Research Interests: Trustworthy AI, adversarial machine learning, and security and privacy in machine learning systems. Specifically, using reinforcement learning to generate adversarial examples and defenses against them for model robustness.
Email: domico@cs.wisc.edu
Address: 1210 W. Dayton St., Room 2262, Madison, WI 53706, USA
@misc{domico2025adversarialagentsblackboxevasion,
archiveprefix = {arXiv},
author = {Kyle Domico and Jean-Charles Noirot Ferrand and Ryan Sheatsley and Eric Pauley and Josiah Hanna and Patrick McDaniel},
booktitle = {Under Review},
eprint = {2503.01734},
primaryclass = {cs.CR},
title = {Adversarial Agents: Black-Box Evasion Attacks with Reinforcement Learning},
url = {https://arxiv.org/abs/2503.01734},
year = {2025}
}
@mastersthesis{domico_generalistpolicies2024,
author = {Kyle Domico},
booktitle = {Master Thesis},
month = {December},
school = {University of Wisconsin-Madison},
title = {Generalist Adversarial Policies in Black-Box Settings},
year = {2024}
}
@inproceedings{pauley_secure_2025,
address = {San Diego, CA},
author = {Eric Pauley and Kyle Domico and Blaine Hoak and Ryan Sheatsley and Quinn Burke and Yohan Beugin and Engin Kirda and Patrick McDaniel},
booktitle = {2025 Network and Distributed Systems Security Symposium (NDSS)},
month = {February},
publisher = {Internet Society},
title = {Secure {IP} {Address} {Allocation} at {Cloud} {Scale}},
url = {https://arxiv.org/abs/2210.14999},
year = {2025}
}