EVENTS

Affiliation: College of William and Mary, U.S.A.


Venue: office 27, 3rd floor of the Mathematics Department Building

Departamento de Matemática da Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (FCT NOVA)

Affiliation: Faculty of Mathematics and Natural Science, South-West University "Neot Rilski", Bulgaria


Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Institute of Mathematics, Potsdam University, Germany


Venue: office 2, 3rd floor of the Mathematics Department Building

Departamento de Matemática da Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (FCT NOVA)

The 11th European Conference on Mathematical and Theoretical Biology (ECMTB 2018) will be held in Lisbon, Portugal, from 23 to 27 July, 2018.

Departamento de Matemática da Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (FCT NOVA)

Affiliation: University of Granada, Spain

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Department of Mathematical Sciences, Durham University, Durham

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Department of Philosophy, Université Paris 1 Panthéon-Sorbonne

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: University of Copenhagen

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: University of Tunis El Manar

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Universidade Federal Fluminense

Venue: office 5, 3rd floor of the Mathematics Department Building

Affiliation: Komi Science Centre Ural Division, Russian Academy of Sciences, Department of Mathematics, Syktyvkar, Russian Federation and Syktyvkar State University

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: University of St Andrews, UK

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Institute of Mathematics, Potsdam University, Germany

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Centro de Investigación en Ciencias, Universidad Autónoma del Estado de Morelos (Cuernavaca, Morelos, México)

Venue: office 36, 3rd floor of the Mathematics Department Building

Affiliation: Faculty of Mathematics and Natural Science, South-West University "Neot Rilski", Bulgaria

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation:

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Università Degli Studi Di Salerno

Venue: office 35, 3rd floor of the Mathematics Department Building

Affiliation: King's College London

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Centro de Investigación en Ciencias, Universidad Autónoma del Estado de Morelos (Cuernavaca, Morelos, México)

Venue: Office 2, 3rd floor of the Mathematics Department Building

Departamento de Matemática da Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (FCT NOVA)

Sala 1.A - Edifício VII

Affiliation: Departamento de Matemática, Federal University of Minas Gerais (UFMG), Brazil

Venue: Office 5, 3rd floor of the Mathematics Department Building

Affiliation: College of William & Mary, USA

Venue: office 27, 3rd floor of the Mathematics Department Building

The purpose of this first DCV - DM Meeting was to present the research of both groups seeking to create new synergies in the area of biomathematics. The discussion was very dynamic with 25 researchers present. New meetings are already scheduled, in the form of more specific seminars. CMA as several researchers working on Mathematical Biology  

Affiliation: Faculty of Mathematics and Natural Science, South-West University "Neofit Rilski", Bulgaria

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Institute of Mathematics, University of Potsdam, Germany

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Department of Statistics and Operations Research, Institute of Mathematics,
University of Sevilha, Sevilha, Spain

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: School of Mathematics and Physical Sciences, University of Hull, United Kingdom

Venue: office 6, 3rd floor of the Mathematics Department Building

Affiliation: School of Mathematics and Statistics, University of St Andrews, United Kingdom

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: UNIMIB - Department of Mathematics and its Applications,
Università degli Studi di Milano-Bicocca, Milan, Italy

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Division of Mathematical Sciences, Nanyang Technological University, Singapore

Venue: office 2, 3rd floor of the Mathematics Department Building

Department of Mathematics of NOVA School of Science and Technology (FCT NOVA)

The conference will be held from Monday July 22nd through Friday July 26th, at Instituto Superior Técnico, University of Lisbon, Portugal.

1st WM2 - Women in Mathematics Meeting The Women in Mathematics Meeting will take place at Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, Portugal, from 22 to 24 July.

