News

2024

  • June 23: Our paper "Laplacian convolutional representation for traffic time series imputation" (authors: Xinyu Chen, Zhanhong Cheng, HanQin Cai, Nicolas Saunier, Lijun Sun) was accepted to IEEE Transactions on Knowledge and Data Engineering. This paper received a lot of insightful feedback and suggestions from reviewers. Thank you for the great contributions to this work in the reviewing process.

  • May 16: I am delighted to give a talk at Northeastern University (invited by Prof. Ryan Qi Wang with the Department of Civil and Environmental Engineering) in Boston, USA. The topic is about "Modeling temporal correlations and dynamics in spatiotemporal data systems", highlighting the importance of temporal modeling (e.g., local time series trends and time-varying system behaviors) in real-world data.

  • March 31: We provide slides for understanding the most basic definition, properties, and derivatives of matrix traces in matrix computations and machine learning.

  • March 20: I gave a comment (i.e., Rethink equation (15) for the iterative shrinkage thresholding algorithm) for Attention: Self-expression is all you need on OpenReview. This work has tried to connect transformers with the prior art, a very good attempt!

  • February 13: I changed my homepage photo as this one, which was took at Casa Loma, Toronto, Canada.

  • February 12: Our papers have received 1,000 citations on Google Scholar. Many thanks to the research community!

  • January 11: I gave a presentation with my supervisor Prof. Nicolas Saunier about "Open-source project: Machine learning for transportation data imputation and prediction" (check out the slides) at the Reproducible Research Workshop of the 103rd Transportation Research Board (TRB) Annual Meeting in Washington D.C., USA.

2023

  • December 28: I gave a virtual talk about "Matrix and tensor methods for spatiotemporal traffic data imputation and forecasting" (check out the slides) at Southern University of Science and Technology (SUSTech) Forum with the Department of Statistics and Data Science.

  • December 13: We write a blog post for understanding and reproducing our paper "Discovering dynamic patterns from spatiotemporal data with time-varying low-rank autoregression". The content includes an intuitive explanation of time-varying autoregression, spatiotemporal data processing, and the algorithm implementation with NumPy/CuPy. It would be a good material for beginners to follow our research. Any feedback would be highly appreciated.

  • December 11: I successfully passed my PhD research defense today. 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.

  • October 5: I revisit the core concept of linear algebra by watching Essence of Linear Algebra on YouTube. I really like the visuals-first approach for explaining linear algebra in this series.

  • September 11: Four of our papers have been cited above 100 times on Google Scholar, including all three (first-author) papers published in Transportation Research Part C: Emerging Technologies during my Master's study.

  • July 25: Our papers have received 800 citations on Google Scholar. Many thanks to the research community!

  • July 17: I will give a talk about "Laplacian convolutional representation for traffic time series imputation" (check out the slides) at the WCTR conference on July 19th in Montreal, Canada.

  • July 4: Our open-source project transdim got 1,000+ stars and 270+ forks on GitHub. This project focuses on providing machine learning solutions for transportation data imputation and prediction. It is really a long journey to reach here since the first commit on September 23, 2018.

  • July 2: 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. Chengyuan Zhang was contributed equally to this work, thank you!

  • May 22: I am delighted to give a talk at Southern University of Science and Technology (南方科技大学, invited by Prof. Lili Yang with Department of Statistics and Data Science) in Shenzhen with the topic "Low-rank matrix and tensor methods for spatiotemporal traffic data modeling" (check out the slides).

  • May 16: Our papers have received 700 citations on Google Scholar. Many thanks to the research community!

  • April 21: I am delighted to give a talk at University of Electronic Science and Technology of China (电子科技大学, invited by Prof. Xi-Le Zhao with School of Mathematical Science) in Chengdu with the topic "Low-rank matrix and tensor methods for spatiotemporal data modeling" (check out the slides).

  • April 20: I am delighted to give a talk at Sichuan University (四川大学, invited by Prof. Yuankai Wu) in Chengdu with the topic "Low-rank matrix and tensor methods for spatiotemporal data modeling" (check out the slides).

  • March 15: I am delighted to give a (virtual) talk at Soochow University with the topic "Low-rank matrix and tensor factorization for speed field reconstruction" (check out the slides or the latest version).

  • March 10: Our paper "Bayesian temporal factorization for multidimensional time series prediction" (2022) published in IEEE Transactions on Pattern Analysis and Machine Intelligence was selected as a hot paper (in the top 0.1% of papers in the academic field of Engineering (proof)) from Essential Science Indicators (ESI) Data.

  • March 9: I gave a presentation about "Low-rank matrix and tensor factorization for speed field reconstruction" at the Research Group of Transport, Polytechnique Montreal. If you are interested, welcome to take a look at the slides and the blog post!

  • March 8: Our open-source project awesome-latex-drawing got 1,000+ stars and 130+ forks on GitHub. This project is a collection of 30+ academic drawing examples for using LaTeX, including Bayesian networks, function plotting, graphical models, tensor structure, and technical frameworks.

  • February 22: Our GitHub repositories accumulated more than 3,000 stars.

  • January 26: Our papers have received 600 citations on Google Scholar. Many thanks to the research community!

  • January 22: Our open-source project transdim got 900+ stars and 260+ forks on GitHub. This project focuses on providing machine learning solutions for transportation data imputation and prediction.

  • January 21: We posted an intuitive understanding of tensors in machine learning on Medium. The content includes the basic components (entry/fiber/slice) of third-order tensors and some tensor examples in real-world applications. If you have any suggestions or feedback, feel free to contact us.

  • January 13: Our paper "Bayesian temporal factorization for multidimensional time series prediction" (2022) published in IEEE Transactions on Pattern Analysis and Machine Intelligence was selected as a highly cited paper (in the top 1% of papers in the academic field of Engineering (proof)) from Essential Science Indicators (ESI) Data.

  • January 11: I gave a poster presentation about "Nonstationary temporal matrix factorization for sparse traffic time series forecasting" at TRB 2023 in Washington, D.C., USA.

2022

2021

2020