I am an Applied Scientist at Amazon, where I develop large-scale data analytics and machine learning solutions to enhance warehouse operations and system efficiency. I recently earned my Ph.D. in Civil and Environmental Engineering from the University of Wisconsin–Madison, where I also completed a Master’s in Computer Science. Before that, I received dual Bachelor’s degrees in Environmental Science and Economics from Peking University, China.
My research focuses on advancing remote sensing, image processing, and deep learning techniques to detect, monitor, and characterize natural hazards in the Great Lakes region. More broadly, I am interested in applying stochastic simulations, image analysis, and machine learning to address interdisciplinary problems in ecology, hydrology, environmental science, and the social sciences.Education:
- Ph.D Civil and Environmental Engineering, University of Wisconsin, Madison, 2025
- M.S. Computer Science, University of Wisconsin, Madison, 2021
- B.S. Environmental Science, Peking University, China, 2017
- B.A. Economics, Peking University, China, 2017
Skills:
- Programming Languages: Python, Java, Matlab, C++, JavaScript, R -
- Frameworks & Libraries: PyTorch, TensorFlow, OpenCV, Keras, Scikit-learn, MySQL, Node.js
- Tools & Systems: Git, Linux, Spark, Docker, AWS, Azure, Remote Sensing, Structure-from-Motion
- Others: Surveying, UAV pilot
Software and Python Packages:
- Multi-data Plotting: a Python package for user-friendly high-dimensional data plotting (link: https://github.com/wwang487/MultiDataPlotting)
- UAV-MMI: a Python-based script for processing UAV-based data to obtain stream habitat multi-metric assessments (link: https://github.com/wwang487/UAV-MMI).
- BehaviorRecognition: (Collaborate with Luping Wang from the Department of Wildlife Management, University of Wisconsin-Madison): a Python-based deep learning script for the detection of animal behaviors using camera traps (link: https://github.com/wwang487/BehaviorRecognition).
Contact:
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