I am glad to organize an invited session at EcoSta 2026. Thanks to the two speakers Professor Zheng and Professor Cui. I also gave an Invited Talk about the ‘‘Prediction Inference of Time Series w...

I am glad to share that the joint work with Prof. Jacobson and Prof. Ryan Exploratory Continuous-Time Modeling (expct): Extracting Dynamic Features from Irregularly Spaced Time Series has been acce...

I am glad to present an Invited Talk at the International Symposium on Nonparametric Statistics (ISNPS) 2026, Thessaloniki, Greece. Thanks for the invitation from Professor Bertail.

I am glad to present an Invited Talk entitled Distributional Conformal Prediction for Markov Process at the Recent Advances in Time Series (RATS) 2026, Larnaca, Cyprus. Thanks for the invitation a...

I am glad to present an Invited Talk entitled Distributional Conformal Prediction for Markov Process at the New England Statistical Society (NESS) 2026, University of Connecticut. Thanks for the i...

I am glad to share that I have been selected to receive the Institute of Mathematical Statistics (IMS) New Researcher Travel Award 2026 Link. Thanks, IMS!

I am glad to share that I was invited to organize a session at EcoSta 2026. Thanks for the recommendation from Professor Karmakar.

I am glad to present a Talk entitled Deep Limit Model Free Prediction in Regression at the 2025 IMS International Conference on Statistics and Data Science, Seville, Spain.

I am glad to present my Poster at workshop on NBER NSF Time Series Conference 2025 at Rutgers University. This poster is based on joint work with Professor Sayar Karmakar and Professor Rangan Gupta...

I am glad to join the Department of Mathematics and Statistics, Loyola University Chicago, as an Assistant Professor in Aug. 2025. My Research Statement and Teaching Statement at that moment. H...

Abstract In this work, we explore the forecasting ability of a recently proposed normalizing and variance-stabilizing (NoVaS) transforma-tion with the possible inclusion of exogenous variables in ...

I am glad to pass my defense talk of my Ph.D. in Statistics at University of California San Diego. Thanks to my parents. Thanks to my advisor Dimitris Politis and my committee members Danna Z...

In my opinion, this work has a wide application on various scenrios involved neural network training. Abstract Deep neural networks (DNN) has received increasing attention in machine learning a...

I am glad to present two posters at workshop on Statistical Frontiers in LLMs and Foundation Models. (NeurIPS 2024 in Vancouver, British Columbia, Canada) Poster: Deep Limit Model Free Predicti...

Abstract Because climate change broadcasts a large aggregate risk to the overall macroeconomy and the global financial system, we investigate how a temperature anomaly and/or its volatility affect...

Abstract The nonlinear autoregressive (NLAR) model plays an important role in modeling and predicting time series. One-step ahead prediction is straightforward using the NLAR model, but the multi-...

This is my first paper with my advisor Professor Politis. Thanks for his guidance! Abstract To address the difficult problem of the multi-step-ahead prediction of nonparametric autoregressions, w...

Thanks to my advisor Dimitris Politis and my committee members Danna Zhang, Ery Arias-Castro and Yian Ma. Advance to Candidacy Slides

Abstract Volatility forecasting is important in financial econometrics and is mainly based on the application of various GARCH-type models. However, it is difficult to choose a specific GARCH mode...

I am glad to share the co-authored talk with Professor Oisín Ryan and Professor Nicholas C. Jacobson on Extracting Dynamic Features from Irregularly Spaced Time Series. Talk Slides

I am glad to receive the Richard Libby Graduate Research Award which supports my research for Summer 2022. Thanks to Richard Libby!

This is my first paper with Professor Karmakar. Thanks for his guidance! Abstract Forecasting volatility from econometric datasets is a crucial task in finance. To acquire meaningful volatility p...