Keynote Speakers

Prof. Carlos A. Braumann
University of Évora, Portugal

Carlos A. Braumann is Professor at the University of Évora (UE), Portugal, where he has been Vice-Rector in 1987-94 and Rector in 2010-14. He is also an institutional evaluation expert for A3ES (the Portuguese Agency for Evaluation and Accreditation of Higher Education). His publications are mostly on Stochastic Differential Equations and its applications in several areas (population dynamics, fisheries, animal growth, demography, finance). He got his Ph.D. in 1979 at the Stony Brook University and his habilitation in Stochastic Processes at the UE in 1988. He is an elected member of the International Statistical Institute since 1992, a former President of the European Society for Mathematical and Theoretical Biology (2009-12) and of the Portuguese Statistical Society (2006-09 and 2009-12), and a former member of the European Regional Committee of the Bernoulli Society (2008-12).

Speech Title: "Some Biological Applications of Stochastic Differential Equations"

Abstract: The dynamics of some biological phenomena are affected by random environmental fluctuations and can be described by stochastic differential equation (SDE) models. We will present a few applications of these models, some developed with the co-authors Patrícia A. Filipe, Clara Carlos and Nuno M. Brites:
a) Models for the growth of animal populations, including the qualitative behavior of general models (in what concerns extinction and existence of a stationary density) and the effect of using approximate models.
b) Harvesting models and optimization of the fishing effort, including the comparison of optimal (but inapplicable) variable effort fishing policies with sustainable constant effort policies.
c) Models for individual growth of an animal and extension to mixed models for several animals, with applications to profit optimization of bovine growers.
Acknowledgements: The author is in the Departamento de Matemática, Escola de Ciências e Tecnologia, Universidade de Évora and in the research centre Centro de Investigação em Matemática e Aplicações, Instituto de Investigação e Formação Avançada, Universidade de Évora, supported by FCT (Fundação para a Ciência e a Tecnologia, Portugal, project UID/MAT/04674/2013).

Prof. João Tiago Praça Nunes Mexia
Universidade Nova de Lisboa, Portugal

João Tiago Praça Nunes Mexia was born in Lisbon in June of 1939. The most part of his career was as Full Professor at the FCT/UNL-Faculty for Sciences and Technology of the New University of Lisbon. At that time he supervised the teaching of Statistics at FCT/UNL and directed the Research Center in Mathematics of the University (CMA-Center for Mathematics and its Applications) from 1999 to 2009. In 2009 he became Emeritus Professor. Until now he supervised 19 Ph.D. and co-supervised 12 Ph.D. His research is centered on Linear Statistical Inference, having almost 100 papers published in International Journals.

Speech Title: "Dialectics Model x Observations in Statistics"

Abstract: We start by stressing the interplay between model and observations in statistical inference. While the model expresses what we know before collecting observations, the statistical inference uses it to extend information from the observations. In developing the models, probability concepts are used. We also stress in the first part the role played by duality in unifying parameter estimation and hypothesis testing. This approach is followed in the second part in which we apply it to Normal Mixed Models.

Prof. Swanhild Bernstein
TU Bergakademie Freiberg, Germany

Swanhild Bernstein studied from 1982 to 1987 Mathematics at the TU Karl-Marx-Stadt (nowadays Chemnitz, Germany) and finished her studies with the Diploma in Mathematics. After that she moved to Freiberg, Germany, and got a Ph.D. at the TU Bergakademie Freiberg in 1993. She continued working the university and was awarded a Feodor Lynen Fellowship of the Alexander von Humboldt foundation for the years 1998/99 which she spent at the University of Arkansas at Fayetteville, USA. Then she moved to the Bauhaus University in Weimar, Germany, and continued working in mathematics and applied topics. Finished her Habilitation in 2001 at the TU Bergakademie Freiberg and 2003 at Bauhaus University Weimar. Since 2013 she is a professor at TU Bergakademie Freiberg for Harmonic analysis and its applications. Her research interests are function theory, hypercomplex analysis, wavelets and approximation theory. She is an associated editor for Advances in Applied Clifford Algebras.
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Speech Title: "Quasi-Monogenic Functions and Riesz-Hilbert Transforms"

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Assoc. Prof. Alexander Plakhov
Universidade de Aveiro, Portugal

Alexander Plakhov is Associate Professor at the University of Aveiro, Portugal and Leading Researcher (without pay) at the Institute for Information Transmission Problems, Russia. His research interests focus on dynamical systems, optimization, billiards, optimal mass transport, Newton’s problem of minimal resistance, Kakeya problem, and classical geometry. Possible applications of his research include invisibility, retroreflectors, and aerodynamics of highly rarefied media. He got his Ph.D. in 1986 at the Moscow State University and his habilitation at the University of Aveiro. Alexander Plakhov was supervisor of the research projects PTDC/MAT/72840/2006 (2007 – 2010, Portugal) and PTDC/MAT/113470/2009 (2011 – 2013, Portugal) and is now a co-supervisor of the Royal Society International Exchanges Award IE160503 (2016 – 2018, UK). He is a member of the research group Optimization, Graph Theory and Combinatorics at CIDMA (Center for Research & Development in Mathematics and Applications) at the University of Aveiro.

Speech Title: "New Trends in Newton’s Problem of Minimal Resistance"

Abstract: Isaak Newton posed this problem more than 300 years ago in his Mathematical Principles of Natural Philosophy. It is as follows. A body moves in a highly rarefied medium of point particles, and the particles reflect elastically when colliding with the body’s surface. It is required to find the shape of the body that minimizes the force of aerodynamic resistance of the medium. Starting from 1993, new interest in mathematical community to Newton’s problem has been raised. The problem proved to be highly interdisciplinary, and various aspects of it were studied using methods borrowed from multidimensional variational analysis, theory of billiards, optimal mass transport, Kakeya needle problem, and theory of convex bodies. Interesting connections of the problem with Geometric Optics were found, including retroreflectors, invisibility, and the problem of camouflaging. A review of the state of art in this area will be given.

Invited Speakers

Assist. Prof. Sandra S. Ferreira
University of Beira Interior, Portugal

Sandra S. Ferreira is Assistant Professor at the University of Beira Interior (UE), Portugal. Her publications and current research interests focus on statistical inference for estimable functions and variance components, in linear mixed models with commutative orthogonal block structure (COBS). She completed her Ph.D. in 2006 at the University of Beira Interior, where she teaches courses in basic statistics, quantitative methods, hierarchical linear models and multivariate analysis. She is member of the working group (WG) CMStatistics (this WG focuses on all computational and methodological aspects of statistics) and member of IEOM Society and serves as an editorial board member of several journals.

Speech Title: "Additive Models and Cumulant Generating Function"

Abstract: In this talk, we first explain why the cumulant generating function is important. The cumulant generating function and the cumulants change in simple, easy to understand ways when their underlying probability density function is changed, and they are easy to define on most spaces. Then, a well-known property of cumulant generating function is used to obtain unbiased estimators for the first four order moments, which allow us to estimate the skewness and kurtosis. In this way we go beyond to the estimation of mean values and variances. As a consequence of this new approach, we no longer require the symmetry of densities as well as kurtosis similar to that of normal distribution in perform inference considering mixed models.