Research

Peer-Reviewed Papers

[2] N. Welsh*, L. J. Shikhman*, M. N. Attzs, S. K. Putane, V. M. Nguyen, R. T. White. Post-Launch Capability Expansion of Vision-Language Models via Prompting for On-Orbit Spacecraft Inspection. CVPR 2026 Workshop on AI4Space. [paper]

[1] L. J. Shikhman. One Operator to Rule Them All? On Boundary-Indexed Operator Families in Neural PDE Solvers. ICLR 2026 Workshop on AI & Partial Differential Equations. [paper][arxiv][code]

Preprints

[1] L. J. Shikhman. Forcing and Diagnosing Failure Modes of Fourier Neural Operators Across Classes of PDEs. [arXiv][code]

Invited Talks

[1] L. J. Shikhman, L. Lawler. Deploying Physics Models at the Edge: Quantized AI for Weather and Fluid Simulation on Dell Pro Max with GB10. Optimized AI Conference, 2026, Atlanta, GA.

Manuscripts in Preparation

S. G. Dhekane*, L. J. Shikhman*, A. Joshi, B. Jayaraman, T. Ploetz. Distributional Structure of Learned Representations for Personalized Illness Detection from Wearables.

B. Buchwald, L. J. Shikhman, R.T. White, R.J. Usselman. Learning Approximate Inverse Operators for Hyperspectral Reconstruction.

L. Papadopoulos, E. Reck, L. J. Shikhman. Accounting-Informed Machine Learning for Detecting Financial Reporting Fraud.