Renzhi Jing

I am a climate scientist and data scientist working at the intersection of climate change, population health and extreme weather resilience. My research combines statistical modeling, machine learning, geospatial analysis and causal inference to study how physical environmental changes interact with human populations across space and time, and how these interactions shape health, education, and economic well-being — particularly in low- and middle-income countries.

I am currently a Sustainability Data Scientist at Google. I received my Ph.D. from Princeton University and completed my postdoctoral training at Stanford University. I hold a B.S. in Atmospheric Physics and a B.A. in Chinese Language and Literature from Peking University.

Contact: Email Scholar

Publications

2026

ECCVLineGraph2Road: Structural graph reasoning on line graphs for road network extraction

Zhengyang Wei, Renzhi Jing, Yiyi He, Jenny Suckale

European Conference on Computer Vision (ECCV), 2026
PNASThe debt burden of tropical cyclones and climate change

June Choi, Renzhi Jing, Christopher W. Callahan, Marshall Burke, Noah S. Diffenbaugh

Proceedings of the National Academy of Sciences

2025

GRLSpatial patterns of historical changes in human heat stress disagree across metrics

Qinqin Kong, Renzhi Jing, Colin Raymond, Cascade Tuholske, Sam Heft-Neal, Zachary Wagner, Zetianyu Wang, Andrew Zimmer, Matthew Huber, Eran Bendavid

Geophysical Research Letters, 2025
NatureWildfire smoke exposure and mortality burden in the USA under climate change

Minghao Qiu, Jessica Li, Carlos F. Gould, Renzhi Jing, Makoto Kelp, Marissa L. Childs, Jeff Wen, Yuanyu Xie, Meiyun Lin, Mathew V. Kiang, Sam Heft-Neal, Noah S. Diffenbaugh, Marshall Burke

Nature 647, 935–943, 2025
Science AdvancesThe impact of tropical cyclone exposure on infant mortality in low- and middle-income countries

Zetianyu Wang, Renzhi Jing, Sam Heft-Neal, Aaron Clark-Ginsberg, Debarati Guha-Sapir, Eran Bendavid, Zachary Wagner

Science Advances 11 (21), eadt9640, 2025
PNASDecreased likelihood of schooling as a consequence of tropical cyclones: Evidence from 13 low- and middle-income countries

Renzhi Jing, Sam Heft-Neal, Zetianyu Wang, Minghao Qiu, Marshall Burke, Zachary Wagner, Eran Bendavid

Proceedings of the National Academy of Sciences 122 (18), e2413962122, 2025

2024

JAMESTC-GEN: Data-driven tropical cyclone downscaling using machine learning-based high-resolution weather model

Renzhi Jing, Jianxiong Gao, Yunuo Cai, Dazhi Xi, Yinda Zhang, Yanwei Fu, Kerry Emanuel, Noah Diffenbaugh, Eran Bendavid

Journal of Advances in Modeling Earth Systems 16, e2023MS004203, 2024

Ranked within the top 10% of most-viewed papers published by the journal in 2024
J. ClimateUncertainties inherent from large-scale climate projections in the statistical downscaling projection of North Atlantic tropical cyclone activity

Dazhi Xi, Ning Lin, Renzhi Jing, Patrick Harr, Michael Oppenheimer

Journal of Climate, 2024

2023

NatureGlobal population profile of tropical cyclone exposure from 2002 to 2019

Renzhi Jing, Sam Heft-Neal, Daniel R. Chavas, Max Griswold, Zetianyu Wang, Aaron Clark-Ginsberg, Debarati Guha-Sapir, Eran Bendavid, Zachary Wagner

Nature, 2023

2022

Scientific ReportsIncreasing typhoon impact and economic losses due to anthropogenic warming in Southeast China

Mingfeng Huang, Qing Wang, Maofeng Liu, Ning Lin, Yifan Wang, Renzhi Jing, Jianping Sun, Hiroyuki Murakami, Wenjuan Lou

Scientific Reports 12 (1), 14048, 2022
JWEIATropical cyclone full track simulation in the western North Pacific based on random forests

