Publications

Ryan Barron, Maksim E. Eren, Valentin Stanev, Cynthia Matuszek, Boian S. Alexandrov (2025). Topic Modeling and Link-Prediction for Material Property Discovery. In 25th ACM Symposium on Document Engineering (DocEng), 2025.

Preprint PDF Details

Ryan Barron, Maksim E. Eren, Olga M. Serafimova, Cynthia Matuszek, Boian S. Alexandrov (2025). Bridging Legal Knowledge and AI: Retrieval-Augmented Generation with Vector Stores, Knowledge Graphs, and Hierarchical Non-negative Matrix Factorization. In 20th International Conference on Artificial Intelligence and Law (ICAIL), 2025.

Preprint PDF Details

Manish Bhattarai, Ryan Barron, Maksim E. Eren, Minh Vu, Vesselin Grantcharov, Ismael Boureima, Valentin Stanev, Cynthia Matuszek, Vladimir Valtchinov, Kim Rasmussen, Boian Alexandrov (2025). HEAL: Hierarchical Embedding Alignment Loss for Improved Retrieval and Representation Learning. In 13th International Conference on Learning Representations, Workshop on Scaling Self-Improving Foundation Models without Human Supervision (ICLR 2025 SSI-FM).

Preprint PDF Details

Maksim E. Eren, Boian S. Alexandrov, Charles Nicholas (2024). Classifying Malware Using Tensor Decomposition. Chapter in Springer Nature book Malware; Handbook of Prevention and Detection, 2024.

DOI Preprint PDF Details

Ryan Barron, Vesselin Grantcharov, Selma Wanna, Maksim E. Eren, Manish Bhattarai, Nicholas Solovyev, George Tompkins, Charles Nicholas, Kim O. Rasmussen, Cynthia Matuszek, Boian S. Alexandrov (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).

DOI Preprint PDF Details

Maksim E. Eren (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.

Dissertation PDF Code Details

Afia Anjum, Maksim E. Eren, Ismael Boureima, Boian S. Alexandrov, Manish Bhattarai (2024). Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs. In IEEE Conference on Machine Learning and Applications (ICMLA 2024) with Best Paper Award, 2024.

DOI Preprint PDF Details

Ryan Barron, Maksim E. Eren, Manish Bhattarai, Ismael Boureima, Cynthia Matuszek, Boian S. Alexandrov (2024). Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection. In the IEEE High Performance Extreme Computing (HPEC) Conference, 2024.

DOI Preprint PDF Details

Selma Wanna, Nick Solovyev, Ryan Barron, Maksim E. Eren, Manish Bhattarai, Kim Rasmussen, Boian S. Alexandrov (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.

DOI Preprint PDF Details

Ryan Barron, Maksim E. Eren, Manish Bhattarai, Selma Wanna, Nicholas Solovyev, Kim Rasmussen, Boian S. Alexandrov, Charles Nicholas, Cynthia Matuszek (2024). Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization. In IEEE 12th International Symposium on Digital Forensics and Security (ISDFS), 2024.

DOI Preprint PDF Details

Maksim E. Eren, Ryan Barron, Manish Bhattarai, Selma Wanna, Nicholas Solovyev, Kim Rasmussen, Boian S. Alexandrov, Charles Nicholas (2024). Catch'em all: Classification of Rare, Prominent, and Novel Malware Families. In IEEE 12th International Symposium on Digital Forensics and Security (ISDFS), 2024.

DOI Preprint PDF Details

Alexander B. Most, Maksim E. Eren, Boian S. Alexandrov, Nigel Lawrence (2023). Electrical Grid Anomaly Detection via Tensor Decomposition. In IEEE Military Communications Conference, Articial Intelligence for Cyber Workshop (MILCOM), 2023.

DOI Preprint PDF Details

Nick Solovyev, Ryan Barron, Manish Bhattarai, Maksim E. Eren, Kim O. Rasmussen, Boian S. Alexandrov (2023). Interactive Distillation of Large Single-Topic Corpora of Scientific Papers. In IEEE Conference on Machine Learning and Applications (ICMLA 2023), 2023.

DOI Preprint PDF Details

Maksim E. Eren, Manish Bhattarai, Robert J. Joyce, Edward Raff, Charles Nicholas, Boian S. Alexandrov (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.

DOI Preprint PDF Details

Ismael Boureima, Manish Bhattarai, Maksim E. Eren, Erik Skau, Philip Romero, Stephan Eidenbenz, Boian S. Alexandrov (2023). Distributed out-of-memory NMF on CPU/GPU architectures. In The Journal of Supercomputing, 2023.

DOI Details

Maksim E. Eren, Manish Bhattarai, Kim Rasmussen, Boian S. Alexandrov, Charles Nicholas (2023). MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware. In IEEE International Conference on Intelligence and Security Informatics (ISI), 2023.

DOI Preprint PDF Details

Maksim E. Eren, Kim O. Rasmussen, Charles Nicholas, Boian S. Alexandrov (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.

Poster Details

Maksim E. Eren, Nicholas Solovyev, Ryan Barron, Manish Bhattarai, Ismael D. Boureima, Kim O. Rasmussen, Boian S. Alexandrov (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.