Affiliation: Federal University of Minas Gerais, Brazil

Venue: office 5, 3rd floor of the Mathematics Department Building

Affiliation: Institute of Mathematics, Potsdam University, Germany

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Laboratoire G-SCOP, France

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Faculty of Mathematics and Natural Science, South-West University "Neofit Rilski", Bulgaria

Venue: office 18, 3rd floor of the Mathematics Department Building

Department of Mathematics of NOVA School of Science and Technology (FCT NOVA)

Affiliation: Departamento de Biologia e CESAM, University of Aveiro

Venue: office 18, 3rd floor of the Mathematics Department Building

Workshop*
Sessões nos dias 9/10 e 10/10, das 14h às 15h30, no laboratório 2.2 do edifício 7

Modelação Estatística em Biologia: Como lidar com a não-normalidade de dados contínuos, com dados discretos ou dados qualitativos?

Prof.ª Regina Bispo, Departamento de Matemática & Centro de Matemática e Aplicações, FCT Nova

Resumo: Neste workshop pretende-se abordar alguns aspetos iniciais da Modelação Estatística, em duas situações frequentemente encontradas na Biologia: (1) quando a variável resposta, cuja variação se pretende explicar, apesar de contínua, não tem distribuição Normal e (2) quando a variável resposta não é contínua, podendo nesse caso ser quer uma quantidade discreta (contagem) que uma qualidade binária. Serão apresentados alguns casos reais que servirão de ponto de partida para uma abordagem prática, utilizando o software R.

* O workshop destina-se a investigadores e alunos de final do 1º ciclo ou 2º ciclo das áreas de Matemática e Biologia

[Entrada livre mediante inscrição prévia obrigatória AQUI ]

Workshop*
Sessões nos dias 9/10 e 10/10, das 14h às 15h30, no laboratório 2.2 do edifício 7

Modelação Estatística em Biologia: Como lidar com a não-normalidade de dados contínuos, com dados discretos ou dados qualitativos?

Prof.ª Regina Bispo, Departamento de Matemática & Centro de Matemática e Aplicações, FCT Nova

Resumo: Neste workshop pretende-se abordar alguns aspetos iniciais da Modelação Estatística, em duas situações frequentemente encontradas na Biologia: (1) quando a variável resposta, cuja variação se pretende explicar, apesar de contínua, não tem distribuição Normal e (2) quando a variável resposta não é contínua, podendo nesse caso ser quer uma quantidade discreta (contagem) que uma qualidade binária. Serão apresentados alguns casos reais que servirão de ponto de partida para uma abordagem prática, utilizando o software R.

* O workshop destina-se a investigadores e alunos de final do 1º ciclo ou 2º ciclo das áreas de Matemática e Biologia

[Entrada livre mediante inscrição prévia obrigatória AQUI ]

Mathematical Biology Day @ FCT NOVA
10/10/2019 Palestra
Dia 10/10, das 15h30 às 16h30, na sala de seminários do edifício 7

Título: Mathematical modeling: a fundamental tool in biology
Prof. Ruy Ribeiro, Laboratório de Biomatemática, Faculdade de Medicina da Universidade de Lisboa and Theoretical Biology and Biophysics, Los Alamos National Laboratory

[Entrada livre mediante inscrição prévia obrigatória AQUI ]
(https://eventos.fct.unl.pt/mathematicalbiologydayatfctnova)

Affiliation: Department of Mathematics, Denver University, USA

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Alfréd Rényi Institute of Mathematics & Eötvös University, Budapest, Hungary

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Fluminense Federal University, Brazil

Venue: office 5, 3rd floor of the Mathematics Department Building

Affiliation: Departamento de Matemática Aplicada, State University of Campinas, São Paulo, Brazil

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, Poland

Venue: CMA room, 2nd floor of the Mathematics Department Building

Affiliation: Moscow State University, Russia 

Venue: Office 18, 2nd floor of the Mathematics Department Building

Affiliation: University of Zielona Góra, Poland

Venue: CMA room, 2nd floor of the Mathematics Department Building

Affiliation: University of St Andrews, United Kingdom

Venue: Office 17, 3rd floor of the Mathematics Department Building

Faculdade de Ciências e Tecnologia – Universidade Nova de Lisboa (FCT NOVA), Seminar Room – Departamento de Matemática – Building VII

Affiliation: King's College London, London, United Kingdom

Venue: Office 2, 3rd floor of the Mathematics Department Building

Dates: 15/12/2019 to 21/12/2019

Departamento de Matemática da Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (FCT NOVA)

