The three winners of the 2022 IMS Lawrence D. Brown PhD Student Awards were previously announced here. Rungang Han, Duke University, Rong Ma, Stanford University, and Chan Park, University of Wisconsin–Madison, will present their papers in a special session at the IMS London meeting (June 27–30, 2022).

Rungang Han was a PhD student at University of Wisconsin–Madison, advised by Anru Zhang. His bachelor’s degree was from the School of Mathematical Sciences at Zhejiang University in 2017. He describes his research interests: “I am broadly interested in methodology and theory in high-dimensional statistics, machine learning and optimization. My recent interest focuses on challenges in large-scale statistical matrix/tensor inference. These challenges arise as the classic methods suffer from either statistical sub-optimality or computational limitation. In theory, I focus on studying the statistical guarantee for general non-convex optimization methods; in practice, I develop efficient algorithms in applied data science.” Rungang’s paper is titled, “Exact Clustering in Tensor Block Model: Statistical Optimality and Computational Limit.” 

Rong Ma is a postdoctoral scholar in the Statistics Department at Stanford University, advised by David Donoho; his PhD in Biostatistics was awarded from the University of Pennsylvania, jointly advised by T. Tony Cai and Hongzhe Li. He says, “My research interest, broadly speaking, lies in understanding and underpinning of the foundations of data science from a statistical point of view. My current research focuses on (i) statistical inference for large disordered systems and high-dimensional models, (ii) improving theoretical cognitions of data visualization and dimension reduction algorithms, and (iii) their applications in interdisciplinary research such as microbiomics, integrative genomics, among many other fields.” He added, “I am very pleased and honored to be selected for the IMS Brown Award!” Rong’s paper is titled, “Statistical Inference for High-Dimensional Generalized Linear Models with Binary Outcomes.” 

Chan Park’s broad research interest is “to develop flexible, nonparametric methods to infer causal effects in dependent and/or clustered data and to show the optimality of these methods. To this end, my paper (“Assumption-Lean Analysis of Cluster Randomized Trials in Infectious Diseases for Intent-to-Treat Effects and Network Effects”) proposes a new bound-based method that uses pre- treatment covariates, classification algorithms, and a linear program to obtain sharp bounds of the network causal effects that are not point-identified under the presence of interference (i.e. effect spillovers) and noncompliance in cluster randomized trials.” Chan also expressed his gratitude for “this once-in-a-lifetime experience,” adding, “I want to thank Dr. Brown’s family and friends who made this opportunity possible. I also want to thank my ‘perfect’ advisor Dr. Hyunseung Kang who helped me during the doctoral program. Lastly, I am grateful to my beloved wife and my family for their moral support. This achievement will motivate my future research to contribute to statistics and related fields of study. I am planning to graduate in May 2022 and am looking for a post-doctoral position. Congratulations to the other two recipients, and I look forward to meeting you in London!”

This year’s Brown Award winners, Xin Bing, Ilmun Kim and Yichen Zhang, presented their papers at the 2021 virtual JSM. You can watch a video of their talks (and other special IMS lectures) on our new YouTube channel (see the list of videos so far here).

Lawrence D. Brown (1940-2018), Miers Busch Professor and Professor of Statistics at The Wharton School, University of Pennsylvania, had a distinguished academic career. He was known for his groundbreaking work in a broad range of fields including decision theory, recurrence and partial differential equations, nonparametric function estimation, minimax and adaptation theory, and the analysis of call-center data. Professor Brown’s firm dedication to all three pillars of academia—research, teaching, and service—sets an exemplary model for generations of new statisticians. The IMS Lawrence D. Brown Ph.D. Student Award advocates for the values by which he lived. Donations are welcome to the IMS Lawrence D. Brown PhD Student Award Fund: There’s a list of the donors to this fund (and other IMS funds) on pages 8–10 of the December 2021 issue, or here.