Xu (Sunny) Wang

My research program focuses on developing new statistical tools to analyze, model, and interpret complex systems such as human dynamics and high dimensional multimodal data arising from medical research. This research lies at the intersection of modern statistical learning and "traditional" statistical ideas. Currently I am focusing on two research directions:

• Develop efficient statistical models and algorithms for describing, analyzing and interpreting human behaviour data, such as email communication, emergency calls etc. The ultimate goal of the first research direction is to propose a flexible model, which does not require domain knowledge and is interpretable.
• Develop automated statistical learning tools for analyzing high dimensional multimodal data. To overcome the difficulties in analyzing high dimensional multimodal data from multiple sources, we propose to develop a hybrid approach that interactively combines methods from statistics, computational topology and deep learning.

• Merit Award in Teaching and Service, Wilfrid Laurier University (2023)
• SOSCIP-Mitacs Accelerate Grant (2022)
• Donald F. Morgenson Awards for Teaching Excellence in the Category of Innovation, Wilfrid Laurier University (2021)
• NSERC COVID-19 Alliance Award (2020 - 2021)
• Faculty of Science Teaching for Excellence Award, Wilfrid Laurier University (2020)
• Merit Award in Teaching and Research, Wilfrid Laurier University (2019)
• Mitacs Accelerate Grant (2019)
• NSERC Individual Discovery Grant (2019-2025)
• NSERC Engage Grant (2018)
• Merit Award in Teaching, Wilfrid Laurier University (2018)
• National Research Council-Industrial Research Assistance Program (2016)
• Outstanding Teaching Award, St. Francis Xavier University (2016)
• NSERC Individual Discovery Grant (2010-2017)
• NSERC early researcher award (2011-2017)

I have research assistantship opportunities for undergraduate and graduate students interested in developing statistical learning and data mining techniques.

I am willing to supervise graduate students in the areas of statistical learning, data mining and deep learning.

Proceedings

1. Corresponding Editor. Recent Advances in Mathematical and Statistical Methods. Co-editors: D. Marc Kilgour, Herb Kunze, Roman Makarov, Roderick Melnik, \textbf{Xu Wang}. December, 2020 (expected), Springer.
2. Advanced in Data Science. Co-editors: Yifei Lou, Xu Wang, Kathrin Welker. December, 2020 (expected), Springer.
3. Corresponding editor. Recent Advances in Mathematical and Statistical Methods for Scientific and Engineering Applications. Co-editors: D. Marc Kilgour, Herb Kunze, Roman Makarov, Roderick Melnik, Xu Wang. 2018, Springer.

1. Kolen-Thompson, A.M., Wadsworth, L.A., Wang, X., van Bommel, C.M.* and Terrio, C.A.* (2013). Measuring physical activity in children and youth: Learning from experience, in P.S. de Brito AndrAé & H. Varnum (Eds). Accelerometers: Principles, Structure and Applications, Nova Science Publishers. ebook pp 245-269.
2. Heo, Giseon, Leonard, Kathryn, Wang, Xu and Zhou, Yi* (2019). High-dimensional Multiple Scaled Data Analysis of Obstructive Sleep Apnea Study with Interdisciplinary Endeavor. Research in Data Science, Springer. Gasparovic, Ellen, Domeniconi, Carlotta (Eds.) Page 81-107. 

Refereed Journal and Proceeding Publications

1. Longlong Feng*, Xu Wang (2020). Automate Obstructive Sleep Apnea Diagnosis Using Convolutional Neural Networks. Accepted to the AMMCS 2019 Proceedings.
2. Emily T. Winn*, Marilyn Vazquez, Prachi Loliencar, Kaisa Taipale, Xu Wang, and Giseon Heo (2020). A Survey of Statistical Learning Techniques as Applied to Inexpensive Pediatric Obstructive Sleep Apnea Data. Accepted to the Women in Data Science 2019 Proceedings.
3. Bappee, Fateha *, Wang, Marcia , Chipman, Hugh , Wang, X. Sunny and Welch, William (2019). Mining Im- balanced Drug Discover Data with Adaptively Chosen k & Weighted K Nearest Neighbour. (Under revision) Canadian Journal of Statistics.
4. Li, Chenlong *, Song, Zhanjie, Wang, Xu (2019). Mining Periodic Cascading Bursts Pattern in Individual Email Communication. (Accepted) Journal of Applied Statistics.
5. Li, Chenlong , Song, Zhanjie , Wang, Xu (2019). Modelling and Estimation of Clustering Phenomena in Emergency Calls Using Spatial-temporal Self-exciting Point Processes. IEEE Access. Issue Date: December 2019. Volume: 7, Issue: 1. Pages 24865-24876. DOI, 10.1109/ACCESS.2019.2900340.
6. Wu, Longyang, Weng, Chengguo, Wang, Xu, Wang, Kesheng, and Liu, Xuefeng (2018). Test of Covariance and Correlation Matrices. arXiv1812.01172.
7. Bigelow, A. E., Power, M., MacLean, K., Gillis, D., Ward, M., Taylor, C., Berrigan, L., and Wang. X. (2018). Mother-infant skin-to-skin contact and mother-child interaction nine years later. Social Development, 27, 937-951. DOI: 10.1111/sode.12307.

Note: The names marked by * are students.

• ST494/ST694: Statistical Learning
• ST462/ST662: Advanced Regression Analysis
• ST362/ST562: Regression Analysis
• ST260: Introduction to Statistics
• ST231: Statistical Methods for Life and Health Sciences
• DATA200: Data Analytics
• DATA100: Introduction to Data Science

• SOSCIP COVID-19 Projects – A curated list.
• Reopening the economy responsibly: Recruit and measure the impact of volunteers during and after COVID-19 pandemic
• Laurier researchers, Lovell Corporation collaborate on app to help meet UN Sustainable Development Goals
• Shad program to launch at Wilfrid Laurier University in 2020
• Laurier Keen to Bring Academic Excellence to the Town of Milton