Jack Gindi*, Suyash Gupta*, Rohit Patra*. Adaptive Risk-based challenge system for platform-wide friction management using conformal uncertainty calibration. US Patent (approved).
Suyash Gupta, Rohit Patra, Xuexin Ren, Aman Gupta, Viral Gupta. Efficient machine learning prediction system with adaptive switching between lightweight and heavy models (large language models) using conformal inference. US Patent (approved).
John Duchi*, Suyash Gupta*, Kuanhao Jiang*, Pragya Sur*. Predictive inference in Multi-environment scenarios. Statistical Science 2025. Shorter version accepted at NeurIPS workshop on statistical frontiers in LLMs and foundation models 2024. [workshop] [journal]
Maxime Cauchois*, Suyash Gupta*, Alnur Ali, John Duchi. Predictive inference with weak supervision. Journal of Machine Learning Research 2024. Shorter version accepted at ICML Workshop on Distribution-free Uncertainty Quantification 2021. [workshop][journal]
Maxime Cauchois*, Suyash Gupta*, Alnur Ali, John Duchi. Robust Validation: Confident Predictions Even When Distributions Shift. Extended version published in Journal of American Statistical Association 2024. Shorter version accepted at ICML Workshop on Distribution-free Uncertainty Quantification 2021. [workshop] [journal]
Suyash Gupta, Dominik Rothenhaeusler. The s-value: evaluating stability with respect to distributional shifts. Advances in Neural Information Processing Systems 2023. [conference]
Maxime Cauchois*, Suyash Gupta*, John Duchi. Knowing what you know: valid confidence sets in multiclass and multilabel prediction. Journal of Machine Learning Research 2021. [journal]
PhD Thesis: Reliability and stability in statistical and machine learning problems, Stanford University, 2022.