University of Denver
• Ph.D. Program - Geography
University of Pennsylvania
• Master of Environmental Studies
University of California, Berkeley
• BS in Environmental Economics and Policy
Microsoft Professional Program Certificate in Data Science (2017)
Chartered Financial Analyst Level II Candidate (2017)
• Passed Level I of the CFA Program in 2016
Professional Energy Manager (2014-2016)
• Certified by Schneider Electric and Institute of Energy Professionals
40-Hour Hazardous Waste Operations and Emergency Response Training (2014-2016)
• Certified by Compliance Solutions
Wang, X., Rafa, M., Moyer, J. D., Li, J., Scheer, J., & Sutton, P. (2019). Estimation and Mapping of Sub-National GDP in Uganda Using NPP-VIIRS Imagery. Remote Sensing, 11(2), 163.
Li, J., Wang, X., Zhang, T., & Xu, Y. (2018). Efficient Parallel K Best Connected Trajectory (K-BCT) Query with GPGPU: A Combinatorial Min-Distance and Progressive Bounding Box Approach. ISPRS International Journal of Geo-Information, 7(7), 239.
My name is Tony and I am currently a Ph.D. student at the University of Denver. Before studying at DU, I graduated with a Bachelor of Science degree in Environmental Economics and Policy at the University of California, Berkeley in 2014, and a Master of Environmental Studies degree at the University of Pennsylvania. My concentration is GIS and I am specialized in data mining, data visualization, cyberinfrastructure, high-power computing, artificial intelligence, cloud computing, and drone mapping.
My previous responsibilities include developing interactive desktop-based GIS data visualization platform (supported by OGC and USGS), developing machine learning/deep learning algorithms and modules for land use classification (using Java and Python), developing parallel strategies to optimize database engines for managing massive human mobility data and efficient data mining, constructing cyberinfrastructure platform to optimize the application and processing of machine learning methods, and conducting field research to collect environmental data in the field.
As a PhD student, I have participated in various research projects to apply my knowledge and skills in the real world. For example, I have worked with the professionals from the Pardee Center and the USAID to generate subnational GDP estimation data for Uganda. Besides that, I am currently supported by Microsoft to develop new tools and platforms based on cloud for solving current environmental challenges.
These relevant research experiences greatly motivated me and made me prepared for GIS data analysis and research. For instance, I have taken relevant advanced geospatial courses, including geographical information analysis and database management courses, at the University of Denver. Besides that, I have also completed the Microsoft’s Data Science program and obtained the data science certificate. I have also actively participated in many national conferences to share my research findings and products with other geography professionals. In the 2019 AAG conference, I was awarded with the Cyberinfrastructure Specialty Group Robert Raskin Student Competition Travel Award for my paper presentation about optimizing machine learning methods for trajectory data pattern extraction and traffic predictions.