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Christopher Thomas RyanView profile

Associate Professor

• Optimization
• Game Theory
• Theoretical Economics
• +7 more

Christopher Thomas Ryan is an Associate Professor in the Operations and Logistics Division at the UBC Sauder School of Business. He holds a PhD and BA from UBC in Management Science and Mathematics, respectively. His research spans optimization theory, game theory, theoretical economics, video game design, and pedagogy for business education. He has held positions at the University of Chicago Booth School of Business and is affiliated with the Colibri Learning Foundation. Education: BA (Mathematics) and PhD (Management Science) from UBC; BA (Sociology and Economics) from University of Guelph. He has authored numerous textbooks and case studies, including works on research careers, operations management, and teaching methodologies. His work integrates human-centric approaches to operations and education systems. Research Interests include small business operations, education operations, theoretical economics, and the design of video games. He has published in top journals like Management Science, Econometrica, and Mathematical Programming. His grants include SSHRC and NSERC awards. Ryan advises students across multiple institutions and has mentored prominent faculty in marketing, operations, and MIS fields. Teaching focuses on core operations management for MBA programs and pedagogical innovation. He has developed cases on AI in education, early childhood development, and small business sustainability. Ryan’s work bridges academic research with practical applications in business and education sectors.

• Computational Statistics
• Markov Chain Monte Carlo Methods
• Bootstrap and Resampling Techniques
• +4 more

Dr. Angelo J. Canty is an Associate Professor in the Department of Mathematics and Statistics at McMaster University, Canada. His research focuses on computational statistics, genetic data analysis, and resampling methods. B.Sc. (1989) from University College Cork, Ireland M.Sc. (1991) and Ph.D. (1995) from the University of Toronto Postdoctoral work at University of Oxford and EPFL, Lausanne Assistant Professor at Concordia University (1998–2001) before joining McMaster His research spans computational statistics, with key contributions to: Markov Chain Monte Carlo convergence diagnostics Bootstrap and resampling techniques Saddlepoint approximations in statistical inference Efficient algorithm implementation for survey data analysis Genetic data analysis (microarrays, GWAS) His publications highlight a focus on automating convergence assessment (1994–1999), resampling for labor statistics (1999), and saddlepoint approximations in resampling (1996–1999). He developed an influential S-Plus library for resampling methods. Teaching includes: Statistics 4C03/6C03: Generalized Linear Models (Undergraduate/Graduate) Statistics 752: Linear Models and Experimental Design (Graduate)

• Operational Research
• Mathematical Optimization
• Simplex Algorithms
• +2 more

Richard J. Caron is a Professor at the University of Windsor's College of Engineering, specializing in operational research and mathematical optimization. He has supervised students including Nooshin Nekoiemehr, Qiqi Zhang, and Anqi Chen. His team won the first practice prize at the national conference of the Canadian Operational Research Society. His research focuses on mathematical programming, constraint analysis, and optimization algorithms. Recent publications examine simplex algorithms, matrix inequalities, and probabilistic methods for extreme point identification. Dr. Caron's awards include the First Practice Prize from the Canadian Operational Research Society for developing cargo optimization tools for Air Canada. His work demonstrates consistent contributions to optimization theory and computational mathematics throughout his career.

Yanglei SongView profile

Assistant Professor

• Sequential Decision-Making
• Mathematical Statistics
• High-Dimensional Statistics
• +7 more

Yanglei Song is an Assistant Professor in the Department of Mathematics and Statistics at Queen's University, affiliated with the Faculty of Arts and Science. His research focuses on sequential decision-making problems, including hypothesis testing, change detection, and multi-armed bandits, alongside mathematical statistics such as U-statistics, high-dimensional statistics, and cut-point analysis. Education: Ph.D. in Statistics, University of Illinois at Urbana-Champaign (2019) M.Sc. in Mathematics, University of Illinois at Urbana-Champaign (2016) B.Eng. in Electronic Engineering, Tsinghua University (2012) Research Interests: Sequential decision-making frameworks with applications in hypothesis testing and stochastic optimization. Statistical methodologies for high-dimensional data and nonparametric modeling. Development of robust algorithms for reinforcement learning and adaptive systems. Mathematical foundations of U-statistics and their computational guarantees. Publications Trends: Recent work emphasizes theoretical advancements in bandit algorithms, robust model approximation, and statistical inference under covariate-adaptive randomization. Contributions span machine learning, computational statistics, and applied mathematics, with a focus on practical implementations and rigorous theoretical analysis. Students: J. Liu Y. Zhou Z. Wang Z. Zhao N. Li M. Zhou Labs/Teams: Maintains an active research group focused on statistical learning and sequential decision-making, with open-source projects such as Stratified incomplete local simplex tests for nonparametric regression analysis.

