Rushmore: securely displaying static and animated images using TrustZone. - Chang Min Park; Donghwi Kim; Deepesh Veersen Sidhwani; Andrew Fuchs; Arnob Paul; Sung-Ju Lee; Karthik Dantu; Steven Y. Ko (MobiSys, 2021)

Theory of Mind for Deep Reinforcement Learning in Hanabi. - Andrew Fuchs; Michael Walton; Theresa Chadwick; Doug Lange (CoRR, 2021)

Demonstrating Optimized Delegation between AI and Human Agents. - Andrew Fuchs; Andrea Passarella; Marco Conti (SMARTCOMP, 2022)

A Cognitive Framework for Delegation Between Error-Prone AI and Human Agents. - Andrew Fuchs; Andrea Passarella; Marco Conti (SMARTCOMP, 2022)

Modeling Human Behavior Part II - Cognitive approaches and Uncertainty. - Andrew Fuchs; Andrea Passarella; Marco Conti (CoRR, 2022)

Modeling Human Behavior Part I - Learning and Belief Approaches. - Andrew Fuchs; Andrea Passarella; Marco Conti (CoRR, 2022)

Optimizing Delegation Between Human and AI Collaborative Agents. - Andrew Fuchs; Andrea Passarella; Marco Conti (PKDD/ECML Workshops (2), 2023)

Compensating for Sensing Failures via Delegation in Human-AI Hybrid Systems. - Andrew Fuchs; Andrea Passarella; Marco Conti (Sensors, 2023)

Modeling, Replicating, and Predicting Human Behavior: A Survey. - Andrew Fuchs; Andrea Passarella; Marco Conti (ACM Trans. Auton. Adapt. Syst., 2023)

Optimizing Risk-Averse Human-AI Hybrid Teams. - Andrew Fuchs; Andrea Passarella; Marco Conti (SMARTCOMP, 2024)

Optimizing Delegation in Collaborative Human-AI Hybrid Teams. - Andrew Fuchs; Andrea Passarella; Marco Conti (ACM Trans. Auton. Adapt. Syst., 2024)