MoDALAS: Model-Driven Assurance for Learning-Enabled Autonomous Systems. - Michael Austin Langford; Kenneth H. Chan; Jonathon Emil Fleck; Philip K. McKinley; Betty H. C. Cheng (MoDELS, 2021)

EvoAttack: An Evolutionary Search-Based Adversarial Attack for Object Detection Models. - Kenneth H. Chan; Betty H. C. Cheng (SSBSE, 2022)

Expound: A Black-Box Approach for Generating Diversity-Driven Adversarial Examples. - Kenneth H. Chan; Betty H. C. Cheng (SSBSE, 2023)

MoDALAS: addressing assurance for learning-enabled autonomous systems in the face of uncertainty. - Michael Austin Langford; Kenneth H. Chan; Jonathon Emil Fleck; Philip K. McKinley; Betty H. C. Cheng (Softw. Syst. Model., 2023)

SafeDriveRL: Combining Non-cooperative Game Theory with Reinforcement Learning to Explore and Mitigate Human-based Uncertainty for Autonomous Vehicles. - Kenneth H. Chan; Sol Zilberman; Nick Polanco; Joshua E. Siegel; Betty H. C. Cheng (SEAMS@ICSE, 2024)

Evoattack: suppressive adversarial attacks against object detection models using evolutionary search. - Kenneth H. Chan; Betty H. C. Cheng (Autom. Softw. Eng., 2025)