About Me

I am currently a Biostatistician at Roche, and a part-time statistical consultant at Yale University. Before this, I was the postdoc fellow working with Dr. Donna Spiegelman and Dr. Laura Forastiere in the Center for Methods in Implementation and Prevention Science (CMIPS), Yale School of Public Health, Yale University.

Before joining CMIPS, I obtained my Ph.D degree in Biostatistics from the University of Waterloo, supervised by Dr. Grace Y. Yi. My thesis won the Pierre Robillard Award in Canada, 2021

I received my Master of Science in Public Health in Biostatistics from Rollins School of Public Health, Emory University and BA in Statistics from Southwestern University of Finance and Economics.

Research Interests

Methodology:

Matrix-variate data analysis, Measurement Error, Causal Inference with Network based Design, Bayesian Analysis, Regression for High-dimensional data, Experimental Study Designs

Applications:

Designing and analyzing complex health studies using innovative statistical methods in HIV research, Brian Imaging, and Oncology

Publications and Working Papers

• Fang, J. and Yi, G.Y. (2021). Matrix-Variate Logistic Regression with Measurement Error. Biometrika, 108.(1), 83-97.
• Fang, J. and Yi, G.Y. (2021). Imputation and Likelihood Methods for Matrix-Variate Logistic Regression with Response Misclassification. The Canadian Journal of Statistics, 2021.
• Fang, J. and Yi, G.Y. (2022). Regularized Matrix-Variate Regression with Misclassification in Binary Response. The Journal of Statistical Planning and Inference, 49(4), 1298-1316.
• Thompson, M. E., Sedransk J., Fang, J. and Yi, G.Y. (2022). A Bayesian pairwise composite likelihood with survey data. Survey Methodology. 48(1), 73-93.
• Fang, J. and Yi, G.Y. Bayesian Approach for Matrix-Variate Logistic Regression with/without Response Misclassification and Structural Measurement Error. (2023). Statistics and Computing, 33 (6), 121
• Fang, J. , Spiegelman, D., Buchanan, A., Forastiere L. (2023+). Design of network-based studies to estimate individual and spillover effects and identify key influencer. arXiv preprint arXiv:2308.00791
• He, W., Yi, G.Y., and Fang, J. (2023+). Prediction with Response Error, with an Application to the Prostate Cancer Imaging Study. To be submitted for publication shortly.

Honors and Awards

• The Pierre Robillard Award for the best PhD thesis in the areas of probability and statistics defended in Canada, 2021
• The Sprott Award for the best Ph.D. Thesis Proposal, 2019, University of Waterloo
• Statistics and Actuarial Science Graduate Teaching Award, Winter 2017, University of Waterloo

Notable Scholarships

• MATH Senate Graduate Scholarship, Winter 2020, University of Waterloo
• Statistics and Actuarial Science Chair’s Award, Fall 2019, University of Waterloo

Conference and Academic Presentations

• Joint Statistical Meetings 2021, Virtual. Contributed Talk: Leveraging Influencers in the Design of Network-Structured Studies to Estimate Direct and Spillover Effects, 2021.
• Statistical Society of Canada 2020 Annual Meeting, Virtual. Invited Talk: Matrix-Variate Logistic Regression with Measurement Error, 2020.
• Statistical Society of Canada 2019 Annual Meeting, University of Calgary, Calgary, Alberta. Contributed Talk: Imputation and Likelihood Methods for Matrix-Variate Logistic Regression with Response Misclassification, 2019.
• Statistical Society of Canada 2018 Annual Meeting, McGill University, Montreal, Québec. Contributed Talk: Matrix-Variate Logistic Regression with Measurement Error, 2018.
• 2nd SAS/WatRISQ Research Presentation Day, University of Waterloo, Waterloo, Ontario. Contributed Talk: Matrix-Variate Logistic Regression with Measurement Error, 2018.

Research Experience

• Research Assistant, The Mayberg’s Lab, Department of Psychology, School of Medicine, Emory University, Atlanta, GA, Jun 2015 - May 2016.

• Research Assistant, Center for Global Safe Wash, Rollins School of Public Health, Emory University, Atlanta, GA, Nov 2014 - May 2016.

• Member, The Center for Biomedical Imaging Statistics, Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, Aug 2014 - May 2016.

Teaching Experience

• Teaching Assistant at Yale Univeristy
  • BIS 629: Advanced Methods for Implementation and Prevention Science
• Teaching Assistant at Univesity of Waterloo
  • Stat 431: Generalized Linear Regression
  • Stat 371: Applied Linear Models and Process Improvement for Business
  • Stat 331: Applied Linear Models
  • Stat 230: Probability
• Teaching Assistant at Emory Univeristy
  • Applied Biostatistics I

Peer-review Service

• Statistics in Medicine

Technical Skills

R, Matlab, Python, SAS, SQL