Aditi Chandrashekar
Courant Institute, NYU
I am a first-year Ph.D. student in CILVR at NYU Courant, advised by Professors Eero Simoncelli, Kyunghyun Cho, and Rob Fergus. I am grateful for the mentorship of Professors Bahareh Tolooshams, Anima Anandkumar, Soon-Jo Chung, and Katie Bouman during my time at Caltech.
My research focuses on prediction and generative modeling, with an emphasis on physical plausibility. I am motivated by questions at the intersection of AI, neuroscience, and vision.
For more info, please find my CV here.
News
I am a recipient of the 2026 NSF Graduate Research Fellowship.
I graduated from Caltech!
I will be starting my PhD at NYU Courant this Fall!
Publications
EquiReg: Symmetry-driven regularization for physically grounded diffusion-based inverse solvers
Building Physically Plausible World Models at ICML 2025 [paper]
VARS-fUSI: Variable Sampling for Fast and Efficient Functional Ultrasound Imaging using Neural Operators
Submitted to Nature Communications [paper]
A Unified Model for Compressed Sensing MRI Across Undersampling Patterns
CVPR 2025 [paper]
Posters/ Talks
Multi-Modal Diffusion Models to Reconstruct Dark Matter Fields
AI2ASE Workshop at AAAI, 2026 [code]
Feature Selection using Explainable AI to Refine Associations between Prominent Genes and Alzheimer’s Disease Neuropathology
SURF Seminar at Caltech, 2022 [paper]