By invitation of the Meeting Committee, there will be minisymposia in the following areas.
Org: Mike Zabrocki (York University)
This minisymposia will have speakers who research areas of algebra and combinatorics. Topics might include representation theory, algebra and symmetric functions and the use of combinatorial tools to solve problems in these areas.
Nantel Bergeron (York University), Sara Faridi (Dalhousie University), Adriano Garsia (University of California San Diego), Angela Hicks (University of California San Diego), Kurt Luoto (University of British Columbia).
Org: Miklos Csuros (University of Montreal)
The mini-symposium addresses current problems in the mathematics of molecular sequence analysis. Advanced technologies for sequencing DNA and proteins drive increasingly more comprehensive studies about the diversity of molecular sequences across living organisms. Talks in this mini-symposium touch on fundamental mathematical and algorithmic issues arising at different stages along the analysis pipeline between sequence data production and their biological applications.
Cedric Chauve (Simon Fraser University), Lucian Ilie (University of Western Ontario), Bin Ma (University of Waterloo), Paul Medvedev (University of California San Diego / University of Toronto), Juraj Stacho (Caesarea Rothschild Institute, University of Haifa).
Org: Mohit Singh (McGill University)
Combinatorial optimization problems usually come in two flavours, ones that can be solved in polynomial time and others that are NP-hard. This session will feature recent developments on problems from both classes. For the former, the talks will present fast algorithms for some fundamental combinatorial optimization problems. For the problems that are NP-hard, the talks will present approximation algorithms that are efficient and solve the problem approximately with a good guarantee on the solution.
Glencora Borradaile (Oregon State University), Dan Golovin (California Institute of Technology), Tom McCormick (University of British Columbia), Guyslain Naves (McGill University, Montreal), Bruce Shepherd (McGill University).
Org: Venkatesh Srinivasan (University of Victoria)
Computational complexity is a central field of research in theoretical computer science that focuses on classifying computational problems based on the amount of resources they require. Examples of such resources include time, space, communication, amount of randomness and so on. This field has introduced many interesting computational models to study such problems and has been the source of amazing results in the recent years leading to a deeper understanding of the power and limitations of efficient computation.
Paul Beame (University of Washington), Valerie King (University of Victoria), David Kirkpatrick (University of British Columbia), Anup Rao (University of Washington), Venkatesh Srinivasan (University of Victoria).
Org: Bruce Kapron (University of Victoria)
There are a now a variety of well-founded mathematical approaches to understanding security in cryptographic systems. Techniques from algorithms and computational complexity, formal logic, and information theory have all been successfully used in providing a more rigorous foundation for the study of cryptography. This minisymposium will explore cryptographic security from these varied perspectives.
Discrete and Computational Geometry
Org: Binay Bhattacharya (Simon Fraser University)
Binay Bhattacharya (Simon Fraser University), David Kirkpatrick (University of British Columbia), Ladislav Stacho (Simon Fraser University), Caoan Wang (Memorial University of Newfoundland), Sue Whitesides (University of Victoria).
Extremal Graph Theory
Org: Penny Haxell (University of Waterloo)
Extremal graph theory can be described as the study of how global properties of a graph can guarantee the existence of local substructures. A classical example is the theorem of Turán, which tells us the maximum number of edges that a graph with $n$ vertices can have, if it does not contain a complete subgraph with $r$ vertices. Many natural questions can be formulated as extremal graph problems, and the subject has developed into a rich theory. Applications abound in many fields, including number theory, optimization, theoretical computer science, economics, hardware design, and optical networks.
M. DeVos (Simon Fraser University), A. Kostochka (University of Illinois at Urbana-Champaign), D. Mubayi (University of Illinois at Chicago), O. Pikhurko (Carnegie Mellon University), J. Verstraete (University of California at San Diego).
Org: Tom Bohman and Po-Shen Loh (Carnegie Mellon University)
Probabilistic Combinatorics stands at the intersection of several thriving areas of Mathematics and Computer Science. It focuses on the combinatorial properties of random discrete objects (e.g., random graphs), and their potential applications to other branches of Mathematics. This mini-symposium will highlight a variety of recent advances in the field. We also intend to use this forum to make state of the art probabilistic techniques available to a broader audience.
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