Personal Update:
I am currently involved in the Mens, Manus, and Machina (M3S) project on Artificial Intelligence (AI) led by Prof. Jinhua Zhao at MIT. M3S applies AI and machine learning practically, addressing technology design, human skill development, and societal adaptation to AI, automation, and robotics, with the goal of creating inclusive, resilient solutions with global impact.
About Me
I am Xinyu Chen (陈新宇), currently working on developing some data-driven machine learning methods (e.g., matrix/tensor methods) and autoregressive time series methods for modeling various spatiotemporal data. These data are by nature multidimensional collected from real-world systems, including human mobility, traffic flow, fluid flow, climate/weather data, and energy consumption data. The specific scientific problems are 1) estimating and forecasting missing values of spatiotemporal data in real-world scenarios, 2) discovering dynamic patterns from spatiotemporal data (e.g., human mobility and climate data), and 3) generating high-resolution output from the low-resolution input data according to the spatiotemporal domain knowledge (e.g., speed field reconstruction and high-resolution climate variables generation). My Ph.D. thesis is entitled as "Matrix and Tensor Models for Spatiotemporal Traffic Data Imputation and Forecasting".
I like mathematics and computer science related stuff. My research interests include (but are not limited to) machine learning, spatiotemporal data modeling, intelligent transportation systems, urban science, and AI for science. My research philosophy comes from an ancient Chinese philosopher and writer Laozi, who stated "大道至简" (make it as simple and clear as possible). I am a strong advocate of open-source and reproducible research. To contribute more ideas to the research community, I am trying to make the datasets and Python codes of our research publicly available on GitHub. I am now leading some innovative open-source projects on GitHub (with 500+ followers), and they have accumulated more than 4k stars. Two most popular GitHub repositories are transdim (providing machine learning algorithms for transportation data imputation and prediction, 1.1k+ stars) and aswesome-latex-drawing (providing academic drawing examples in LaTeX, 1.2k+ stars).
Fortunately, I have received several awards, including IVADO PhD Excellence Scholarship ($100k by Institute for Data Valorisation (IVADO)) and CIRRELT PhD Excellence Scholarship ($5k 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.
Selected News
(For the full list of news please check the News tab.)
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December 2023: I successfully passed my PhD research defense. It would be my great pleasure to have Prof. Francesco Ciari, Prof. Nicolas Saunier, Prof. Lijun Sun, Prof. James Goulet, and Prof. Guillaume Rabusseau as the jury members. If you are interested in my PhD research, welcome to take a look at the slides. Special thanks to my supervisor Prof. Nicolas Saunier for the great suggestion when I was organizing all materials.
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July 2023: Our paper "Discovering dynamic patterns from spatiotemporal data with time-varying low-rank autoregression" (authors: Xinyu Chen, Chengyuan Zhang, Xiaoxu Chen, Nicolas Saunier, Lijun Sun) was accepted to IEEE Transactions on Knowledge and Data Engineering.
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December 2021: I am delighted to be awarded the CIRRELT PhD Excellence Scholarship. For more details on Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT) and its mission, please check out the website.
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July 2021: Our paper "Low-rank autoregressive tensor completion for spatiotemporal traffic data imputation" (authors: Xinyu Chen, Mengying Lei, Nicolas Saunier, Lijun Sun) was accepted to IEEE Transactions on Intelligent Transportation Systems.
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May 2021: Our paper "Scalable low-rank tensor learning for spatiotemporal traffic data imputation" (authors: Xinyu Chen, Yixian Chen, Nicolas Saunier, Lijun Sun) was accepted to Transportation Research Part C: Emerging Technologies.
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March 2021: Our paper "Bayesian temporal factorization for multidimensional time series prediction" (authors: Xinyu Chen, Lijun Sun) was accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence.
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April 2020: I am delighted to be awarded the IVADO PhD Excellence Scholarship. The awarded research topic is "City-Scale Traffic Data Imputation and Forecasting with Tensor Learning". For more details on Institute for Data Valorisation (IVADO) and its mission, please check out the website.
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