Peng Zheng, PhD, is Acting Assistant Professor of Health Metrics Sciences at the at the Institute for Health Metrics and Evaluation (IHME) at the University of Washington. Dr. Zheng specializes in statistical modeling, optimization, and algorithm design for inference, inversion, and machine learning. He designed and implemented the MR-BRT software package for meta-analysis and evidence score work, along with underlying open source LimeTr and Xspline packages that improve on the general state of the art for mixed effects models and B-splines. Dr. Zheng engages with researchers across many projects on a range of technical problems including risk factor analysis, meta-analysis, robust modeling, and frontier analysis; implements, tests, and helps deploy these solutions across IHME.
Dr. Zheng earned a PhD in Applied Mathematics from University of Washington.
IHME was established at the University of Washington in Seattle in 2007. Its mission is to improve health through better health evidence.
Zheng P, Barber R, Sorensen R, Murray C, Aravkin A. Trimmed Constrained Mixed Effects Models: Formulations and Algorithms. Journal of Computational and Graphical Statistics. 4 January 2021. doi: 10.1080/10618600.2020.1868303.
IHME COVID-19 Forecasting Team. Modeling COVID-19 scenarios for the United States. Nature Medicine. 23 October 2020. doi:10.1038/s41591-020-1132-9.
GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 17 October 2020. doi:10.1016/S0140-6736(20)30752-2.
GBD 2019 Universal Health Coverage Collaborators. Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 27 August 2020. doi:10.1016/S0140-6736(20)30750-9.