Mingfeng Huang, Qing Wang, Renzhi Jing, Wenjuan Lou, Yi Hong, Lizhong Wang

Journal of Wind Engineering and Industrial Aerodynamics 228, 105119, 2022

2021

JWEIATyphoon wind hazard estimation by full-track simulation with various wind intensity models

Mingfeng Huang, Qing Wang, Qiang Li, Renzhi Jing, Ning Lin, Lizhong Wang

Journal of Wind Engineering and Industrial Aerodynamics 218, 104792, 2021
J. ClimateA comparison of tropical cyclone projections in a high-resolution global climate model and from downscaling by statistical and statistical-deterministic methods

Renzhi Jing, Ning Lin, Kerry Emanuel, Gabriel Vecchi, Thomas R. Knutson

Journal of Climate 34 (23), 9349–9364, 2021

2020

JAMESAn environment-dependent probabilistic tropical cyclone model

Renzhi Jing, Ning Lin

Journal of Advances in Modeling Earth Systems 12 (3), e2019MS001975, 2020

Recognized by the Research & Development Council of New Jersey with the 2026 Edison Patent Award

2019

J. ClimateTropical cyclone intensity evolution modeled as a dependent hidden Markov process

Renzhi Jing, Ning Lin

Journal of Climate 32 (22), 7837–7855, 2019

2017

Monthly Weather ReviewA statistical investigation of the dependence of tropical cyclone intensity change on the surrounding environment

Ning Lin, Renzhi Jing, Yuyan Wang, Emmi Yonekura, Jianqing Fan, Lingzhou Xue

Monthly Weather Review 145 (7), 2813–2831, 2017

Patent

Ning Lin and Renzhi Jing. “System and method for environment-dependent probabilistic tropical cyclone modeling.” U.S. Patent Application 17/629,581. Licensed to One Concern, Jupiter Intelligence, and BP.

News

Oct 2025Our paper on how heat stress trends disagree across metrics is out in Geophysical Research Letters.
Sep 2025Our paper on wildfire smoke and mortality under climate change is out in Nature.
Sep 2025Joined Google as a Sustainability Data Scientist.
May 2025New paper in Science Advances on tropical cyclone exposure and infant mortality.
Apr 2025New paper in PNAS on tropical cyclones and loss of schooling in 13 low- and middle-income countries.

Experience

Sustainability Data Scientist, Google
Research Consultant (part-time), UNICEF Evaluation Office
Postdoctoral Researcher, Department of Health Policy & Woods Institute for the Environment, Stanford University (advisor: Eran Bendavid)
Data Scientist II, Disney+ Hotstar
Research Scientist Consultant (part-time), Cervest AI
Data Science Fellow, Insight Data Science

Education

Ph.D. in Natural Hazard and Risk Analysis, Princeton University
Thesis: Statistical Modeling of Tropical Cyclone Climatology
Certificate in Statistics and Machine Learning, Princeton University
B.S. in Atmospheric Physics (with honor) and B.A. in Chinese Language and Literature (double major), Peking University

Honors & Awards

National Institutes of Health (NIH) T32 Fellowship
The Katharine McCormick Fellowship
Stanford Maternal and Child Health Research Postdoctoral Fellowship
Stanford Dean’s Postdoctoral Fellowship
Student Award, Symposium on Hurricane Risk in a Changing Climate
Award for Excellence, School of Engineering and Applied Science, Princeton University
Intellectual Property Accelerator Fund
NeurIPS Climate Change Workshop Travel Grant
Princeton Graduate Fellowship
Outstanding Graduate Award, Peking University (top 5%)
May Fourth Scholarship, Peking University

Teaching & Mentoring

Research mentor, Stanford graduate students
Mentor, Stanford Small Science Group (10-week research program for local community college students)
Instructor, GeoKids (hands-on earth science lessons for elementary school children)
Teaching Assistant, CEE 460 Risk Analysis, Princeton University

Service

Reviewer — Nature Communications; Earth’s Future; Scientific Reports; Geomatics, Natural Hazards and Risk; Stochastic Environmental Research and Risk Assessment; Natural Hazards and Earth System Sciences; Climate Change AI Innovation Grants
Ambassador, Women in Data Science (WiDS)
Program Ambassador, Center for Statistics and Machine Learning, Princeton University