELM Workshop, ICLR 2021)
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Collaborative benchmark for measuring and extrapolating the capabilities of language models.
ReScience-C (MLRC, NeurIPS 2020)
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We introduce Hierarchical Attention, a recurrent transformer module that imitates convolution-like operation with significantly lower computational budget.
We propose a transformer architecture for sparse set learning, e.g. point cloud understanding.
Teaching humanoid robots to interact with a dynamic world.
Dynamic scene reconstruction from in-the-wild videos.
Large-scale 3D generative models.
Accelerating eye-gaze text entry with context-aware large language models.
Garment-, pose-, and prompt-conditioned human generation.
Minors in Artificial Intelligence & Computer Science.
I regularly review for major vision and machine learning conferences, including CVPR, ICCV, ECCV, ICLR, and NeurIPS. Back at IIT Madras, I TA'd courses in machine learning (EE5180), reinforcement learning (CS6700), and computer vision (EE5179).
I enjoy hiking ⛰️ (cuz duh I am a boring computer science kid), used to sketch ✏️ a bit, and love playing most sports, particularly badminton 🏸, tennis 🎾 and soccer ⚽.
