Research
My research interests lie broadly at the intersection of time series and learning theory, with a central focus on developing valid statistical inference methods for data exhibiting complex dependency structures. Most recently, I've been exploring the emerging statistical foundations of large language models.
Preprints
-
Stability beyond bounded differences: sharp generalization bounds under finite Lp moments.
Under review.
-
Identifying stability regions of SGD with constant learning rates.
Under review.
-
Fast segmentation of watermarked texts from large language models through epidemic change-points framework.
Under Review at JASA, 2025
-
How Private is Your Attention? Bridging Privacy with In-Context Learning.
Under Review at TMLR, 2025
Journal Publications
-
Testing synchronization of change-points for multiple time series.
Major Revision at Biometrika, 2025
🏆 IMS Hannan Graduate Student Travel Award, 2025
-
Gaussian Approximation For Non-stationary Time Series with Optimal Rate and Explicit Construction.
Annals of Statistics, 52(5): 2293–2317, 2024
-
A Generalized Epidemiological Model with Dynamic and Asymptomatic Population.
Statistical Methods in Medical Research, 31(11): 2137–2163, 2022