4144 Newmark Civil Engineering Laboratory
205 North Mathews Ave.
Urbana, IL 61801-2352
I am actively seeking research opportunities in Environmental Data Science and Sustainable Urban Systems Modeling and Engineering (e.g., Urban Heat Stress and Air Quality).
SHORT BIO | (Academic Curriculum Vitae) | (One-Page Résumé)
I am currently a Ph.D. Candidate (Defense Passed, Pending Revision of Thesis) at the University of Illinois studying Environmental Engineering in Civil Engineering with a concentration in Computational Science and Engineering, supervised by Prof. Nicole Riemer and Prof. Lei Zhao. I closely work with Prof. Matthew West and Prof. Christopher Tessum. I am also a Data Scientist Intern at Bayer Innovation Center at University of Illinois, mainly working for The Climate Corporation (2018 - Present).
I was a Graduate Teaching Assistant at the Department of Civil and Environmental Engineering (CEE) @ Illinois during academic year 2019–2020; a Graduate Assistant at the Department of Computer Science (CS) @ Illinois during academic year 2018–2019; an ORISE Ph.D. Intern/Researcher at Oak Ridge National Laboratory (ORNL) during Summer 2018, working with National Center for Computational Sciences - Advanced Data and Workflow Group; and a Data Scientist Intern during Spring 2018 at Monsanto Innovation Center where I mainly worked for The Climate Corporation.
I am passionate about learning and solving practical problems using Data Science (DS), Artificial Intelligence (AI), Cloud Computing, and High-Performance Computing (HPC). My work focuses on computer simulation, modeling, and spatiotemporal analysis of 1) urban climate and environment, 2) aerosol properties, and 3) complex agriculture-environment nexus system.
- 09/2019 – 12/2020: Data Scientist Intern at Bayer AG (Crop Science Division)
- 08/2019 – 05/2020: Graduate Teaching Assistant at University of Illinois
- 09/2018 – 07/2019: Data Scientist Intern at Bayer AG (Crop Science Division)
- 08/2018 – 05/2019: Graduate Assistant at University of Illinois
- 05/2018 – 08/2018: Researcher at Oak Ridge National Labratory (ORNL)
- 01/2018 – 05/2018: Data Scientist-UIUC Innovation Center- at Monsanto Company
- Ph.D., Environmental Engineering in Civil Engineering, University of Illinois at Urbana-Champaign, 2021 (Expected)
- M.S., Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, 2016
- B.Eng., Biosystems Engineering (Top 2 "A+" Agricultural Engineering Program in China), Zhejiang University, 2015
- Student, English Language Courses, The University of Manchester, 2013
- Introduction to University Life and British Cultural Studies, Univeristy Language Centre (28 January 2013 – 21 February 2013)
- AI for Earth, Microsoft, 2020
- Earth on AWS & Amazon Sustainability Data Initiative, Amazon, 2020
- Kuck Computational Science & Engineering Scholarship, Grainger College of Engineering, UIUC, 2019
- Loh Kwan Chen Fellowship, College of Engineering, UIUC, 2019
- Travel Grant, Deep Learning for Science School at Lawrence Berkeley National Laboratory (Berkeley Lab), 2019
- Outstanding Poster Award, School of Earth, Society, & Environment, UIUC, 2019
- Travel Grant, 18th Conference on Artificial and Computational Intelligence and its Applications to the Environmental Sciences (18 AI), American Meteorological Society (AMS) 99th Annual Meeting, 2018
- Finalist, SMOKY MOUNTAIN Computational Sciences and Engineering Conference (SMC) Data Challenge, 2018
- First Place, Student Paper Award, Association of Overseas Chinese Agricultural, Biological, and Food Engineers (AOCABFE), 2016
- Tau Beta Pi (The Engineering Honor Society), inducted 2016
- Alpha Epsilon (The Honor Society of Agricultural, Biological & Food Engineering), inducted 2015
SELECTED CERTIFICATES AND GRADUATE COURSEWORK
- Machine Learning, issued by Stanford University on Coursera, 2018 (Verifiable Link)
- Deep Learning, a 5-course specialization by deeplearning.ai on Coursera. Specialization Certificate earned on June 8, 2018 (Verifiable Link)
- Fundamental Engineer (FE) in Environmental Engineering, issued by NCEES, 2017 (Verifiable Link)
- Community Earth System Model (CESM) Tutorial, 2019 (Certificate)
- Statistical Learning Learning and Data Analytics (UIUC)
- STAT 542 / CSE 542, Statistical Learning (A+)
- STAT 420, Methods of Applied Statistics (A+)
