Industry and academic professionals will be sharing their expertise and experiences in the field of Mathematics and Statistics.
Dr. Caroline Colijn
Dr. Caroline Colijn will describe research topics at the interface of public health and mathematics and showcase how new mathematical methods are needed for understanding and controlling infectious disease.
Dr. Colijn works at the interface of mathematics, evolution, infection and public health. She joined SFU's Mathematics Department in 2018 as a Canada 150 Research Chair in Mathematics for Infection, Evolution and Public Health. She now heads an interdisciplinary research group at SFU. She did her PhD in applied mathematics at the University of Waterloo, where she studied the foundations of quantum mechanics. She changed tack in her postdoctoral years, working on mathematical modelling with Prof. Michael Mackey at McGill and the on TB modelling and epidemiology in Megan Murray's group at the Harvard School of Public Health and the Broad Institute at MIT. She moved to the Department of Engineering Mathematics in Bristol, England in 2007 and later joined Imperial College London's Department of Mathematics in 2011. She has broad interests in applications of mathematics to questions in evolution and health, and was a founding member of Imperial's Centre for the Mathematics of Precision Healthcare.
Dr. Peter Martin Krafft
Peter’s research develops new social data analysis methods to better understand rumors, fads, disinformation, and information flow. Some of his recent work in these areas has also touched on public understanding of science and public understanding of artificial intelligence (AI). The methods he has developed span observational data analysis, behavioral modeling, online laboratory experimentation, and online field experimentation. Several of his research projects have specific implications that could inform pressing policy issues, such as the development of systems for dealing with certain types of misinformation, the design of online financial exchange platforms, ethical approaches to social data science, and AI governance.
Peter is currently a Moore/Sloan & WRF Innovation in Data Science Postdoctoral Fellow at the University of Washington, where he works in the DataLab, and co-directs the Critical Platform Studies Group. He is also a part-time postdoctoral researcher at the University of California Berkeley's Social Science Matrix. Peter completed his PhD in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, where he was located in the Computer Science and Artificial Intelligence Laboratory. He has published across human-computer interaction (HCI) and AI, and has won awards for his teaching and research.
Dr. Stephanie Van Willigenburg
Stephanie’s area of expertise is algebraic combinatorics. Initially she concentrated on descent algebras of Coxeter groups with a particular focus on their multiplicative structure, and the establishment of their basic algebraic structure and representation theory over fields of finite characteristic.
Subsequently, she worked on Pieri operators on posets that link the diverse areas of Schubert calculus, combinatorics of polytopes, and P-partitions, amongst others. One particular discovery was the duality between peak functions and the cd-index. This led to studying ribbon Schur function equality, generalising this study to skew Schur function equality and applying the knowledge gleaned to the study of Schur positivity.
Most recently, she have been studying a natural quasisymmetric refinement of Schur functions that reflect many of the properties displayed by Schur functions, such as Pieri rules, a Littlewood-Richardson rule, and their role in the representation theory of the 0-Hecke algebra. Stephanie has also become interested in a generalization of the chromatic polynomial, known as the chromatic symmetric function.
Dr. David Muraki
The common mathematical theme in David’s research is the development and application of asymptotic methods for nonlinear PDEs. These asymptotic techniques are used for simplifying model systems to allow further analysis or computation, or for constructing approximate solution algorithms for PDEs. Numerical computation plays an essential role in the investigation and verification of these asymptotic theories. These methods are then used as a basis for understanding the evolution and dynamics of nonlinear patterns and waves within PDE models.
Most recently, he has been investigating models from the field of geophysical fluid dynamics (GFD), a specialization to rotating and stratified fluids which applies to the motions of the atmosphere and oceans. Much of this work, pertaining to midlatitude (North American) weather, is in direct collaboration with meteorologists at the National Center for Atmospheric Research (NCAR, Boulder CO) and the Atmospheric Sciences Department at the University of Washington (Seattle WA). In addition to the above issue of pressure-cell asymmetry, we are also investigating the generation of atmospheric gravity waves in connection with clear-air turbulence, and the Influence of the tropopause (the lower boundary of the stratosphere) on the development of surface weather.