collaborators

5 papers

cs.LG2026

Towards Data-Efficient Cross-Device Generalization of Grad-Shafranov Equilibria via Transfer Learning Neural Operator

Jay Phil Yoo, William Howes, Yashika Ghai +3

Real-time reconstruction of magnetohydrodynamic equilibria is essential for plasma shaping, stability assessment and feedback control in magnetic confinement fusion. However, Grad-…

cs.LG2026

Real-Time Sensing of Inaccessible Physical Fields via an Edge-Deployable Hardware-Portable Graph Neural Operator

William Howes, Jason Yoo, Kazuma Kobayashi +4

Real-time inference of inaccessible interior physical fields from sparse boundary observations is a fundamental but unresolved problem in scientific machine learning, with direct r…

cs.LG2026

When Spike Sparsity Does Not Translate to Deployed Cost: VS-WNO on Jetson Orin Nano

Jason Yoo, Shailesh Garg, Souvik Chakraborty +1

Spiking neural operators are appealing for neuromorphic edge computing because event-driven substrates can, in principle, translate sparse activity into lower latency and energy. W…

cs.LG2026

Sensing Without Colocation: Operator-Based Virtual Instrumentation for Domains Beyond Physical Reach

Jay Phil Yoo, Kazuma Kobayashi, Souvik Chakraborty +1

Classical sensing rests on one foundational assumption: the quantity of interest must be colocated with the measurement device. This is not an engineering convenience. It is the or…

cs.CR2026

Agent-Fence: Mapping Security Vulnerabilities Across Deep Research Agents

Sai Puppala, Ismail Hossain, Md Jahangir Alam +5

Large language models are increasingly deployed as *deep agents* that plan, maintain persistent state, and invoke external tools, shifting safety failures from unsafe text to unsaf…