Jason Pacheco

Jason Pacheco serves as an Assistant Professor in the Department of Computer Science at the University of Arizona, maintaining an office in GS 724. He earned his Ph.D. from Brown University in 2016 and specializes in theoretical and applied machine learning.

His educational background includes:

• Ph.D. in Computer Science, Brown University (2016)

Dr. Pacheco's research centers on statistical machine learning, probabilistic graphical models, and approximate inference algorithms, with emphasis on information-theoretic decision making. He bridges theoretical foundations with practical applications in cybersecurity, privacy-preserving AI, and environmental monitoring systems, developing novel approaches for robust sequential decision making under uncertainty.

Analysis of his 15 most recent publications (2021-2025) reveals three dominant research thrusts: (1) Privacy-preserving machine learning, particularly federated learning and differential privacy for large language models; (2) Adversarial reinforcement learning for cyber defense and malware detection; and (3) Variational information-theoretic methods for mutual information estimation and sequential decision making. His work consistently integrates theoretical rigor with real-world applications in security and environmental science.