I am a 4th year Ph.D. student in the Department of Industrial Engineering and Management Sciences, Northwestern University, where I am fortunate to be advised by Prof. Diego Klabjan. My major is applied statistics and statistical learning, with a minor in simulation and stochastic analysis.

I am also fortunate to work with Prof. Imon Banerjee. I also had the pleasure of working with Dr. Matthew Plumlee, Principal applied scientist at Amazon.

My research interests broadly encompass statistics, statistical learning, applied probability, and stochastic simulation. Specifically, my work focuses on computational methods for uncertainty quantification in machine learning and stochastic operations research.

From June to December 2024, I interned with the Global Pricing Team at McDonald’s as a recommendation system researcher. I will be joining Amazon in June 2025 as an applied scientist intern on the Middle Mile Marketplace Science team.

Before joining Northwestern, I received my B.S. degree in mathematics and applied mathematics from Fudan University, and my M.S. degree in mathematical statistics from Purdue University, where I was fortunate to be advised by Prof. Raghu Pasupathy.

Please find my latest CV here.

Publication

Ongoing Work

1. Typical Behavior of Weak Mixing Recurrent Controlled Markov Chains
   Ziwei Su, Imon Banerjee, Diego Klabjan

Published Work

1. Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score Minimization [pdf] [GitHub]
   Ziwei Su, Diego Klabjan
   International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
2. Overlapping Batch Confidence Intervals on Statistical Functionals Constructed from Time Series: Application to Quantiles, Optimization, and Estimation [pdf]
   Ziwei Su, Raghu Pasupathy, Yingchieh Yeh, Peter W. Glynn
   ACM Transactions on Modeling and Computer Simulation, 2024
3. A Modified Multinomial Baseline Logit Model with Logit Functions Having Different Covariates [pdf]
   Hao Ding, Ziwei Su, Xiaoqian Liu
   Communications in Statistics - Simulation and Computation, 2020