Heejong Bong

Research Fellow. Department of Statistics, University of Michigan, Ann Arbor.

prof_pic.jpg

128-C Baker Hall

Carnegie Mellon University

5000 Forbes Ave.

Pittsburgh, PA 15213

Currently, I am serving as a postdoctoral research fellow within the Department of Statistics at the University of Michigan, Ann Arbor. Under the guidance of Professors Liza Levina and Ji Zhu, my current research pursuits problems related to causal inference on networks. My prior research interests have included spatiotemporal methods, graphical models, causal inference on time-series data, high-dimensional central limit theorem, and ranking from pairwise comparisons. For a comprehensive overview of my ongoing and prior research endeavors, I invite you to peruse the details outlined on my dedicated projects page.

In a recent milestone, I attained my Ph.D. in Statistics from Carnegie Mellon University (CMU), under guidance of Professors Robert E. Kass and Valérie Ventura. my doctoral research revolved around the innovation and rigorous examination of statistical methodologies. These methodologies were specifically tailored for the task of uncovering communication among brain regions, drawing insights from intricate neural recordings. To surmount the intricacies posed by high-dimensional data, I pioneered the integration of latent factor time-series techniques and matrix-variate graphical models. Subsequent to the successful completion of my Ph.D., I spent a productive year as a postdoctoral researcher in the same department. This year proved to be a rich period of collaboration, involving joint ventures with a constellation of accomplished scholars. Notably, I had the privilege to collaborate on three impactful research projects with Professors Robert E. Kass, Valérie Ventura, Larry Wasserman, Zhao Ren, Alessandro Rinaldo, and Arun Kuchibhotla.

news

Aug 25, 2023 I started a postdoctoral research fellow position in the Department of Statistics at the University of Michigan, Ann Arbor.
Jul 6, 2022 I defended my thesis ‚ÄúDiscovery of Functional Predictivity across Brain Regions from Local Field Potentials!‚ÄĚ The thesis document is available at KiltHub or here.
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.

selected publications

  1. JNP
    Identification of interacting neural populations: Methods and statistical considerations
    Kass, Robert E,  Bong, Heejong, Olarinre, Motolani, Xin, Qi, and Urban, Konrad
    Journal of Neurophysiology 2023
  2. Dual induction CLT for high-dimensional m-dependent Data
    Bong, Heejong, Kuchibhotla, Arun K, and Rinaldo, Alessandro
    arXiv preprint 2023