Affiliation: Institute of Mathematics, Potsdam University, Germany

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Department of Mathematics, Faculty of Science, Khon Kaen University, Thailand

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: School of Mathematics, University of Manchester, United Kingdom

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Faculty of Mathematics and Natural Science, South-West University "Neofit Rilski", Bulgaria

Venue: office 2, 3rd floor of the Mathematics Department Building

Affiliation: Laboratoire LMNO, Université de Caen Normandie, France

Venue: office 18, 3rd floor of the Mathematics Department Building

Affiliation: Instituto de Matemática e Estatística da Universidade de São Paulo

Venue: office 35, 3rd floor of the Mathematics Department Building

Affiliation: School of Mathematics and Statistics, University of St Andrews

Venue: office 2, 3rd floor of the Mathematics Department Building

09:45 - Opening

António Malheiro (CMA)

Luís Caires (NOVA LINCS)

Marcos Raydan (CMA)

Pedro Barahona (NOVA LINCS)

10:00 - 10:45

Statistics and Machine Learning in Biomedical and Environmental Sciences, Marta Lopes (CMA / NOVA LINCS)

10:45 - 11:15

How to test different block diagonal structures in one or several covariance matrices, Filipe Marques (CMA)  

11:15 - 11:30

SI-MORENA’s Data Driven Projects, Carlos Damásio and João Moura Pires (NOVA LINCS)

11:30 - 12:00

Classification with symbolic data, Paula Amaral (CMA)

12:00 - 12:30

Pot-pourri of Systems for Big Data and Data Science, Nuno Preguiça (NOVA LINCS)

12:30 - 14:00

Lunch

14:00 - 14:30

Semantic Similarity and Textual Entailment in the Portuguese language, Rui Rodrigues (CMA)

14:30 - 15:00

Title TBA, João Magalhães (NOVA LINCS)

15:00 - 15:30

Feature selection for marine species origin prediction, Regina Bispo (CMA)

15:30 - 16:00

Deep Models in Data Science: some problems and applications, Ludwig Krippahl (NOVA LINCS)

16:00 - 16:30

General discussion and closing

Addicional information here.

Addicional information here.

Título: Monitorização da transmissibilidade da COVID-19 em Portugal

Orador: Liliana Antunes, INSA

Título: Estimação de parâmetros epidemiológicos da COVID-19: internamentos e óbitos

Orador: João Pereira, INSA, UTAD (bolseiro do Projeto COVID-19 in-CTRL)

Título: Modelação matemática da dinâmica de transmissão de COVID-19 em Portugal

Orador: Constantino Caetano, INSA

More information is available here.

Addicional information here.

Website

Website

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Venue: office 2, 3rd floor of the Mathematics Department Building

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Venue: office 2, 3rd floor of the Mathematics Department Building

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Venue: office 2, 3rd floor of the Mathematics Department Building

Venue: office 2, 3rd floor of the Mathematics Department Building

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Venue: office 2, 3rd floor of the Mathematics Department Building

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Venue: office 2, 3rd floor of the Mathematics Department Building

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Venue: office 18, 3rd floor of the Mathematics Department Building

Venue: office 2, 3rd floor of the Mathematics Department Building

Venue: office 2, 3rd floor of the Mathematics Department Building

Venue: office 2, 3rd floor of the Mathematics Department Building

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Abstract: This talk will discuss some applications of Bayesian matrix/tensor factorization and mixed effects models on biological and health data. Bayesian matrix factorization is applied to the expanded disability status scale (EDSS) data of multiple sclerosis patients. Mixed effects models are applied to model the effect of pharmaceutical pollution on amphibians’ tadpoles development. The models are fitted in Python for Bayesian matrix factorization and SAS for mixed models. Several models are tested under different situations to discover the best modelling alternatives while giving details on analysis strategy and software implementation. Since the datasets used were relatively small, it was possible to explore different choices for the models within reasonable computation time and study how they impact the predictive performances. The results show that these methods can handle missing data properly and arrive at accurate predictions, especially when working with sparse and noisy real-world datasets.

