Publications

Under Review

Don't Just Eat the EXE: Raw-Binary Malware Classifiers Need Structure and Scale
Luke Kurlandski, David Krisiloff, Scott Coull, and Matthew Wright
Under review, 2026
DAUGL: Cross-Platform Malware Detection via Unsupervised Global and Local Domain Alignment
Craig Xie, Luke Kurlandski, Paul Miller, and Niall McLaughlin
Under review, 2026

Conference Proceedings

Luke Kurlandski, Harel Berger, Yin Pan, and Matthew Wright
Network and Distributed System Security Symposium (NDSS), 2026
Luke Kurlandski and Michael Bloodgood
IEEE International Conference on Semantic Computing (ICSC), 2022
Jonas Strobelt, Daniel Stolz, Maximilian Leven, Luke Kurlandski, and David McGee
IEEE Conference on Lasers and Electro-Optics (CLEO), 2021
Daniel Stolz, Jonas Strobelt, Maximilian Leven, Luke Kurlandski, Heba Abourahma, and David McGee
SPIE Practical Holography: Displays, Materials, and Applications, 2021

Journal Articles

Jonas Strobelt, Daniel Stolz, Maximilian Leven, Matthew Van Soelen, Luke Kurlandski, Heba Abourahma, and David McGee
Optics Express, 2022

Workshop Papers

Ita Ryan, Luke Kurlandski, and Nate Mathews
Workshop on Software Engineering Research and Practices for the IoT (SERP4IoT), 2026
Luke Kurlandski, Rayan Mosli, Yin Pan, Sirapat Thianphan, and Matthew Wright
Workshop on Rethinking Malware Analysis (WoRMA), co-located with IEEE EuroS&P, 2025

Poster Sessions

Pretrained Executable Language Models (ELMs) Excel at Malware Understanding
Luke Kurlandski, Harel Berger, Yin Pan, and Matthew Wright
USENIX Security Symposium (Poster), 2024
Modeling Stepping-Stone Flows Using Stochastic Random Walks and Black Box Neural Networks
Luke Kurlandski, Nate Mathews, Nicholas Hopper, and Matthew Wright
Western New York Image and Signal Processing Workshop (WNYISPW), 2024
From Bytes to Insights: A New Era of Malware Detection
Luke Kurlandski, Yin Pan, and Matthew Wright
Western New York Image and Signal Processing Workshop (WNYISPW), 2023
An Adversarial Malware Evasion Attack Using Machine Translation
Luke Kurlandski, Yin Pan, and Matthew Wright
AI@RIT Summit, 2022
Evaluating ML Recommender Systems without Interactions Data
Luke Kurlandski
ACM Technical Symposium on Computer Science Education (SIGCSE), 2021