Bingxin Zhao
- Assistant Professor of Statistics and Data Science
Contact Information
- Primary Email:
bxzhao@wharton.upenn.edu
- office Address:
413 Academic Research Building
265 South 37th Street
Philadelphia, PA 19104
Research Interests: statistical methods & applications to big data, high-dimensional statistics, biomedical & biological data science, environmental data science, and social data science
Links: Personal Website, Curriculum Vitae
Overview
Education
Ph.D. in Biostatistics, University of North Carolina at Chapel Hill, 2020
M.S. in Biostatistics, University of Florida, 2016
B.Hist. History & B.Econ, Mathematical Statistics, Xiamen University, 2014
Academic Positions Held
Assistant Professor of Statistics (Tenure-track), Purdue University, 2020-2022
Research
Bingxin Zhao and Fei Zou (2022), On polygenic risk scores for complex traits prediction, Biometrics, (in press).
Bingxin Zhao, Fei Zou, Hongtu Zhu (2022), Cross-trait prediction accuracy of summary statistics in genome-wide association studies, Biometrics, (in press).
Esther Annan, Jinghui Guo, Aracely Angulo-Molina, Wan Fairos Wan Yaacob, Nasrin Aghamohammadi, Timothy C. Guetterman, Sare Ilknur Yavasoglu, Kevin Bardosh, Nazri Che Dom, Bingxin Zhao, Uriel A. Lopez-Lemus, Latifur Khan, Uyen-Sa D.T. Nguyen, Ubydul Haque (2022), Community acceptability of dengue fever surveillance using unmanned aerial vehicles: A cross-sectional study in Malaysia, Mexico, and Turkey, Travel Medicine and Infectious Disease, 49.
Bingxin Zhao, Tengfei Li, Yue Yang, Xifeng Wang, Tianyou Luo, Yue Shan, Ziliang Zhu, Di Xiong, Mads E. Hauberg, Jaroslav Bendl, John F. Fullard, Panagiotis Roussos, Yun Li, Jason L. Stein, Hongtu Zhu (2022), Common genetic variation influencing human white matter microstructure, Science, 372 (6548).
Bingxin Zhao, Tengfei Li, Yujue Li, Zirui Fan, Di Xiong, Xifeng Wang, Mufeng Gao, Stephen M. Smith, Hongtu Zhu (Working), An atlas of trait associations with resting-state and task-evoked human brain functional architectures in the UK Biobank.
Bingxin Zhao, Tengfei Li, Stephen M. Smith, Di Xiong, Xifeng Wang, Yue Yang, Tianyou Luo, Ziliang Zhu, Yue Shan, Nana Matoba, Quan Sun, Yuchen Yang, Mads E. Hauberg, Jaroslav Bendl, John F. Fullard, Panagiotis Roussos, Weili Lin, Yun Li, Jason L. Stein, Hongtu Zhu (2022), Common variants contribute to intrinsic human brain functional networks, Nature Genetics, 54, pp. 508-517.
Bingxin Zhao, Xiaochen Yang, Hongtu Zhu (Working), Estimating trans-ancestry genetic correlation with unbalanced data resources.
Bingxin Zhao, Shurong Zheng, Hongtu Zhu (Working), On block-wise and reference panel-based estimators for genetic data prediction in high dimensions.
Bingxin Zhao, Tengfei Li, Zirui Fan, Yue Yang, Xifeng Wang, Tianyou Luo, Jiarui Tang, Di Xiong, Zhenyi Wu, Jie Chen, Yue Shan, Chalmer Tomlinson, Ziliang Zhu, Yun Li, Jason L. Stein, Hongtu Zhu (Working), Heart-brain connections: phenotypic and genetic insights from 40,000 cardiac and brain magnetic resonance images.
Bingxin Zhao, Tianyou Luo, Tengfei Li, Yun Li, Jingwen Zhang, Yue Shan, Xifeng Wang, Liuqing Yang, Fan Zhou, Ziliang Zhu, Alzheimer’s Disease Neuroimaging Initiative, Pediatric Imaging, Neurocognition and Genetics, Hongtu Zhu (2021), Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits, Nature Genetics, 51, pp. 1637-1644.
Teaching
Current Courses (Spring 2023)
STAT4770 - Intro To Python Data Sci
The goal of this course is to introduce the Python programming language within the context of the closely related areas of statistics and data science. Students will develop a solid grasp of Python programming basics, as they are exposed to the entire data science workflow, starting from interacting with SQL databases to query and retrieve data, through data wrangling, reshaping, summarizing, analyzing and ultimately reporting their results. Competency in Python is a critical skill for students interested in data science. Prerequisites: No prior programming experience is expected, but statistics, through the level of multiple regression is required. This requirement may be fulfilled with Undergraduate courses such as Stat 1020, Stat 1120.
STAT4770401 ( Syllabus )
STAT4770402 ( Syllabus )
OIDD4770 - Intro To Python Data Sci
The goal of this course is to introduce the Python programming language within the context of the closely related areas of statistics and data science. Students will develop a solid grasp of Python programming basics, as they are exposed to the entire data science workflow, starting from interacting with SQL databases to query and retrieve data, through data wrangling, reshaping, summarizing, analyzing and ultimately reporting their results. Competency in Python is a critical skill for students interested in data science. Prerequisites: No prior programming experience is expected, but statistics, through the level of multiple regression is required. This requirement may be fulfilled with Undergraduate courses such as Stat 1020, Stat 1120.
OIDD4770401 ( Syllabus )
OIDD4770402 ( Syllabus )
All Courses
MATH5999 - Independent Study
Study under the direction of a faculty member. Hours to be arranged.
OIDD4770 - Intro To Python Data Sci
The goal of this course is to introduce the Python programming language within the context of the closely related areas of statistics and data science. Students will develop a solid grasp of Python programming basics, as they are exposed to the entire data science workflow, starting from interacting with SQL databases to query and retrieve data, through data wrangling, reshaping, summarizing, analyzing and ultimately reporting their results. Competency in Python is a critical skill for students interested in data science. Prerequisites: No prior programming experience is expected, but statistics, through the level of multiple regression is required. This requirement may be fulfilled with Undergraduate courses such as Stat 1020, Stat 1120.
STAT4770 - Intro To Python Data Sci
The goal of this course is to introduce the Python programming language within the context of the closely related areas of statistics and data science. Students will develop a solid grasp of Python programming basics, as they are exposed to the entire data science workflow, starting from interacting with SQL databases to query and retrieve data, through data wrangling, reshaping, summarizing, analyzing and ultimately reporting their results. Competency in Python is a critical skill for students interested in data science. Prerequisites: No prior programming experience is expected, but statistics, through the level of multiple regression is required. This requirement may be fulfilled with Undergraduate courses such as Stat 1020, Stat 1120.
STAT9910 - Sem in Adv Appl of Stat
This seminar will be taken by doctoral candidates after the completion of most of their coursework. Topics vary from year to year and are chosen from advance probability, statistical inference, robust methods, and decision theory with principal emphasis on applications.
STAT9990 - Independent Study
Written permission of instructor and the department course coordinator required to enroll.
Awards and Honors
- Dean’s Distinguished Dissertation Award, The Graduate School, UNC-Chapel Hill, 2022 Description
The highest level of graduate student scholarship at UNC-Chapel Hill
- Kupper Dissertation Publication Award, Department of Biostatistics, UNC-Chapel Hill, 2022 Description
Recognition of the best doctoral dissertation-based paper appearing in a prestigious biostatistics journal completed during a calendar year
- ENAR Distinguished Student Paper Award, 2020