A Generalized Workflow for Creating Machine Learning-Powered Compact Models for Multi-State Devices. - Jack Hutchins; Shamiul Alam; Andre Zeumault; Karsten Beckmann; Nathaniel C. Cady; Garrett S. Rose; Ahmedullah Aziz (IEEE Access, 2022)

Cryogenic In-Memory Matrix-Vector Multiplication using Ferroelectric Superconducting Quantum Interference Device (FE-SQUID). - Shamiul Alam; Jack Hutchins; Md. Shafayat Hossain; Kai Ni 004; Vijaykrishnan Narayanan; Ahmedullah Aziz (DAC, 2023)

Quantum Anomalous Hall Effect-Based Variation Robust Binary Content Addressable Memory. - Md. Mazharul Islam 006; Jack Hutchins; Shamiul Alam; Md. Shafayat Hossain; Akhilesh Jaiswal 001; Ahmedullah Aziz (MWSCAS, 2023)

Machine Learning-powered Compact Modeling of Stochastic Electronic Devices using Mixture Density Networks. - Jack Hutchins; Shamiul Alam; Dana S. Rampini; Bakhrom G. Oripov; Adam N. McCaughan; Ahmedullah Aziz (CoRR, 2023)

Black-Box Adversarial Attacks on Spiking Neural Network for Time Series Data. - Jack Hutchins; Diego Ferrer; James Fillers; Catherine D. Schuman (ICONS, 2024)

CMOS-Based Single-Cycle in-Memory XOR/XNOR. - Shamiul Alam; Jack Hutchins; Nikhil Shukla; Kazi Asifuzzaman; Ahmedullah Aziz (IEEE Access, 2024)

Redefining "Hallucination" in LLMs: Towards a psychology-informed framework for mitigating misinformation. - Elijah Berberette; Jack Hutchins; Amir Sadovnik (CoRR, 2024)

Agentic AI and the Cyber Arms Race. - Sean Oesch; Jack Hutchins; Phillipe Austria; Amul Chaulagain (Computer, 2025)

Embedding-Enhanced Probabilistic Modeling of Ferroelectric Field Effect Transistors (FeFETs). - Tasnia Nobi Afee; Jack Hutchins; Md. Mazharul Islam 006; Thomas Kampfe; Ahmedullah Aziz (CoRR, 2025)