Visualizing Compression of Deep Learning Models for Classification. - Marissa Dotter; Chris M. Ward (AIPR, 2018)

SRC3: A Video Dataset for Evaluating Domain Mismatch. - Jonathan Sato; Chelsea Mediavilla; Chris M. Ward; Shibin Parameswaran (AIPR, 2019)

Ship classification from overhead imagery using synthetic data and domain adaptation. - Chris M. Ward; Josh Harguess; Cameron Hilton (CoRR, 2019)

Leveraging synthetic imagery for collision-at-sea avoidance. - Chris M. Ward; Josh Harguess; Alexander G. Corelli (CoRR, 2019)

Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN). - Chris M. Ward; Josh Harguess; Brendan Crabb; Shibin Parameswaran (CoRR, 2019)

Baseline Evaluation Methodology for Adversarial Patterns on Object Detection Models. - Emily Holt; Anto Malkastian; Savanna Smith; Chris M. Ward; Josh Harguess (AIPR, 2021)

Physical Adversarial Attacks in Simulated Environments. - Michael Threet; Colin Busho; Josh Harguess; Melanie Jutras; Nicole Lape; Sara Leary; Keith Manville; Mike Tan; Chris M. Ward (AIPR, 2021)

Adversarial Examples in Self-Driving: A Review of Available Datasets and Attacks. - Mohammad R. Alam; Chris M. Ward (AIPR, 2022)

Is the Next Winter Coming for AI? Elements of Making Secure and Robust AI. - Josh Harguess; Chris M. Ward (AIPR, 2022)

Detecting Physical Adversarial Patch Attacks with Object Detectors. - Melanie Jutras; Ethan Liang; Sara Leary; Chris M. Ward; Keith Manville (AIPR, 2022)

Adversarial Barrel! An Evaluation of 3D Physical Adversarial Attacks. - Mohammad Zarei; Chris M. Ward; Josh Harguess; Marshal Aiken (AIPR, 2022)

The AI Security Pyramid of Pain. - Chris M. Ward; Josh Harguess; Julia Tao; Daniel Christman; Paul Spicer; Mike Tan (CoRR, 2024)

Offensive Security for AI Systems: Concepts, Practices, and Applications. - Josh Harguess; Chris M. Ward (CoRR, 2025)

Adversarial Threat Vectors and Risk Mitigation for Retrieval-Augmented Generation Systems. - Chris M. Ward; Josh Harguess (CoRR, 2025)