Research

My current work is in deep learning theory at BAIR in the DeWeese lab, neutron production in (\(\alpha\),n) reactions at LLNL and BARN, and information geometry (generously supported by a grant from VESSL AI).

Papers

Minimax Rates for Hyperbolic Hierarchical Learning
Divit Rawal, Sriram Vishwanath
Preprint, 2026
[arXiv]
ALPHANSO: Open-Source Modeling of (\(\alpha\),n) Neutron Source Terms
Divit Rawal, Anthony J. Nelson, William Zywiec, Daniel Siefman
Under Review, 2026
[GitHub]
Foundation-Sec-8B-Instruct Technical Report
Cisco Foundation AI contributor: automated data collection and processing pipelines
Technical Report, 2025
[arXiv] | [HuggingFace]
Foundation-Sec-8B Technical Report
Cisco Foundation AI contributor: automated data collection and processing pipelines
Technical Report, 2025
[arXiv] | [HuggingFace]
Measurement of off-shell Higgs boson production in the \(H^* \to ZZ \to 4\ell\) decay channel using a neural simulation-based inference technique in 13 TeV \(\text{pp}\) collisions with the ATLAS detector
ATLAS Collaboration contributor: neural nets for soft extrapolation
Reports on Progress in Physics, 2024
[DOI] | [arXiv]
An implementation of neural simulation-based inference for parameter estimation in ATLAS
ATLAS Collaboration contributor: particle reconstruction algorithms
Reports on Progress in Physics, 2024
[DOI] | [arXiv]