Personal Update:
I am now working on some open-source research projects, including transdim (Machine learning for transportation data imputation and prediction) and tracebase (Multivariate time series forecasting on high-dimensional and sparse Uber movement speed data). If you are interested, welcome to take a look and give me feedback!

About Me



I am Xinyu Chen (陈新宇), a Ph.D. candidate at Polytechnique Montreal affiliated with University of Montreal in Canada. I am currently working on developing some data-driven intelligent transportation solutions with machine learning. My Ph.D. research project is "Spatiotemporal Traffic Data Imputation and Forecasting with Tensor Learning". My research interests include (but are not limited to) machine learning, spatiotemporal data modeling, and intelligent transportation systems. My research papers have been cited more than 450 times on Google Scholar, and they have been published in some top-tier scientific journals, including (as the first author)

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI, 1 paper) (IF: 24.314)
Transportation Research Part C: Emerging Technologies (5 papers)
IEEE Transactions on Intelligent Transportation Systems (1 paper)

These papers include one ESI hot paper (🔥) and one ESI highly cited paper (🏆). My research philosophy comes from an ancient Chinese philosopher and writer Laozi (老子), who stated "大道至简". I am a strong advocate of open-source and reproducible research. I am now leading some innovative open-source projects on GitHub (with 370+ followers), and they have accumulated more than 2,600 stars.

Fortunately, I have also received several awards, including IVADO PhD Excellence Scholarship (by Institute for Data Valorisation (IVADO)) and CIRRELT PhD Excellence Scholarship (by Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT)). I would like to thank IVADO and CIRRELT for funding my Ph.D. research.

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