SCIENTIFIC PROGRAMS AND ACTIVITIES

April 26, 2024

Citations

GODAMBE, Vidyadhar P.
Department of Statistics and Actuarial Science, University of Waterloo
Vidyadhar P. Godambe, Department of Statistics and Actuarial Science, University of Waterloo, is internationally recognized as a major influence on the development of statistics over the past five decades. His pioneering and continuing work in the foundations of inference in survey sampling has provided deep insight into the characterization of optimal procedures and the role of randomization in statistics. He has also made outstanding and innovative contributions to the theory of estimation, formulating the methodology of estimating functions, leading and stimulating its further development, and promoting its application to diverse areas. His work has attracted many other researchers and students to fundamental problems in the theory of estimation and statistics generally.

GUTHRIE, J. Peter
Department of Chemistry, The University of Western Ontario
J. Peter Guthrie, Department of Chemistry, The University of Western Ontario, is a scientific leader in developing methods for the prediction of rate constants for chemical reactions in solution. He began with studies of the application of Marcus Theory to organic reactions, then developed Multidimensional Marcus Theory to treat concerted reactions in terms of the hypothetical stepwise reactions, and recently developed No Barrier Theory, which allows calculation of the rate constants for a great many reactions in solution with no adjustable parameters. Along the way he devised indirect methods, starting with calorimetric measurements, for determining equilibrium constants for formation of undetectable intermediates.

KAMRAN, Niky
Department of Mathematics and Statistics, McGill University
Niky Kamran, Department of Mathematics and Statistics, McGill University, is a leading researcher in the geometric study of differential equations. In a series of joint papers with Finster, Smoller and S. T. Yau, he has recently established sharp estimates for the long-time behaviour of Dirac fields in axisymmetric black hole geometries. His work on differential invariants and conservation laws for differential equations has led to an in-depth understanding of the property of geometric integrability for hyperbolic equations. He is also a founder of the rapidly expanding field of quasi-exactly solvable spectral problems in quantum mechanics. The growth of this field is due to a significant extent to his foundational papers. He is the recipient of the André Aisenstadt Prize in 1992, and is a Laureate of the Royal Academy of Sciences of Belgium. He won that academy's prize in mathematics in 1988 for his research monograph "Contributions to the study of the equivalence problem of Elie Cartan and its applications to partial and ordinary differential equations."

MADRAS, Neal
Department of Mathematics and Statistics, York University
Neal Madras, Department of Mathematics and Statistics, York University, is well known in the international mathematical and mathematical-physics communities for his leading edge contributions to the rigorous theory of self-avoiding walks. He is one of the world leaders in this field. His book with Gordon Slade, The Self-Avoiding Walk, is a major contribution that is of fundamental interest to physicists, chemists and mathematicians alike. It is recognized as the definitive reference work on the subject. Madras is also one of the leading contributors to the development and applications of more efficient Monte Carlo methods for the numerical simulation of self-avoiding walks, and has also made significant contributions to the general mathematical theory of self-avoiding geometrical objects, such as trees and lattice animals, which are important as lattice models of polymers. He is also one of the influential contributors to the general theory of Monte Carlo methods and randomized algorithms. Madras is also well known for his contributions to probability theory and stochastic processes, as well as for his excursions into mathematical biology.

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