Poster Details

Maksim E. Eren, Kim O. Rasmussen, Charles Nicholas, Boian S. Alexandrov (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.

Poster Details

Maksim E. Eren, Manish Bhattarai, Nick Solovyev, Luke E. Richards, Roberto Yus, Charles Nicholas, Boian S. Alexandrov (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..

DOI Preprint PDF Details

Ismael Boureima, Manish Bhattarai, Maksim E. Eren, Nick Solovyev, Hristo Djidjev, Boian Alexandrov (2022). Distributed Out-of-Memory SVD on CPU/GPU Architectures. In the IEEE High Performance Extreme Computing (HPEC) Conference with Outstanding Paper Award, 2022.

DOI Preprint URL Preprint PDF Details

Maksim E. Eren, Nick Solovyev, Manish Bhattarai, Kim Rasmussen, Charles Nicholas, Boian S. Alexandrov (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.

DOI Preprint PDF Details

Prajna Bhandary, Colin Vieson, Auguste Kiendrebeogo, Iman Adetunji, Robert J. Joyce, Maksim E. Eren, Charles Nicholas (2022). Malware Antivirus Scan Pattern Mining via Tensor Decomposition. Presented at the 13th Annual Malware Technical Exchange Meeting, Online, 2022.

Abstract Poster Details

Ran Liu, Maksim E. Eren, Charles Nicholas (2022). Can Feature Engineering Help Quantum Machine Learning for Malware Detection?. Presented at the 13th Annual Malware Technical Exchange Meeting, Online, 2022.

Poster Details

Maksim E. Eren (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.

Thesis PDF Code Details

Maksim E. Eren, Luke E. Richards, Manish Bhattarai, Roberto Yus, Charles Nicholas, Boian Alexandrov (2022). FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation. arXiv preprint.

Preprint URL Preprint PDF Details

Ismael Boureima, Manish Bhattarai, Maksim E. Eren, Erik Skau, Philip Romero, Stephan Eidenbenz, Boian Alexandrov (2022). Distributed Out-of-Memory NMF of Dense and Sparse Data on CPU/GPU Architectures with Automatic Model Selection for Exascale Data. arXiv preprint.

Preprint URL Preprint PDF Details

Maksim E. Eren, Juston S. Moore, Erik Skau, Elisabeth Moore, Manish Bhattarai, Gopinath Chennupati, Boian S. Alexandrov (2022). General-Purpose Unsupervised Cyber Anomaly Detection via Non-Negative Tensor Factorization. In ACM Digital Threats Research and Practice (DTRAP) Journal, 2022.

DOI Preprint PDF Code Details

Maksim E. Eren, Nick Solovyev, Chris Hamer, Renee McDonald, Boian S. Alexandrov, Charles Nicholas (2021). COVID-19 Multidimensional Kaggle Literature Organization. In ACM Symposium on Document Engineering 2021 (DocEng ’21), 2021.

DOI Preprint URL Preprint PDF Interactive Plot Details

Maksim E. Eren, Charles Nicholas, Renee McDonald, Chris Hamer (2021). Random Forest of Tensors (RFoT). Presented at the 12th Annual Malware Technical Exchange Meeting, Online, 2021.

Abstract Poster Details

John Boutsikas, Maksim E. Eren, Charles Varga, Edward Raff, Cynthia Matuszek, Charles Nicholas (2021). Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery. Presented at the 12th Annual Malware Technical Exchange Meeting, Online, 2021.

Preprint URL Preprint PDF Abstract Poster Code Details

Maksim E. Eren, Juston S. Moore, Boian S. Alexandrov (2020). Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization. In IEEE International Conference on Intelligence and Security Informatics (ISI), 2020.

DOI Preprint PDF Details

Maksim E. Eren, Nick Solovyev, Edward Raff, Charles Nicholas, Ben Johnson (2020). COVID-19 Kaggle Literature Organization. In ACM Symposium on Document Engineering 2020 (DocEng ’20), 2020.

DOI Preprint URL Preprint PDF Poster Code Interactive Plot Details

Enis Golaszewski, Alan T. Sherman, Linda Oliva, Peter A. H. Peterson, Michael R. Bailey, Scott Bohon, Cyrus Bonyadi, Casey Borror, Ryan Coleman, Johannah Flenner, Elias Enamorado, Maksim E. Eren, Mohammad Khan, Emmanuel Larbi, Kyle Marshall, William Morgan, Lauren Mundy, Gabriel Onana, Selma Gomez Orr, Lauren Parker, Caleb Pinkney, Mykah Rather, Jimmy Rodriguez, Bryan Solis, Wubnyonga Tete, Tsigereda B. Tsega, Edwin Valdez, Charles K. Varga, Brian Weber, Ryan Wnuk-Fink, Armand Yonkeu, Lindsay Zetlmeisl, Damian Doyle, Casey O'Brien, Joseph Roundy, Jack Suess (2020). Project-based learning continues to inspire cybersecurity students: the 2018--2019 SFS research studies at UMBC. In Association for Computing Machinery (ACM), 2020.

DOI Details