Radhika Garg

Ph.D. Candidate, Computer Science, Northwestern University

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I am a Ph.D. candidate in Computer Science at Northwestern University, advised by Dr. Xiao Wang. I work on applied cryptography, with a focus on making secure computation practical and deployable. I am interested in both the protocols and the tooling around them. I am joining Silence Laboratories as an Applied Research Scientist in December 2026.

On the protocol side, I work on threshold cryptography and multi-party computation. I designed a threshold signing scheme compatible with unmodified NIST FALCON verification. I have also worked on scalable generic MPC and on secure noise sampling for differentially private federated learning.

On the systems side, I build tools that make MPC usable by non-experts. Smaug is an LLVM-based compiler that runs standard C++ and Rust programs under MPC without a domain-specific language. I am also interested in automated testing and formal verification of interactive protocol implementations and cryptography libraries.

I have interned at Silence Laboratories, working on threshold cryptography and MPC compilers, and at Meta FAIR with Dr. Kristin Lauter, working on machine learning for cryptanalysis.

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.

Publications

  1. Thresholdizing Standardized FALCON Signatures
    Radhika Garg, Daniel Escudero, Antigoni Polychroniadou, Akira Takahashi, and Xiao Wang
    In ACM Conference on Computer and Communications Security (CCS), 2026
  2. Noisette: Certifying Differential Privacy Mechanisms Efficiently
    Qi Pang, Radhika Garg, Ziling Liu, Hanshen Xiao, Virginia Smith, Wenting Zheng, and Xiao Wang
    In IEEE Symposium on Security & Privacy (S&P), 2027
  3. Smaug: Modular Augmentation of LLVM for MPC
    Radhika Garg and Xiao Wang
    In IEEE Symposium on Security & Privacy (S&P), 2025
  4. Secure Noise Sampling for Differentially Private Collaborative Learning
    Olive Franzese, Congyu Fang, Radhika Garg, Xiao Wang, Somesh Jha, Nicolas Papernot, and Adam Dziedzic
    In ACM Conference on Computer and Communications Security (CCS), 2025
  5. Scalable Mixed-Mode MPC
    Radhika Garg, Kang Yang, Jonathan Katz, and Xiao Wang
    In IEEE Symposium on Security & Privacy (S&P), 2024