Mohammad Mahmoody

Mohammad Mahmoody is an Associate Professor in the Computer Science Department at the University of Virginia (UVA), where he conducts theoretical research at the intersection of cryptography and machine learning.

His research focuses on understanding fundamental limitations in cryptography and machine learning through the lens of lower bounds, impossibility results, and security barriers. Key areas include cryptographic protocols, adversarial robustness in learning systems, and computational complexity.

His recent publications show a strong trend toward bridging cryptographic techniques with machine learning security, particularly in understanding data poisoning attacks, robust learning under adversarial conditions, and the computational foundations of security guarantees. His work spans both theoretical computer science venues (CRYPTO, EUROCRYPT, TCC) and machine learning conferences (NeurIPS, ICML).

He actively advises graduate students and postdocs, with a track record of mentoring PhD candidates through completion of their degrees. His service to the academic community includes extensive program committee work for major conferences in both cryptography and machine learning.

Dr. Mahmoody teaches advanced courses including Theory of Computation, Algorithms, and Cryptography at both undergraduate and graduate levels, demonstrating his commitment to educating the next generation of theoretical computer scientists.