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.)


vistors & views since September 2021