Venue: office 18, 3rd floor of the Mathematics Department Building

Venue: office 2, 3rd floor of the Mathematics Department Building

Abstract: "In this paper we consider constrained optimization problems where both the objective and constraint functions are of the black-box type. Furthermore, we assume that the nonlinear inequality constraints are non-relaxable, i.e. their values and that of the objective function cannot be computed outside of the feasible region. This situation happens frequently in practice especially in the black-box setting where function values are typically computed by means of complex simulation programs which may fail to execute if the considered point is outside of the feasible region. For such problems, we propose a new derivative-free optimization method which is based on the use of a merit function that handles inequality constraints by means of a log-barrier approach and equality constraints by means of a quadratic penalty approach. We prove convergence of the proposed method to KKT stationary points of the problem under quite mild assumptions. Furthermore, we also carry out a preliminary numerical experience on standard test problems and comparison with state-of-the-art solvers which shows efficiency of the proposed method."

Abstract: "In this paper we consider constrained optimization problems where both the objective and constraint functions are of the black-box type. Furthermore, we assume that the nonlinear inequality constraints are non-relaxable, i.e. their values and that of the objective function cannot be computed outside of the feasible region. This situation happens frequently in practice especially in the black-box setting where function values are typically computed by means of complex simulation programs which may fail to execute if the considered point is outside of the feasible region. For such problems, we propose a new derivative-free optimization method which is based on the use of a merit function that handles inequality constraints by means of a log-barrier approach and equality constraints by means of a quadratic penalty approach. We prove convergence of the proposed method to KKT stationary points of the problem under quite mild assumptions. Furthermore, we also carry out a preliminary numerical experience on standard test problems and comparison with state-of-the-art solvers which shows efficiency of the proposed method."

Abstract: From minimizing construction costs to maximizing image quality, optimization arises naturally in virtually every field of modern research. In many of these applications, the objective function is provided by a blackbox or simulation. Derivative-free algorithms (DFA) provide powerful tools to solve such problems. In this workshop, we introduce the basics of DFA, including several examples of their usage. We expand further by including recent research results and
future directions of DFA.

Day 31 will cover:
- What is BBO and DFA?
- Basics of Direct-search methods
- Recent advancements in p-bases

Speaker Bio: Dr. Warren Hare is a Full Professor of Mathematics at the University of British Columbia, Canada. He serves as an Associate Editor with Set Valued and Variational Analysis and the Pacific Journal of Optimization. He is co-author of the book Derivative-Free and Blackbox Optimization and co-winner of the EURO excellence in practice prize.

Abstract: From minimizing construction costs to maximizing image quality, optimization arises naturally in virtually every field of modern research. In many of these applications, the objective function is provided by a blackbox or simulation. Derivative-free algorithms (DFA) provide powerful tools to solve such problems. In this workshop, we introduce the basics of DFA, including several examples of their usage. We expand further by including recent research results and
future directions of DFA.

Day 4 will cover:
     - Basics of Model-based methods
     - Constructing models
     - Future of DFA

Speaker Bio: Dr. Warren Hare is a Full Professor of Mathematics at the University of British Columbia, Canada. He serves as an Associate Editor with Set Valued and Variational Analysis and the Pacific Journal of Optimization. He is co-author of the book Derivative-Free and Blackbox Optimization and co-winner of the EURO excellence in practice prize.

Venue: office 2, 3rd floor of the Mathematics Department Building

Abstract:

Millions of people play solitaire (patience) every day. One of the (many) embarrassments of the applied probability community is: WE CAN'T FIGURE OUT SOLITAIRE!. What's a good strategy? If one plays well, what's the chance of winning? How does this depend on the rules? In Vegas, you can 'buy a deck' for $52 and get $5 for each card played forward (rules; go through once, one at a time, no splitting piles (a la Microsoft)). How close to fair is this? I will report some machine learning results (with Ben VanRoy and Robbie Yan). The main point of the talk is to introduce a simple solitaire that we can solve. One point is the connection with the deepest mathematics. Symmetric functions, tableaux combinatorics, Baik-Deift-Johansson theorem. A second point is that this variant, patience sorting, has recently emerged in semigroup theory!--work of Cain,Malheiro,Silva and others. In this introductory talk, I hope to start a conversation between these two communities.

