First‑Author Research

• EMBER2024 — A Benchmark Dataset for Holistic Evaluation of Malware Classifiers. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2025. (Paper) (GitHub)

• Claravy — A Tool for Scalable and Accurate Malware Family Labeling. In Proceedings of the ACM on Web Conference, 2025. (Paper) (GitHub)

• MalDICT: Benchmark Datasets on Malware Behaviors, Platforms, Exploitation, and Packers. In Proceedings of the Conference on Applied Machine Learning in Information Security, 2023. (Paper) (GitHub)

• AVScan2Vec — Feature Learning on Antivirus Scan Data for Production‑Scale Malware Corpora. In Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023. (Paper) (GitHub)

• MOTIF — A Malware Reference Dataset with Ground Truth Family Labels. In Computers & Security, vol. 124, 2023. (Paper) (GitHub)

• Rank‑1 Similarity Matrix Decomposition For Modeling Changes in Antivirus Consensus Through Time. In Proceedings of the Conference on Applied Machine Learning for Information Security, 2021. (Paper)

• A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels. In Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021. (Paper)

• Malware Attribution Using the Rich Header. Presented at ShmooCon 2019. (Paper) (GitHub)

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Co‑Authored Research

• Ransomware Evolution: Unveiling Patterns Using HDBSCAN. In Proceedings of the Conference on Applied Machine Learning in Information Security, 2024. (Paper)

• Evaluating Representativeness in PDF Malware Datasets: A Comparative Study and a New Dataset. In Proceedings of the IEEE International Conference on Big Data, 2023 (Paper)

• Semi-supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection In ACM Transactions on Privacy and Security, Volume 26, Issue 4, 2023. (Paper)

• Malware Antivirus Scan Pattern Mining via Tensor Decomposition. (Paper)

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PhD Dissertation

• Investigating Antivirus Scan Results as a Source of Features and Labels for Machine Learning (Dissertation)

Master’s Thesis

• Evaluating Automatic Malware Classifiers in the Absence of Reference Labels (Thesis)

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Patents

• System and method for converting antivirus scan to a feature vector. (Patent)

• System and method for modeling correlation in a sourcing model using similarity matrix decomposition. (Patent)

• Evaluating automatic malware classifiers in the absence of reference labels. (Patent)