325 FMS Bldg.
Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213
I am a postdoctoral researcher in the Department of Statistics and Data Sciences, Carnegie Mellon University (CMU). My current research consists of three projects, in collaboration with Professors Robert E. Kass, Valérie Ventura, Larry Wasserman, Zhao Ren, Alessandro Rinaldo, and Arun Kuchibhotla. Please see the projects page for the current and previous research topics. I am on the 2022-23 job market and looking for faculty and postdoctoral positions.
I received my Ph.D. in Statistics at CMU, advised by Professors Robert E. Kass and Valérie Ventura. My doctoral thesis developed and studied statistical methods of discovering communication across brain regions from neural recordings. I solved the high-dimensional challenge with latent factor time-series and matrix-variate Graphical models. Alongside the thesis, I was fortunate to collaborate with Professor Alessandro Rinaldo on the theoretical consistency of ranking from pairwise comparisons.
My research interests include spatiotemporal methods, graphical models, causal inference on time-series data, high-dimensional central limit theorem, and ranking from pairwise comparisons.
|Jul 6, 2022||I defended my thesis “Discovery of Functional Predictivity across Brain Regions from Local Field Potentials”|
|May 15, 2022||My submission to ICML2022 about Generalized Results for the Existence and Consistency of the MLE in the Bradley-Terry-Luce Model is accepted for one of 118 long presentations.|
|Nov 3, 2019||I won the 1st place on Reproducible Research Paper Competition, CMSAC19, for Time-Varying Bradley Terry Ranking Model with Penalized Estimation, as a collaborated work with Shamindra Shrotriya and Wanshan Li. Check the following CMU Stats Twitter.|
|May 22, 2019||I presented about Linear Factor Model for Discovering Lead-Lag Relationship between Two Brain Areas in the poster session of SAND9.|
- Latent cross-population dynamic time-series analysis of high-dimensional neural recordingssubmitted to Annals of Applied Statistics 2021
- ICMLGeneralized Results for the Existence and Consistency of the MLE in the Bradley-Terry-Luce Modelto appear in International Conference on Machine Learning 2022