Zoom link: https://videoconf-colibri.zoom.us/j/95986880586?pwd=a2lHSWYwQnM2VGswRGdUWXFRUk5oUT09

Abstract:

It is well known that the set of transformations on a set X
and the set of endomorphisms of a vector space V have many properties in
common, so that these monoids are now seen under the framework of
endomorphism monoids of independence algebras (matroids with an
additional free basis property whose classification helped Givant to
work on categorising varieties and quasi-varieties categorical/free in
power).
Symons started to look at automorphisms of the set of all transformation
on a set X that have image a fixed subset of X, say Y, and this study
got extended to Green's relations and ideals by multiple authors, who
also carried a similar study on vector spaces. As the results were
(maybe unsurprisingly) similar, it prompted a generalisation of their
study under the framework of independence algebras. The semigroup T(A,B)
which consists of all endomorphisms of an independence algebra A whose
image lie inside a subalgebra B is a non-regular subsemigroup of End(A),
the endomorphism monoid of A. This means in particular that the usual
Green's relations are not directly inherited from that of End(A) and its
ideals and extended Green's relations are more interesting. In
particular the latter somewhat depend on the codimension of the
subalgebra B. In this talk, I will describe some structural properties
of this semigroup.

Zoom link: https://videoconf-colibri.zoom.us/j/95986880586?pwd=a2lHSWYwQnM2VGswRGdUWXFRUk5oUT09

Abstract:

The Dehn function for a semigroup or group M is an asymptotic measure of how bad the "naive solution" to the word problem in M may be. The word problem in M is decidable if and only if the Dehn function of M is a recursive function, but frequently the Dehn function is significantly more poorly behaved than the complexity of the word problem. On the other hand, the word problem for one-relation monoids is one of the most intriguing and important open problems in semigroup theory. For that reason, it makes sense to ask: how bad can the Dehn function of a one-relation monoid be? I will present the history of the problem, as well as some of my own recent progress on this topic for the class of one-relation monoids where the relation is of the form bUa = a, for a word U, answering in particular a question posed by Cain & Maltcev in 2013.

More information available here

Abstract: Analytics focuses on transforming data into insights by applying advanced analytical methods, based on mathematics, statistics, operations research and artificial intelligent models and algorithms, with the objective to improve the performance of an organization. One of the main tools in Analytics is Optimization. In this talk, we present the optimization tools and methodologies applied to NonProfit Organizations (NPO). We will describe applications of  Mathematical Programming Models and Metaheuristics Algorithms to Social Care, Healthcare, Humanitarian Logistics and Environmental organizations. Examples of applications of Optimization in these organizations are: home health care logistics and scheduling; location of the primary health care centers or schools; planning the humanitarian aid distribution; planning a sustainable transportation, etc. We will also discuss the main aspects of these models and algorithms, and the main differences to other more frequent applications, as in manufacturing and retailing industries. 

Bio: Helena Ramalhinho Lourenço is a Full Professor at the Economics and Business Department at the University Pompeu Fabra, Barcelona, Spain. She has a B.A. and Master degree in Statistics and Operations Research from the University of Lisbon, Portugal, and a Ph.D. in Operations Research from Cornell University, New York, USA. She has been involved in different research projects and consulting for business firms in the area of Operations Research and Logistics. Helena has published many articles in prestigious international scientific journals and has presented her work at international congresses and conferences. Helena teaches at various undergraduate, master’s and PhD’s programs at UPF and other universities. She is currently the director of the Business Analytics Research Group. Her research interests include Operations Research, Scheduling, Combinatorial Optimization, Metaheuristics, Iterated Local Search, Heuristic Search Optimization, Vehicle Routing, and applications on Supply Chain Management, Logistics, Operations Management and Health Care.
http://lena.upf.edu/

