Zijian Guo

Zijian Guo is an Associate Professor in the Department of Statistics at Rutgers University, School of Arts and Sciences. He holds a PhD in Statistics from the University of Pennsylvania (2017) and a B.S. in Mathematics from The Chinese University of Hong Kong (2012). His research focuses on high-dimensional statistical inference, causal inference with instrumental variables, nonparametric methods, and applications in health and genomics data.

Education:

• Ph.D., Statistics, The Wharton School, University of Pennsylvania (2017)
• B.S. (First Honor), Mathematics, The Chinese University of Hong Kong (2012)

Research Interests:
His work addresses uncertainty quantification in high-dimensional models, causal inference with invalid instruments, and machine learning applications in healthcare. Notable contributions include federated meta-learning, semi-supervised risk prediction, and robust Mendelian randomization analysis.

Grants:

• NIH R01LM013614 (Co-PI): Semi-supervised Approaches to Denoising Electronic Health Records
• NIH R01GM140463 (PI): Predictive Modeling with High-Dimensional Incomplete Data
• NSF DMS 2015373 (Co-PI): Repro Sampling Method for Discrete Parameter Inference

Awards:

• ICSA New Researcher Award (2019)
• Bernoulli Society New Researcher Award Honorable Mention (2023)
• President Gutmann Leadership Award (2017)

He has developed R packages like SIHR, RobustIV, and DDL for high-dimensional statistical inference. Teaching includes Financial Data Mining and Advanced Modern Statistical Inference at the PhD level.