Computational Methods in
Industrial Mathematics

Current economic development is based on continuous increase in efficiency of business processes and industrial organization. This increase is obtained through better collection of business process data, data analytics tools (including machine learning and data science methods), and advanced simulation and optimization techniques. Including available data within optimization of processes requires constructing complex mathematical models. In particular, many real world scenarios exhibit high combinatorial complexity, need to include several sophisticated constraints imposed by the business environment, and need to consider uncertainty. Including all key features characterizing industrial processes and their business environment leads to complex mathematical models.


The complexity of the problems leads to a need for large, sophisticated computational systems, consisting of hundreds or thousands of computational units. Computational technologies (such as distributed computing, GPU computing, massive parallel computing) allow for the management of that process. Our lab tries to narrow the gap between the  huge demand from the industrial side and the lack of tools on the academic side. Our goal is to

Ryerson University

focus on developing new mathematical methods and tools (new theorems, algorithms, and computer implementations of them, for non-standard industrial applications).

Lab Leader

Pawel Pralat

Associate Professor

Faculty of  Science

Department of Mathematics

Ryerson University

Lab Team

Ayse Bener

Ryerson University

Konstantinos Georgiou
Ryerson University

Bogumil Kaminski
SGH Warsaw School of Economics

Atefeh Mashatan
Ryerson University

Andrei Raigorodskii
Moscow Institute of Physics and Technology

Przemyslaw Szufel
SGH Warsaw School of Economics

Industry Partner

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Postdocs and Graduate Trainees

Marek Antosiewicz

Postdoctoral Fellow

Arash Dehghan
Master's Candidate, Ryerson University

Jacek Filipowski

PhD Candidate

Reaz Huq
Master's Candidate, Ryerson University

Łukasz Kraiński
PhD Candidate

Somnath Kundu
PhD Candidate, Ryerson University

Rajaram Natarajan
Master's Candidate, Ryerson University

Marcin Opalski

PhD Candidate

Bartosz Pankratz

PhD Candidate

Kiryl Varanovich

PhD Candidate

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