Abstract: Analytics focuses on transforming data into insights by applying advanced analytical methods, based on mathematics, statistics, operations research and artificial intelligent models and algorithms, with the objective to improve the performance of an organization. One of the main tools in Analytics is Optimization. In this talk, we present the optimization tools and methodologies applied to NonProfit Organizations (NPO). We will describe applications of  Mathematical Programming Models and Metaheuristics Algorithms to Social Care, Healthcare, Humanitarian Logistics and Environmental organizations. Examples of applications of Optimization in these organizations are: home health care logistics and scheduling; location of the primary health care centers or schools; planning the humanitarian aid distribution; planning a sustainable transportation, etc. We will also discuss the main aspects of these models and algorithms, and the main differences to other more frequent applications, as in manufacturing and retailing industries. 

Bio: Helena Ramalhinho Lourenço is a Full Professor at the Economics and Business Department at the University Pompeu Fabra, Barcelona, Spain. She has a B.A. and Master degree in Statistics and Operations Research from the University of Lisbon, Portugal, and a Ph.D. in Operations Research from Cornell University, New York, USA. She has been involved in different research projects and consulting for business firms in the area of Operations Research and Logistics. Helena has published many articles in prestigious international scientific journals and has presented her work at international congresses and conferences. Helena teaches at various undergraduate, master’s and PhD’s programs at UPF and other universities. She is currently the director of the Business Analytics Research Group. Her research interests include Operations Research, Scheduling, Combinatorial Optimization, Metaheuristics, Iterated Local Search, Heuristic Search Optimization, Vehicle Routing, and applications on Supply Chain Management, Logistics, Operations Management and Health Care.
http://lena.upf.edu/

Title: EVT-Informed Statistical Inference

Speaker: Miguel de Carvalho, University of Edinburgh

Date | Time: December 7, 2022 | 14h00

Place: FCT NOVA, IX-2.25

Zoom: https://videoconf-colibri.zoom.us/j/88333359956  (For remote participants)

Abstract: The widely felt impact of record-breaking extreme events—such as stock market crashes, earthquakes, heatwaves, or widespread flooding—calls for an urgent need for a better understanding and quantification of their risk. In this talk, I will offer an overview on recent developments on the field of Extreme Value Theory (EVT) with a bias towards some of my own contributions.

Short Bio: Miguel de Carvalho is Reader in Statistics at the School of Mathematics, University of Edinburgh and the former Director of the Centre for Statistics of the same University. His research interests include, inter alia, Applied Statistics, Biostatistics, Econometrics, Risk Analysis, and Statistics of Extremes. He has been an AE for a variety of top tier journals in the field of Statistics, including the Journal of the American Statistical Association, the Annals of Applied Statistics as well as the American Statistician. He is currently the President of the Portuguese Statistical Society.

Será realizado em modelo híbrido presencial e online. O link para assistir online é o seguinte
https://videoconf-colibri.zoom.us/j/8088003611

Shor convexity, min-max QCQPs and application to min-max regret of
nonconvex QPs

Immanuel M. Bomze (Univ.Vienna), jointly with Paula Amaral (Univ.Nova
Lisboa, work in progress)

Under (finitely many) uncertain scenarios, min-max regret for (possibly
nonconvex) Standard QPs can be reduced to a min-max (fractional) QCQP.
En route to narrowing the gap between powerful conic lower bounds and
efficient upper bounds, i.e. good feasible values, we will study
the apparently novel notion of *Shor convexity* (not to be confused with
the well-known notion of Schur convexity) suggested by lifting
techniques, and discuss possibilities to use bundle methods for
tightening upper bounds. A generalization of the famous Jensen's
inequality will be proved as well.

Palestra Motivacional

Venue: office 2, 3rd floor of the Mathematics Department Building

Guillaume Cantin

Département Informatique, UMR_6004 Laboratoire des Sciences du Numérique de Nantes, Nantes Université

Title:

Modeling and analysis of complex epidemic events using hybrid dynamical systems

Abstract:

In this talk, I will present recent works realized in collaboration

with Cristiana J. Silva on the modeling and analysis of complex epidemic events.

