Summary
Aditya Hegde is a PhD candidate in Computer Science at Johns Hopkins University with nine years of research experience spanning cryptography, privacy-preserving ML, and theoretical computer science. His work bridges multi-party computation, differential privacy, federated learning, and security aspects of generative and adversarial models, informed by research visits at IISc and ENCRYPTO (TU Darmstadt) and industry internships including GE Healthcare. He combines rigorous mathematical foundations from an iM.Tech in CS with hands-on systems experience, exploring both algorithmic privacy guarantees and practical ML defenses. Based in Baltimore, he pursues cross-disciplinary problems that blend cryptographic protocols with statistical and ML methods, often focusing on deployable privacy mechanisms rather than purely theoretical constructs.
9 years of coding experience
1 year of employment as a software developer
Johns Hopkins University
International Institute of Information Technology Bangalore
Kannada, English, Hindi