Publications

(2024). Classifying Malware Using Tensor Decomposition. Chapter in Springer Nature book Malware; Handbook of Prevention and Detection, 2024.

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(2024). Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization. In IEEE Conference on Machine Learning and Applications, Special Session on Machine Learning for Natural Language Processing (ICMLA 2024).

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(2024). Advanced Semi-supervised Tensor Decomposition Methods for Malware Characterization. Ph.D. Dissertation in Computer Science at the University of Maryland, Baltimore County Department of Computer Science and Electrical Engineering.

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(2024). Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs. In IEEE Conference on Machine Learning and Applications (ICMLA 2024), 2024.

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(2024). Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection. In the IEEE High Performance Extreme Computing (HPEC) Conference, 2024.

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(2024). TopicTag: Automatic Annotation of NMF Topic Models Using Chain of Thought and Prompt Tuning with LLMs. In ACM Symposium on Document Engineering 2024 (DocEng ’24), 2024.

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(2024). Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization. In IEEE 12th International Symposium on Digital Forensics and Security (ISDFS), 2024.

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(2024). Catch'em all: Classification of Rare, Prominent, and Novel Malware Families. In IEEE 12th International Symposium on Digital Forensics and Security (ISDFS), 2024.

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(2023). Electrical Grid Anomaly Detection via Tensor Decomposition. In IEEE Military Communications Conference, Articial Intelligence for Cyber Workshop (MILCOM), 2023.

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(2023). Interactive Distillation of Large Single-Topic Corpora of Scientific Papers. In IEEE Conference on Machine Learning and Applications (ICMLA 2023), 2023.

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(2023). 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 (TOPS) journal, 2023.

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(2023). Distributed out-of-memory NMF on CPU/GPU architectures. In The Journal of Supercomputing, 2023.

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(2023). MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware. In IEEE International Conference on Intelligence and Security Informatics (ISI), 2023.

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(2023). Malware-DNA: Machine Learning for Malware Analysis that Treats Malware as Mutations in the Software Genome. Presented at the Malware Technical Exchange Meeting (MTEM), Lawrence Livermore National Laboratory, California. July 25-27, 2023.

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(2023). Sub-topic and Semantic Sub-structure Extraction via SPLIT: Joint Nonnegative Matrix Factorization (NMF) with Automatic Model Selection. Presented at the Conference on Data Analysis 2023 (CoDA 23’), Santa Fe, New Mexico. March 7-9, 2023.

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(2023). Malware-DNA: Machine Learning for Malware Analysis that Treats Malwares as Mutations in the Genome of the Software. Presented at the Conference on Data Analysis 2023 (CoDA 23), Santa Fe, New Mexico. March 7-9, 2023.

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(2022). One-Shot Federated Group Collaborative Filtering. In IEEE Conference on Machine Learning and Applications (ICMLA 2022), 2022. Awarded Best M.S. Research at 2023 UMBC CSEE Research Day..

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(2022). Distributed Out-of-Memory SVD on CPU/GPU Architectures. In the IEEE High Performance Extreme Computing (HPEC) Conference with Outstanding Paper Award, 2022.

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(2022). SeNMFk-SPLIT: Large Corpora Topic Modeling by Semantic Non-negative Matrix Factorization with Automatic Model Selection. In ACM Symposium on Document Engineering 2022 (DocEng ’22), 2022.

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(2022). Malware Antivirus Scan Pattern Mining via Tensor Decomposition. Presented at the 13th Annual Malware Technical Exchange Meeting, Online, 2022.

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(2022). Can Feature Engineering Help Quantum Machine Learning for Malware Detection?. Presented at the 13th Annual Malware Technical Exchange Meeting, Online, 2022.

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(2022). Random Forest of Tensors (RFoT). Master’s Thesis in Computer Science at the University of Maryland, Baltimore County Department of Computer Science and Electrical Engineering.

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(2022). FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation. arXiv preprint.

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(2022). Distributed Out-of-Memory NMF of Dense and Sparse Data on CPU/GPU Architectures with Automatic Model Selection for Exascale Data. arXiv preprint.

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(2022). General-Purpose Unsupervised Cyber Anomaly Detection via Non-Negative Tensor Factorization. In ACM Digital Threats Research and Practice (DTRAP) Journal, 2022.

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(2021). COVID-19 Multidimensional Kaggle Literature Organization. In ACM Symposium on Document Engineering 2021 (DocEng ’21), 2021.

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(2021). Random Forest of Tensors (RFoT). Presented at the 12th Annual Malware Technical Exchange Meeting, Online, 2021.

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(2021). Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery. Presented at the 12th Annual Malware Technical Exchange Meeting, Online, 2021.

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(2020). Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization. In IEEE International Conference on Intelligence and Security Informatics (ISI), 2020.

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(2020). COVID-19 Kaggle Literature Organization. In ACM Symposium on Document Engineering 2020 (DocEng ’20), 2020.

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(2020). Project-based learning continues to inspire cybersecurity students: the 2018--2019 SFS research studies at UMBC. In Association for Computing Machinery (ACM), 2020.

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