4144 Newmark Civil Engineering Laboratory
205 North Mathews Ave.
Urbana, IL 61801-2352
SHORT BIO | (Academic Curriculum Vitae) | (One-Page Résumé)
I am currently a Ph.D. Candidate at the University of Illinois studying Environmental Engineering, supervised by Prof. Nicole Riemer. I closely work with Prof. Lei Zhao and Prof. Matthew West. 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.
- [2020.06] Our project towards global urban heat waves projections via machine learning has been released on EarthArXiv.
- [2020.05] Our project towards integration of detailed aerosol process modeling and a large-scale earth system model via machine learning has been released on EarthArXiv.
- [2020.05] I have been awarded by Microsoft AI for Earth for my research!
- [2020.04] I have been awarded by AWS on Earth and Amazon Sustainability Data Initiative for my research!
- [2020.03] I will continue my internship at Bayer AG // The Climate Corporation this summer.
- [2020.01] I gave a talk about Future Climate-Driven Risks to Urban Area during Night of Ideas Chicago 2020 at The Field Museum.
- [2020.01] I am the co-chair (three sessions) of 19th Conference on Artificial Intelligence for Environmental Science, 100th American Meteorological Society Annual Meeting.
- [2019.12] I am invited to attend and give a talk about the intergration of machine learning and particle-resolved aerosol simulations in the International Aerosol Modeling Algorithms Conference (IAMA).
- 09/2019 – Present: 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, 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, Zhejiang University, 2015 (Top 2 "A+" Agricultural Engineering Program in China)
- 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 (pdf)
- 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 July 6, 2020 by Zhonghua Zheng
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