Radhika Garg

I am a Ph.D. candidate in Computer Science at Northwestern University, advised by Dr. Xiao Wang, graduating late 2026. My research is in applied cryptography, with a focus on making secure computation practical and deployable.

I have designed scalable generic MPC frameworks supporting 100+ parties, worked on secure noise sampling for differentially private federated learning, and published the first threshold signature scheme compatible with the deployed NIST FALCON standard. I am currently working on a practical variant that preserves FALCON’s standardized verification, making threshold signing deployable without breaking compatibility. Seeing that usability barriers were as much an obstacle as protocol efficiency, I also built Smaug — an LLVM compiler that brings MPC to standard C++ and Rust without a domain-specific language, achieving up to 1240× faster compilation while improving circuit size and depth. Beyond these projects, I am also interested in pseudorandom correlation generators (PCGs), automated testing for interactive protocol implementations and cryptography libraries, and broadly MPC applications.

I am currently a research intern at Silence Laboratories, working on threshold cryptography and compilers for MPC. Previously, I interned at Meta FAIR (AI4Crypto) with Dr. Kristin Lauter, where I built transformer-based distinguishers targeting the EA-LPN hardness assumption, bridging deep learning and cryptographic analysis.

I received my B.Tech. in Computer Science from the Indian Institute of Technology Roorkee in 2022.

Outside of research, I love to paint and sketch.