The Centre for Computational Science and Engineering (CCSE) was founded in 2016 by a small group of students and professors from various faculties at the University of Toronto, all of whom are engaged in computational research. The students and professors come from a wide range of research backgrounds, ranging from fluid mechanics to operations, but all of them recognize that there exists many opportunities for collaboration across disciplines. The intention of the group is to pool both resources and a wide diversity of knowledge and experience for the benefit of present and future computational researchers at the University of Toronto.


With continuous advances in computing hardware and software, computational science and engineering continues to increase in importance within the physical sciences, both in research and in practice. The purpose of the CCSE is to increase collaboration in high-quality research at the University of Toronto in fields such as as computational fluid dynamics, computational electromagnetics, computational materials engineering, uncertainty quantification, optimization, machine learning, and many others. There is a great deal of research going on within the various faculties at the university that would benefit from increased coordination and visibility, which can help facilitate the advancement of novel research in computational fields within the university as well as attract collaboration and potential students/professors from elsewhere.


Outreach initiatives by the CCSE occur mainly in the form of various events. These events include speakers both from the University of Toronto and invited speakers from other universities. These speakers provide opportunities for researchers in a similar field to learn and collaborate, while researchers in other fields are exposed to new activities. CCSE aims to have at least one seminar every couple of months, with a hope to increase the frequency of seminars in the future as the centre grows.

Additionally, CCSE hopes to begin organizing more formal workshops in the near future. These workshops will be intended to provide a learning resource for both new and experienced researchers. Some potential topics include popular mathematical modelling techniques in Finite Element Methods (FEM), open source software for scientific computing and many others. Information on past and upcoming events can be found on the events page.

Faculty Members

A team of eleven faculty members, all of whom are conducting research in computational algorithms, form the core of CCSE. Each member of the faculty team provides one graduate student to the initiative. Although these eleven faculty members and the students they designate are the core of CCSE, its events are open to all members of the U of T research community. Currently the representatives come from four faculties; UTIAS, MIE, ECE, and MSE, however significant computational research also occurs in CIV, IBBME, CHE and many others. The following list is the eleven faculty members described above and their area of expertise:

  • David Zingg, UTIAS – His research is in the areas of computational fluid dynamics (CFD) and aerodynamic shape optimization, often applied to the investigation of unconventional aircraft configurations with improved fuel efficiency and reduced emissions. His algorithmic contributions include Newton-Krylov methods, homotopy continuation methods, iterative methods, high-order implicit time-marching methods, and high-order summation by parts operators.
  • Masa Yano, UTIAS – His research interests lie in numerical methods, scientific computation, and numerical analysis for partial differential equations (PDEs) with an emphasis on applications in fluid dynamics. Current research topics include a posteriori error estimation, mesh adaptation, and model reduction of parameterized PDEs. Much of his work is focused on the development of PDE solution strategies that provide numerical predictions at a user-specified accuracy using minimal computational effort in an automated manner.
  • Tim Chan, MIE - His research focuses on the development of computational optimization methods to solve problems in healthcare planning, delivery, and treatment. One major research area focuses on computational methods for improving and automating radiation therapy treatment design, using state-of-the-art robust and inverse optimization models solved via decomposition techniques like column and constraint generation. A second area focuses on locating public access defibrillators by estimating cardiac arrest risk, analyzing suitability of potential defibrillator locations, and engineering a match between supply and demand via integer optimization.
  • Chandra Veer Singh, MSE – His research is focused on integrated computational materials engineering. His group develops multi-scale computational tools and models to design novel materials for aerospace, automotive, minerals, and sustainable energy industries. Currently, he is collaborating with another member of the team, Prasanth Nair, on the uncertainty quantification in atomistic modeling. In this collaboration, they are developing Bayesian methods for calibration of interatomic potentials using experimental/ab-initio databases and quantifying the influence of the uncertainty in resultant parameters on materials behavior predicted using molecular dynamics.
  • Piero Triverio, ECE – He is the Canada Research Chair in modelling of electrical interconnects. He is an expert in model order reduction and in the simulation of complex electric/electromagnetic systems. His algorithms are used by leading CAD vendors (Idemworks, Ansys) and companies (IBM, SINTEF, Electricite de France, Siemens, Vestas) for the design of high-speed electronic products, power grids, and antennas.
  • David Steinman, MIE – His research focuses on the use of medical imaging and CFD to understand the role of hemodynamic forces in the development and treatment of cardiovascular diseases. His most recent research, including several international CFD challenges, has demonstrated that the widespread use of underpowered CFD in clinical research had led to an under-appreciation of turbulent-like flow phenomena in vessels of the brain and heart, emphasizing the need for careful attention to the numerics and the importance of highperformance computing strategies.
  • Aimy Bazylak, MIE – Her research is focused on the advancement of clean energy technologies, such as fuel cells and electrolyzers, by tailoring novel porous materials for enhanced flow, heat and mass transport at the microscale and nanoscale. The design of novel materials for improved fuel cell and electrolyzer performance is contingent upon efficient and predictive computational models, and these models must be informed by a detailed understanding of the multiphase transport phenomena in the complex porous materials inherent in state-of-the-art electrochemical conversion devices.
  • Costas Sarris, ECE – His group performs research on computational electromagnetics, with emphasis on highorder, multi-scale/multi-physics numerical methods, as well as uncertainty quantification techniques and convex optimization for electromagnetics. This basic research is targeted at applications ranging from radiowave propagation modeling in large scale environments (such as railway networks and urban areas), the physics of artificial media, microwave and optical meta-materials and antennas, the design of novel radiofrequency ablation probes, hyperthermia applicators and wireless power transfer systems.
  • Markus Bussmann, MIE – His research interests focus on the development and application of algorithms for simulation of interfacial/multiphase flows that may include heat transfer and phase change. Algorithm development has largely focused on volume of fluid methods for the direct simulation of interfacial flows. Algorithms and models are being applied to a number of important materials processing applications, such as oil/water/particle separation and particle coating processes.
  • Prasanth Nair, UTIAS – His research interests lie in three main areas: (i) computational modeling of deterministic and stochastic systems governed by partial differential equations, (ii) optimization algorithms for design, control and parameter estimation, and (iii) generalized function approximation problems. Ongoing research includes numerical methods for stochastic PDEs, real-time emulators of high-dimensional engineering systems with application to robust design optimization and uncertainty analysis, Bayesian methods and greedy algorithms for modelling spatio-temporal datasets and operator problems.
  • Clinton Groth, UTIAS – His current research focuses primarily on the development of reliable and robust, parallel, high-order, adaptive mesh refinement, finite-volume methods for the solution of multi-scale, physically-complex flows and the application of these techniques to numerical combustion modelling, including research on large-eddy simulation (LES) techniques for turbulent premixed, non-premixed, and partially premixed combusting flows, as well as fundamental studies of laminar flames for bio-based fuels under high-pressure gas-turbine-like conditions.

Student Organizing Committee

The student organizing committee is responsible for most of the day-to-day operations of CCSE. This includes organizing events such as seminars and workshops, managing expenses and maintaing the website. The committee wil rotate on an annual basis in order to afford as much opportunity as possible to other students who may wish to get involved. The organizing committee consists of graduate students of the aforementioned faculty team. More information regarding the organizing committee can be found here.