Maksim E. Eren is an early career scientist in A-4, Los Alamos National Laboratory (LANL) Advanced Research in Cyber Systems division. He is an alumnus of the Scholarship for Service CyberCorps program. Maksim graduated Summa Cum Laude with a Bachelor's degree in Computer Science from the University of Maryland Baltimore County (UMBC) in 2020 and earned his Master’s degree from the same institution in 2022. In 2024, he received his Ph.D. from UMBC, focusing on tensor decomposition methods for malware characterization.
Eren's interdisciplinary research interests lie at the intersection of machine learning and cybersecurity, with a focus on tensor decomposition. His tensor decomposition-based research projects encompass large-scale malware detection and characterization, cyber anomaly detection, data privacy, biology, text mining, large language models, knowledge graphs, and high-performance computing. Eren has developed and published state-of-the-art solutions in anomaly detection and malware characterization. He has also worked on various other machine learning research projects, including detecting malicious hidden code, adversarial analysis of malware classifiers, and federated learning. At LANL, Eren was a member of the 2021 R&D 100 winning project SmartTensors AI, where he has released a fast tensor decomposition and anomaly detection software, contributed to the design and development of various other tensor decomposition libraries, and developed state-of-the-art text mining tools.
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