Zhonghua Zheng Follow @zzuiuc Ph.D. Candidate Department of Civil and Environmental Engineering University of Illinois at Urbana-Champaign (UIUC)

URL: http://go.illinois.edu/zhonghua

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.
I was 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 Workflows Group; and a Data Scientist Intern during Spring 2018 at Monsanto Innovation Center where I mainly worked for The Climate Corporation.

CURRENT APPOINTMENTS

• 09/2019 - Present: Data Scientist Intern at Bayer AG (Crop Science Division)
• Affiliation (The Climate Corporation): Science - Data Insights & Discovery
• 08/2019 - Present: Graduate Teaching Assistant at University of Illinois
• Affiliation Department of Civil and Environmental Engineering (CEE)

PROFESSIONAL EXPERIENCE

• 09/2018 - 07/2019: Data Scientist Intern at Bayer AG (Crop Science Division)
• Affiliation (The Climate Corporation): Science - Data Insights & Discovery (01/2019 - 07/2019)
• Affiliation (The Climate Corporation): Science - Measurements Team (09/2018 - 12/2018)
• 08/2018 - 05/2019: Graduate Assistant at University of Illinois
• Affiliation: Department of Computer Science (CS)
• 05/2018 - 08/2018: Researcher at Oak Ridge National Labratory (ORNL)
• Affiliation: National Center for Computational Sciences - Advanced Data and Workflows Group
• Media: ORNL
• 01/2018 - 05/2018: Data Scientist-UIUC Innovation Center- at Monsanto Company
• Affiliation (The Climate Corporation): Science - Measurements Team
• Affiliation (Monsanto Company): GLB Breeding - Analytics & Pipeline Design
• Got summer intern (05/2018 - 08/2018) return offer

RESEARCH THEMES

Agriculture, Atmospheric Science, Computational Science and Engineering, Data Science, Environment

RESEARCH INTERESTS

My work focuses on computer simulation, modeling, and spatiotemporal analysis of 1) aerosol properties, 2) urban environment, and 3) complex agriculture-environment nexus system. I am passionate about learning and solving practical problems using Data Science (DS), Artificial Intelligence (AI), and High-Performance Computing (HPC).

EDUCATION

• Ph.D., Environmental Engineering, University of Illinois at Urbana-Champaign, 2021 (Expected)
• Concentration: Computational Science and Engineering
• Advisor: Prof. Nicole Riemer
• Co-Director of Research: Prof. Lei Zhao
• M.S., Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, 2016
• Advisor: Prof. Xinlei Wang
• Thesis Committee Members: Prof. Richard S Gates and Prof. Liangcheng Yang
• M.S. Thesis: Impedance-based moisture content sensor assessment for gas-phase biofilters
• B.Eng., Biosystems Engineering, Zhejiang University, 2015 (Top 2 "A+" Agricultural Engineering Program in China)
• Advisor: Prof. Zhangying Ye
• 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)

SELECTED AWARDS AND LEADERSHIP

• 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

• 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)
• Neural Networks and Deep Learning, issued by deeplearning.ai on Coursera, 2018 (Verifiable Link)
• Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, issued by deeplearning.ai on Coursera, 2018 (Verifiable Link)
• Structuring Machine Learning Projects, issued by deeplearning.ai on Coursera, 2018 (Verifiable Link)
• Convolutional Neural Networks, issued by deeplearning.ai on Coursera, 2018 (Verifiable Link)
• Sequence Models, issued by deeplearning.ai on Coursera, 2018 (Verifiable Link)
• Data Science (DATAQUEST)
• Path: Data Scientist in Python | Data Analyst in Python | Data Analyst in R
• Courses: Python | R | Natural Language Processing | SQL | Spark and Map-Reduce | Bash Command Line | Git
• Subjects: Data Structure and Algorithms | Data Cleaning | Data Visualization | Data Analysis | Data Science Topics | Data Storage for Analytics | Big Data Tools | APIs and Web Scraping | The Command Line
• Fundamental Engineer (FE) in Environmental Engineering, issued by NCEES, 2017 (Verifiable Link)
• Community Earth System Model (CESM) Tutorial, 2019 (pdf)

SELECTED GRADUATE COURSEWORK

• Machine Learning and Data Analytics
• 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 and Air Quality
• ATMS 420, Atmospheric Chemistry (A+)
• CEE 545, Aerosol Sampling and Analysis (A+)

SELECTED RESEARCH PRODUCTS

• Peer-reviewed Journals
1. 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)
2. 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)
• Thesis
1. 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)
• Conference Proceedings
1. 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)
• Oral Presentations
1. (Invited Speaker) 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.,
2. 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.
• Poster Presentations
1. Zheng, Z., 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)
2. 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)
3. 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)
4. 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)

CONTACT INFORMATION

Email: zzheng25@illinois.edu
4144 Newmark Civil Engineering Laboratory
205 North Mathews Ave.
Urbana, IL 61801-2352

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