Radhika Garg

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

My work spans scalable generic MPC for up to 128 parties, secure noise sampling for differentially private federated learning, and threshold signatures. I designed the first threshold signing scheme compatible with unmodified NIST FALCON verification, and I am currently developing a follow-up with low round complexity to make threshold FALCON practical to deploy. To close the gap between protocol efficiency and usability more broadly, I also built Smaug, an LLVM-based compiler that brings MPC to standard C++ and Rust without a domain-specific language, achieving up to 1240× faster compilation than prior MPC compilers while also improving circuit size and depth. I’m also interested in pseudorandom correlation generators (PCGs), automated testing for interactive protocol implementations and cryptography libraries.

I’m 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 against the EA-LPN hardness assumption under aggressive parameter choices; the attack reduces to a statistical distinguisher and does not extend to more conservative parameter settings.

I received my B.Tech. in Computer Science from the Indian Institute of Technology Roorkee in 2022. Outside of research, I paint and sketch.