Pierre HansenView profile

Professor

• Operational Research
• Optimization
• Graph Theory
• +3 more

Pierre Hansen is a Professor at HEC Montréal since 1990, renowned for his contributions to operational research and optimization. He held the Data Mining Chair and directed the GERAD research center from 1996 to 2001. His multidisciplinary work spans over 15 disciplines, focusing on algorithm design, graph theory, and cluster analysis. He is a Fellow of the Royal Society of Canada (1999) and recipient of the Grand Prize for Excellence in Research (2013). Research interests include variable neighborhood search algorithms, graph spectra, and mathematical programming applications. His articles often explore optimization methods such as column generation, integral simplex decomposition, and geometric optimization problems like circle packing. His work impacts fields like data mining, network analysis, and computational geometry, with contributions to AutoGraphiX —a system for generating conjectures in graph theory. Hansen’s research integrates theoretical advancements with practical applications in operations research and decision sciences.

Warren HareView profile

Professor

• Mathematical Optimization
• Nonconvex Analysis
• Derivative-Free Optimization
• +6 more

Warren Hare is a Professor and Associate Head of the Graduate Program in the Department of Computer Science, Mathematics, Physics and Statistics at the University of British Columbia Okanagan. He holds a PhD in Mathematical Optimization from Simon Fraser University. His research focuses on structured blackbox optimization, emphasizing algorithm development for applications such as road design and computer simulations. He serves as an Associate Editor for Set Valued and Variational Analysis and the Pacific Journal of Optimization , and co-authored the book Derivative-Free and Blackbox Optimization . Research Interests: Mathematical optimization, nonconvex analysis, derivative-free optimization, bundle methods, and applications in road design. He explores structured blackbox optimization problems where mathematical structures (e.g., max functions) can be leveraged to design efficient algorithms. Advising & Grants: Supervises graduate students in optimization and has secured funding for projects involving road alignment optimization and medical imaging applications. Collaborates on interdisciplinary initiatives combining optimization with civil engineering and medical physics. Labs/Teams: Engaged with UBC Okanagan’s optimization research group and collaborates with industry partners on infrastructure and healthcare optimization challenges.

Jacques DesrosiersView profile

Professor

• Operations Research
• Transportation
• Optimization
• +3 more

Jacques Desrosiers is a Full Professor at HEC Montréal in the Department of Management Science since 1989. He has been with the institution since 1978 and is a founding member of the Group for Research in Decision Analysis (GERAD). His research focuses on optimization, transportation systems, and algorithmic methods for solving complex linear and combinatorial problems. He has received prestigious recognitions, including the Grand Prize for Excellence in Research (2015) and Fellowship in the Royal Society of Canada (2001). His work spans contributions to column generation techniques, degenerate linear programming, and vehicle routing problems. Notable achievements include advancing the minimum mean cycle-canceling algorithm, vector space decomposition for large-scale problems, and developing efficient heuristics for logistics challenges. His research bridges theoretical advancements and practical applications, influencing transportation and operations management globally. Desrosiers has authored over 150 peer-reviewed articles, with recent focus on algorithmic optimization, primal degeneracy handling, and decomposition methods. His contributions to software tools like COIN-OR’s CLP further highlight his commitment to advancing computational methods in operations research. Awards: Royal Society of Canada Fellowship (2001), HEC Montréal Grand Prize (2015) Key Research Themes: Column Generation, Network Flow Algorithms, Linear Programming, Vehicle Routing, Degeneracy Resolution Labs/Teams: Co-founder and active member of GERAD, collaborating on optimization projects

• Operations Research
• Mathematical Optimization
• Column Generation Algorithms
• +3 more

Hatem Ben Amor is an Associate Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. With over two decades of academic experience since completing his Master's degree in 1997, he has established himself as a researcher in operations research and mathematical optimization. His research primarily focuses on: Operations Research and Mathematical Optimization Column Generation Algorithms and Stabilization Techniques Shortest Path Problems with Resource Constraints Vehicle Routing and Scheduling Linear and Integer Programming Professor Ben Amor's publication record demonstrates consistent scholarly output in top-tier operations research journals including Operations Research, Transportation Science, and Computers & Operations Research. His work shows a progression from foundational research on column generation stabilization to more applied work in transportation optimization, reflecting both theoretical depth and practical relevance in the field. He has supervised graduate students, including at least one doctoral candidate whose research extended his work on shortest path algorithms. His research has practical implications for transportation logistics, manufacturing optimization, and resource allocation problems. Contact information: Email: hatem.ben-amor@polymtl.ca Phone: (514) 340-4711 ext. 6042 Office: AA-4431