About

I’m a Ph.D. candidate in Computing and Information Science at the Rochester Institute of Technology, advised by Dr. Matthew Wright and Dr. Yin Pan, and an NSF Graduate Research Fellow. I’ve spent most of the past four years researching how machine learning can be applied in the malware domain. Moving forward, I am broadly interested in the intersection of security and artificial intelligence.

I’m on the job market for research scientist positions starting mid-2027.

Research interests

Malware Detection and Mitigation: Malware analysis and threat mitigation.
Adversarial Learning and Robustness: Robust and secure machine learning.
Large Language Models and Agentic AI: Intelligent and autonomous AI systems.
Binary and Program Analysis: Software analysis and vulnerability discovery.

News

Apr 2026 Towards Moving Target Defense for IoT Malware Detection appeared at SERP4IoT 2026.
Feb 2026 Beyond Raw Bytes: Towards Large Malware Language Models appeared at NDSS 2026.
Jun 2025 Do Fear the REAPIR: Adversarial Malware from API Replacement appeared at WoRMA 2025.
Apr 2025 Awarded the Provost's Outstanding Graduate Student Teaching Award.
Apr 2024 Awarded the NSF Graduate Research Fellowship.
Dec 2023 Awarded the AI Seed Fund.
Jan 2022 Impact of Stop Sets on Stopping Active Learning for Text Classification appeared at ICSC 2022.

Selected publications

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

NDSS 2026 Beyond Raw Bytes: Towards Large Malware Language Models

Luke Kurlandski, Harel Berger, Yin Pan, and Matthew Wright

Network and Distributed System Security Symposium (NDSS), 2026

Paper Slides Talk Venue page

BibTeX

@inproceedings{kurlandski2026beyond,
  author    = {Kurlandski, Luke and Berger, Harel and Pan, Yin and Wright, Matthew},
  title     = {Beyond Raw Bytes: Towards Large Malware Language Models},
  booktitle = {Network and Distributed System Security Symposium (NDSS)},
  year      = {2026},
}

WoRMA 2025 Do Fear the REAPIR: Adversarial Malware from API Replacement

Luke Kurlandski, Rayan Mosli, Yin Pan, Sirapat Thianphan, and Matthew Wright

Workshop on Rethinking Malware Analysis (WoRMA), co-located with IEEE EuroS&P, 2025

Paper

BibTeX

@inproceedings{kurlandski2025reapir,
  author    = {Kurlandski, Luke and Mosli, Rayan and Pan, Yin and Thianphan, Sirapat and Wright, Matthew},
  title     = {Do Fear the {REAPIR}: Adversarial Malware from {API} Replacement},
  booktitle = {Workshop on Rethinking Malware Analysis (WoRMA)},
  year      = {2025},
}

ICSC 2022 Impact of Stop Sets on Stopping Active Learning for Text Classification

Luke Kurlandski and Michael Bloodgood

IEEE International Conference on Semantic Computing (ICSC), 2022

Paper

BibTeX

@inproceedings{kurlandski2022stopsets,
  author    = {Kurlandski, Luke and Bloodgood, Michael},
  title     = {Impact of Stop Sets on Stopping Active Learning for Text Classification},
  booktitle = {IEEE International Conference on Semantic Computing (ICSC)},
  year      = {2022},
}

All publications →