- GEOG 480, Principles of GIS (Geographic Information System) (A)
- Atmospheric Science, Air Quality, and Environmental Engineering (UIUC)
- ATMS 420, Atmospheric Chemistry (A+)
- CEE 545, Aerosol Sampling and Analysis (A+)
- CEE 442, Environmental Engineering Principles, Physical (A)
Agriculture, Atmospheric Science, Computational Science and Engineering, Data Science, Environment
SELECTED RESEARCH PRODUCTS
(First Author Only)
- Zheng, Z., Yang, L., Gates, R. S., Wu, J., & Wang, X. (2017). Impedance-based moisture content sensor assessment for gas-phase biofilter media. Transactions of the ASABE, 60(5), 2163-2173. doi: 10.13031/trans.12335. (View)
- Zheng, Z., Lin, X., Zhu, S., He, J., Cao, Y., & Ye, Z. (2016). Investigation on the bactericidal efficacy of atomized slightly acidic electrolyzed water. Chinese Journal of Disinfection, 33(4), 312-317. doi: 10.11726/j.issn.1001-7658.2016.04.004 (Peer-viewed, In Chinese). (View)
- Zheng, Z. (2016). Impedance-based moisture content sensor assessment for gas-phase biofilters. Master thesis, Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign. (View)
- Zheng, Z., Yang, L., & Wang, X. (2016). Monitoring moisture content of gas-phase biofilter based on impedance under different conditions. In 2016 ASABE Annual International Meeting, No. 162461021 (pp. 14). American Society of Agricultural and Biological Engineers. doi:10.13031/aim.20162461021. (View)
- Zheng, Z., Oleson, K. W., Riemer, N., & Zhao, L. (2020). Large model parameter and structural uncertainties in global projections of urban heat waves. doi:10.31223/osf.io/f5pwa. (View)
- Zheng, Z., Curtis, J. H., Yao, Y., Gasparik, J. T., Anantharaj, V. G., Zhao, L., West, M., & Riemer, N. (2020). Estimating Submicron Aerosol Mixing State at the Global Scale with Machine Learning and Earth System Modeling. doi:10.31223/osf.io/fycuq. (View)
- Zheng, Z., & Zhao, L. (2020). Future Climate-Driven Risks to Urban Area. Oral Presentation in Night of Ideas: Alive! (part of La Nuit des Idées, a global series coordinated worldwide by the Institut Français; this event is organized by the Field Museum and the Consulate General of France in Chicago), Chicago, IL., January 31. (Media)
- Zheng, Z., & Riemer, N. (2019). Coarse-Graining of Aerosol Mixing State Metrics Empowered by Machine Learning. Oral Presentation in International Aerosol Modeling Algorithms (IAMA) Conference 2019, Davis, CA., December 5. (Invited Speaker)
- Zheng, Z., Yang, L., & Wang, X. (2016). Monitoring moisture content of gas-phase biofilter based on impedance under different conditions. Oral Presentation in 2016 ASABE Annual International Meeting, American Society of Agricultural and Biological Engineers, Orlando, FL., July 20.
- Zheng, Z., Oleson, K. W., Riemer, N., & Zhao, L. (2019). Projections of Global Urban Heat Waves Empowered by Machine Learning. Poster Presentation in Poster Presentation in 2019 AGU Fall Meeting, American Geophysical Union, San Francisco, CA., December 10. (View)
- Zheng, Z., Anantharaj, V. G., Gasparik, J., Curtis, J. H., Yao, Y., Hughes, M. P., Schmidt, D., West, M., & Riemer, N. (2019). Machine Learning to Predict Multi-Aerosol Mixing State Metrics. Poster Presentation in AMS 99th Annual Meeting - 18th Conference on Artificial and Computational Intelligence and its Applications to the Environmental Sciences (18AI), American Meteorological Society, Phoenix, AZ., January 7. (View)
- Zheng, Z., Dash, S., Schmidt, D., Yin, J., Riemer, N., West, M., & Anantharaj, V. G. (2018). A Machine Learning Approach to Estimate Multi-Aerosol Mixing State Metrics at a Global Scale in Earth System Models. Poster Presentation in 2018 AGU Fall Meeting, American Geophysical Union, Washington, D.C., December 10. (View)
- Zheng, Z., Fu, K., Balasubramanian, S., Koloutsou-Vakakis, S., McFarland, D. M., & Rood, M. J. (2017). Evaluation of WRF Parameterizations for Air Quality Applications over the Midwest USA. Poster Presentation in 2017 AGU Fall Meeting, American Geophysical Union, New Orleans, LA., December 14. (View)
4144 Newmark Civil Engineering Laboratory
205 North Mathews Ave.
Urbana, IL 61801-2352
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Last updated on September 17, 2020 by Zhonghua Zheng
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