Summary
Haoyi Xiong is a Data Mining researcher and PhD candidate at the University of Iowa with 11 years of experience applying Python-first engineering to spatial data mining and GIS problems. He designs and implements scalable algorithms for mapping massive GPS trajectories, spectral clustering of congestion patterns, Markov-based congestion prediction, and DTW-based cascade detection, with work that directly informs ETA, routing, and network planning. His background spans GIS-focused software development (ArcObjects, SWAT integration) to server-side AI prototyping (vehicle detection at Esri), showing fluency across research codebases and production tooling. Comfortable in multiple languages (Python, Java, C#, Fortran reading) he favors Python for rapid experimentation and reproducible research. Notably, he pairs rigorous academic training (PhD, MS in Geographic Information Science) with practical performance engineering—building benchmarking harnesses and indexing methods to make research models work at urban scale.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Engineering (B.E.), Geomatics Engineering, 3.2, Bachelor of Engineering (B.E.), Geomatics Engineering, 3.2 at Wuhan University
Master of Science - MS, Geography (Geographic Information Science), 4.0, Master of Science - MS, Geography (Geographic Information Science), 4.0 at University at Buffalo
Bachelor of Science (B.S.), Computer Science & Technology, 3.1, Bachelor of Science (B.S.), Computer Science & Technology, 3.1 at Huazhong University of Science and Technology
Doctor of Philosophy - PhD, Geography (Geographic Information Science), 3.91, Doctor of Philosophy - PhD, Geography (Geographic Information Science), 3.91 at University of Iowa