Lecture I: Some episodes in the mathematics and science of 
              random phenomena
            Probability, the field of mathematics that studies random phenomena, 
              has a long history going back to the 17th century but it was in 
              the 20th century that it blossomed into one of the core areas of 
              the mathematical sciences. This development was driven by the transformation 
              from the deterministic viewpoint of classical physics to the probabilistic 
              viewpoint of statistical physics and quantum physics, and the emerging 
              role of probability in evolutionary biology and population genetics. 
              The probabilistic modelling of social phenomena including the introduction 
              of probabilistic models of financial markets also served as a powerful 
              catalyst for this development. Probability now plays a central role 
              in science and mathematics. In mathematics it forms a natural link 
              between the continuum world of analysis and physics and the discrete 
              world of combinatorics, computer science, and Monte Carlo methods. 
              Over the past 50 years probability has developed into an essential 
              research tool in the study of many fields including statistical 
              physics statistics, complex biological and communications networks, 
              economics, finance, genomics, genetics and ecology. The scientific 
              challenges posed by these fields have stimulated some exciting mathematical 
              advances which in turn have provided new scientific insights and 
              tools. In this lecture I will take a look at some of the major developments 
              in this story and the current synergetic nature of research in the 
              mathematical sciences.
            Lecture II: Spatial structures and universality classes in 
              stochastic systems
              
              The classical invariance principle establishes that the scaling 
              limit of a large class of discrete stochastic processes is given 
              by Brownian motion. Expanding on this, the idea that the large space 
              and time scale behaviour of many physical systems can be classified 
              into "universality classes" and that the structure of 
              such classes is highly dimension-dependent is one of the great developments 
              in statistical physics. In the realm of population processes, universality 
              classes related to super-Brownian motion have emerged from a surprising 
              range of particle systems and random combinatorial objects. This 
              lecture will present a review some of these developments. I will 
              also describe ongoing work using the idea of hierarchical mean-field 
              limit as one approach to understanding this phenomenon as well as 
              to identify multitype generalizations of these universality classes.
            
            Donald Dawson received his B.Sc.(Hon.) in Mathematics and Physics 
            from McGill University in 1958 and his doctorate from MIT in 1963. 
            He taught at both McGill University and Carleton University. He first 
            came to Carleton in 1970 and was appointed Professor Emeritus and 
            Distinguished Research Professor in 1999. He served as Director of 
            the Fields Institute from 1996-2000 and as the President of the Bernoulli 
            Society for Mathematical Statistics and Probability for 2003-2005. 
            He served as Associate Editor of the Canadian Journal of Statistics 
            (1980-87), Co-Editor-in-Chief of the Canadian Journal of Mathematics 
            (1988-1993) and on the editorial Boards of the Annals of Probability 
            and Electronic Journal of Probability. 
            Professor Dawson gave the 1991 Gold Medal Lecture of the Statistical 
            Society of Canada, the 1994 Jeffery-Williams Lecture of the Canadian 
            Mathematical Society, an invited lecture at the 1994 International 
            Congress of Mathematicians in Zurich, a plenary lecture at the 1996 
            World Congress of the Bernoulli Society in Vienna, and the Fields 
            Institute Distinguished Lecture Series in the Statistical Sciences 
            in 2003. 
            He is a Fellow of the Royal Society of Canada, Institute of Mathematical 
            Statistics and International Statistical Institute and received a 
            Max Planck Award of the for International Cooperation from the Humboldt 
            Foundation in 1996 and the CRM-Fields prize in 2004. He received an 
            honourary degree Dr. Sci. from McGill University in 2005. He was elected 
            to the Royal Society (London) in 2010.
            His research interests include probability and stochastic processes 
            and their applications to complex systems, statistical physics, genetics 
            and evolutionary biology. He has published over 100 scientific papers 
            and 7 monographs and has supervised 27 Ph.D. students and 30 postdoctoral 
            fellows. 
            
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