Mohammad Mahmoody

Mohammad Mahmoody is an associate professor in the Computer Science Department at the University of Virginia. His research focuses on theoretical aspects of cryptography, computational complexity, and machine learning, particularly on understanding barriers such as lower bounds and impossibility results. He has taught courses including Algorithms, Cryptography, and Theory of Computation. His work explores foundational questions in cryptography, adversarial robustness in machine learning, and computational assumptions underlying cryptographic primitives.

• Education: Ph.D. in Computer Science from Princeton University (2010)
• Affiliations: University of Virginia, Department of Computer Science

Research Interests:
His interests span cryptography (e.g., encryption schemes, coin-tossing, and registration-based systems), theoretical computer science (computational complexity, algorithms), and machine learning (adversarial robustness, data poisoning). He emphasizes formal proofs and rigorous analysis in security and learning frameworks.

Publications:
Recent work includes studies on quantum-resistant cryptography, adversarial machine learning, and cryptographic protocol design. Key themes involve impossibility results, lower bounds for cryptographic assumptions, and the interplay between computational constraints and learning theory.

Service & Grants: - Served on program committees for ICML, NeurIPS, CRYPTO, and TCC - Organized workshops on cryptography and lower bounds - Research funded by grants exploring adversarial robustness and cryptographic foundations

Labs/Teams: - Collaborations with researchers in cryptography, machine learning, and theoretical computer science - Advises a team of graduate students and postdocs in security and learning theory.