The Department of Statistics and Data Science Bi-Annual Newsletter, Spring 2026

Table of Contents

Introduction from Xuming He

While the earth moves at a constant pace, the world of humans and machines rapidly accelerates in civilization and technology. In this dynamic environment, a young department like ours is poised to lead. With this edition of our SDS newsletter, we are very pleased to share some of the latest developments from the Department of Statistics and Data Science (SDS).

At our core, we are dedicated to providing the best possible education for our students. To keep pace with the evolving digital landscape, we are continually upgrading our academic programs. This year, we fine-tuned both the statistics major and minor to make statistics and machine learning training more broadly accessible to WashU undergraduates. We recognize that students pursuing careers in fields such as the social sciences, biological sciences, and public health will be better prepared for the future with a solid foundation in statistical thinking and data science skills. Beginning in the fall of 2026, our master’s program will be officially upgraded to a “Master of Arts in Statistics and Data Science,” featuring an applied data science concentration suited for students interested in the social and biological sciences. Furthermore, our students will enjoy greater access to AI-driven and AI-assisted data science training right here at WashU.

Though our alumni base is currently small, it is steadily growing, and we have recently begun building a stronger, more connected network. I am thrilled for Jiaqi Li (PhD, 2024), who will transition into her new role as Assistant Professor of Statistics at Rice University this summer. Additionally, five of our master’s graduates from this year will be continuing their academic journeys to pursue PhD degrees in statistics and related fields. I call upon all of our alumni to stay in touch with us; we love hearing from you and count on your involvement to help guide the future growth and positioning of our programs.

This summer, we are excited to welcome two new faculty members who will enhance our expertise in emerging areas of statistics and data science. Apratim Dey (PhD, 2024, Stanford University) will bring knowledge and expertise in compressed sensing, alongside large language model training and evaluation. Sean McGrath (PhD, 2024, Harvard University) joins us following his postdoctoral training at the Yale School of Public Health, focusing his research on developing and applying statistical methods for causal inference and data integration. The majority of SDS faculty have joined WashU within just the past three years, so I encourage you to visit our department website to learn more about our team.

Finally, I am pleased to note that the latest US News Best Graduate Schools rankings place the WashU Statistics program at #31 in the country, a significant jump of more than 20 spots since the previous 2022 ranking. While rankings are an important indicator, our true priority is to work together to elevate our programs even further—not just in the rankings, but in the everyday quality of the research and training we provide. I deeply appreciate whatever support you can share with us as we continue to grow.

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Graduate Spotlight

Hear from our PhD program’s upcoming graduate, Wei Li

PhD in Statistics, Spring 2026

Wei Li

Wei came to WashU in 2021 from the University of Glasgow, after a one-year deferral due to the COVID-19 pandemic. She chose to pursue her PhD in Statistics due to a lifelong love of Math- particularly its’ factual, objective nature.

During her time in the department, Wei learned how to balance her life and how to be independent. As an only child of “the lonely generation” coming out of a global pandemic, she was surprised to find that being a PhD student in SDS meant being part of a community. “The friends I’ve made here are beyond my expectations... there are so many favorite moments that cannot be replicated,” she shared. “In the moment, you don’t realize that you’re making memories, it’s only when looking back that you realize how important those moments were.” Wei talked about taking first day of school photos with her friends, how proud she felt when she submitted her first paper, and how surrounded by support she felt when so many of her peers showed up to congratulate her after she defended her thesis.

After she graduates this Spring, Wei will relocate to the University of Madison- Wisconsin, where she will work with Dr. Yinqiu He as a postdoctoral researcher. Her PhD advisor, Dr. Robert Lunde, met He at a conference, and later connected the two. Wei’s research focuses on network analysis, and bridging gaps due to dependency. When she spoke with Dr. He, Wei felt that their research would align, and drew connections to illustrate how she could help further Dr. He’s work.

Wei emphasized the importance of networking- from her initial decision to come to WashU, to her upcoming postdoctoral appointment. “The support of others made me feel like I could do it”.

Chao Cheng, Assistant Professor of Statistics & Data Science

Dr. Cheng’s research lies at the intersection of causal inference and machine learning, with the goal of developing methods that are both theoretically rigorous and practically implementable. One central theme of his work is integrating semiparametric inference tools with modern machine learning algorithms to improve robustness and efficiency when studying complex causal effects, including mediation effects, quantile treatment effects, and network or interference effects. One of his long-term goals is applying these methods to health data settings. Ultimately, he aims to develop causal methods that preserve statistical rigor while remaining directly relevant to real-world scientific and policy questions.

Joe Feldman, Assistant Professor of Statistics & Data Science

Dr. Feldman's current research takes place at the intersection of Generative AI and statistical inference. “We develop ‘light-weight’ deep generative models that retain the expressiveness of modern AI tools but are more statistically interpretable. I truly believe that statisticians will play a pivotal role in both education and research in the AI age. Statistical tools and methods are more important than ever when it comes to understanding, fundamentally, AI systems.”

Distinguished Speaker

Among many other speakers during Fall 2025 and Spring 2026, SDS hosted our distinguished guest speaker, Xihong Lin

Chair and Professor of Statistics and Professor of Biostatistics at Harvard University

  • She presented her talk, "Harnessing Synthetic Data from Generative AI for Statistical Inference"

“My two years at UChicago as a William H. Kruskal Instructor have been incredibly rewarding. Since first joining UChicago in 2022 as a visiting student, I have been introduced to new research problems at the intersection of time series and learning theory. This transition has allowed me to learn enormously in new areas and has led me to think more deeply about the role of statisticians in the new era of AI. My PhD training in traditional statistics at WashU provided a strong foundation, but it also became clear to me that our field must continue to adapt to the rapidly evolving needs of data science as AI tools develop at such a fast pace.”

Jiaqi Li

PhD in Statistics, Spring 2024

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Spring 2026 Newsletter