Michael Chen
Associate Professor
Department of Mathematics and Statistics
Faculty of Science
York University
4700 Keele Street, TEL Building Room 2034
Toronto, Canada
chensy@mathstat.yorku.ca
Page Index
- Education
- Research and Teaching Interests
- Projects
- Selected Publications
- Download Software: Dromedary Studio Student Version
- Courses
- Interesting Work from Students
Education
- BSC, Econometrics, Jilin University
- MS, Operations Research, University of British Columbia
- PhD, Industrial Engineering and Management Science, Northwestern University
- PostDoc, Mathematics, IBM T.J. Watson Research Center
Research and Teaching Interests
- Deep Learning
- Operations Research
- Optimization
Professor Chen teaches graduate courses on stochastic programming and nonlinear optimization, as well as undergraduate courses on linear optimization, combinatorial optimization, operations research models, linear algebra and advanced calculus.
Seminars
- 9:30am - 11:00am, July 10th 2019, N Ross 627, Prof. Michael Chen, "A Collaborative Filtering based Model for Recommending Graduate Schools"
Projects
- PI, IRAP Project "Dynamic Routing Algorithms in Building Management"
- PI, Co-PI Professor Hongmei Zhu, Mitacs Project "Optimization of Savings and Retirement for Canadians"
- PI, Co-PI professor Hongmei Zhu, Mitacs Project "Learning Jungle AI Recommender System for Enhanced Education"
- PI on NSERC Discovery Grant "Stochastic Optimization of Renewal Energy"
- PI on NSERC Engage Grant "Deep Learning Method for Drinking Water Pollutant Detection"
- PI on OCE VIP I Grant "Deep Learning Method for University Timetabling Problem"
- PI on IRAP AI Grant "Deep Learning Method for Workplace Safety"
- PI on MITACS Grant "Recommendation System for Online Learning"
- PI on Environment Canada Project "Temporal and Spacial Correlation of PM2.5"
- Member of NSERC Sanofi Industrial Research Chair Jianghong Wu Grant "Math for Infectious Diseases"
- Analyst in Teekay Shipping "Operational Risk Mitigation"
Selected Publications
Yousef Akhavan, Shengyua Chen, Dong Liang. Second Order in Time and Space Corrected Explicit-Implicit Domain Decomposition Scheme for Convection-Diffusion Equations, Journal of Computational and Applied Mathematics, accepted, 2019.Masoud Ataei, Shengyuan Chen, Reza Peyghami. Time homogeneous Top-K Ranking Using Tensor Decomposition, Optimization Method and Software, accepted, 2018.
Sajad Fathi-Hafshejani, Hossein Mansouri, M. Reza Peyghami, Shengyuan Chen. Primal-dual interior-point method for linear optimization based on a kernel function with trigonometric growth term, Optimization, 67:10, 1605-1630, 2018.
M. Reza Peyghami, Kevin Yang, Shengyuan Chen, Zijiang Yang, Masoud Ataei. Accelerated Gradient and Block-Wise Gradient Methods for Big Data Factorization. Canadian AI 2018, LNAI 10832, 2018.
S. Fathi-Hafshejani, Alireza Fakharzadeh Jahromi, Mohammad Reza Peyghami, Shengyuan Chen: Complexity of Interior Point Methods for a Class of Linear Complementarity Problems Using a Kernel Function with Trigonometric Growth Term. J. Optimization Theory and Applications, 178(3): 935-949, 2018.
M. Reza Peyghami , S. Fathi-Hafshejani , Shengyuan Chen. A primal-dual interior-point method for semidefinite optimization based on a class of trigonometric barrier functions. OR Letters, 44(3):319-323, 2016.
M. Zhu, S. Chen, M. Christal. Modeling the impacts of uncertain carbon tax policy on maritime fleet mix strategy and carbon mitigation. Transport, 33(3), 707-717, 2016.
Z. Danling, H. Xi, Shengyuan Chen, and W. Jianhong. The Diffusion of Online Content Based On SEIR Model. Journal of Biomathematics, issue 4, 2016.
Shengyuan Chen, S. Mehrotra, D. Papp. Scenario Generation for Stochastic Optimization Problems via the Sparse Grid Method. Computational Optimization and Applications, 62(3):669-692, 2015.
Fei Yang and Shengyuan Chen. Deep Cutting Plane Inequalities for Stochastic Non-Preemptive Single Machine Scheduling Problem. American Journal of Operations Research, 5:69-76. doi: 10.4236/ajor.2015.52006, 2015.
Y. Akhavan, Shengyuan Chen and D. Liang. Global Optimization of Total Power Generated from Wind Farm, Proceeding of 2014 International Conference on Power System Technology, 2945-2950, 2014.
Shengyuan Chen, X. Qiu, L. Zhang, F. Yang, P. Blanchard. Method Development Estimating Ambient Oxidized Mercury Concentration from Monitored Mercury Wet Deposition. Atmospheric Chemistry and Physics, 13:11287-11293, 2013.
Shengyuan Chen and X. Wang. A Derivative-free Global Optimization Algorithm by Sparse Grid Integration. American Journal of Computational Mathematics, 3(1):16-26, 2013. DOI: 10.4236/ajcm.2013.31003, 2013.
Shengyuan Chen and X. Wang. Approximate Risk Analysis using Numerical Integration On Sparse Grids. Journal of Mathematical and Computational Science,3(4):929-944, 2013.
Shengyuan Chen and S. Mehrotra. Self-concordance and Decomposition Based Interior Point Methods for Two-stage Stochastic Convex Optimization Problem. SIAM Journal of Optimization, 4(21):1667-1687, 2011.
Shengyuan Chen and M. Zhao. Optimal Thermal Generator Portfolio in a Day-ahead Market under Uncertain Carbon Tax Policy. American Journal of Operations Research, 1(4):268-276, 2011.
Download software: Dromedary Studio Student Version
Current Course Taught
- MATH 3171 Linear Optimization
- MATH 3172 Combinatorial Optimization
- MATH 4171 Nonlinear Optimization
- MATH 4172 Operations Research Models
- MATH 6902 Stochastic Programming
- MATH 6904 Modern Optimization
Short Courses
Prof. Chen teaches short courses on the following topics:- Optimization models in finance, education, and scheduling
- Optimization techniques for deep learning
- Introduction to optimization modeling languages and solvers
- Introduction to artificial intelligence
- Introduction to deep learning
- Introduction to data science
- Introduction to Python
Interesting Work from Students
2019, Zhao Lian, Ruimeng Yang, Jingyi Liu, Support Vector Machine (SVM), MATH 6902 Modern Optimization2019, Kosal Chhin, Convexity and Unniqueness, MATH 6902 Modern Optimization
last update 2/19/2019