In the first part, I will show how to model the spatial spreading of an epidemic in a heterogeneous geographical environment using complex networks of dynamical systems.

The influence of the topology of the underlying network

on the dynamics of the epidemic will be illustrated with a theoretical approach for small networks,

and with a computational approach for large networks.

In the second part, I will present a novel approach for studying the impacts of human behaviors

on the spreading of an epidemic, using hybrid dynamical systems coupling a macroscopic approach relying on differential equations

with a microscopic individual-based approach.

Theoretical results on the well-posedness of such hybrid models and on the existence of particular

solutions exhibiting irregular oscillations will be exposed.

Zoom link: https://videoconf-colibri.zoom.us/j/95986880586?pwd=a2lHSWYwQnM2VGswRGdUWXFRUk5oUT09

Abstract: 

The Grassmann variety of k-dimensional subspaces of an n-dimensional vector space over a finite field with q-elements can be thought of as the ``moduli space'' of all linear q-ary (n,k)-codes. At the same time, each Grassmann variety naturally provides an algebraic geometry code via its Plucker embedding. The structure of Grassmann codes has been parsed by many researchers, most notably by Sudhir Ghorpade. In this talk, we will discuss a fruitful generalization of the Grassmann codes by using the embeddings of Grassmannians into higher-dimensional projective spaces. This new family of ``higher Grassmann codes'' has interesting connections with the modular representation theory of SL_n.

We discuss the process of averaging via Cesàro means, both for sequences and for functions. We start reviewing Hardy's results in the 1920s and arrive at some recent results in Functional Analysis and Operator Theory.

The talk is based on a joint work with Oleksiy Karlovych.

The lower estimate by Gohberg and Krupnik (1968) and the upper estimate

by Hollenbeck and Verbitsky (2000) for the norm of the Riesz projection

$P$ on the Lebesgue space $L^p$ lead to $\|P\|_{L^p\to L^p}=1/\sin(\pi/p)$

for every $p\in(1,\infty)$. Hence $L^2$ is the only space among all Lebesgue

spaces $L^p$ for which the norm of the Riesz projection $P$ is equal to one.

Banach function spaces $X$ are far reaching generalizations of Lebesgue spaces

$L^p$. We prove that the norm of $P$ is equal to one on the space $X$ if and

only if $X$ coincides with $L^2$ and there exists a constant $C\in(0,\infty)$

such that $\|f\|_X=C\|f\|_{L^2}$ for all functions $f\in X$. Independently

from this, we also show that the norm of $P$ on $X$ is equal to one if and

only if the norm of the backward shift operator $S$ on the abstract Hardy

space $H[X]$ built upon $X$ is equal to one.

Venue: office 2, 3rd floor of the Mathematics Department Building

Venue: office 2, 3rd floor of the Mathematics Department Building

Abstract

Robot Dance is a computational platform developed in response to the coronavirus
outbreak, to support the decision-making on public policies at a regional
level. The tool is suitable for understanding and suggesting levels of
intervention needed to contain the spread of diseases when the mobility of
inhabitants through a regional network is a concern. Such is the case for Covid-19
that is highly contagious and, therefore, the circulation of people must be
considered in the epidemiological compartmental models. Robot Dance anticipates
the spread of epidemics in a complex regional network, identifying fragile links
where applying differentiated measures of containment, testing, and vaccination
are the most effective. Based on stochastic optimization, the model determines
optimal strategies on the basis of the commuting of individuals and the situation
of hospitals in each district. Uncertainty in the capacity of intensive care beds
is handled by a chance-constraint approach. Some functionalities of Robot Dance
are illustrated on the state of São Paulo in Brazil, using real data for a region
with more than forty million inhabitants. We will also show extensions of the model
that allow to design vaccination campaigns that take into account multiple
sub-populations that present different responses to the virus.

Title: Business dynamics models: one step ahead optimal control via optimization

Abstract: Bsiness dynamics refers to a combination of business management and financial objectives embedded in a dynamical system model subject to a control that optimizes an index that takes both management and financial aspects into account. . The objective is to optimize an index that takes into account both managerial and financial aspects, so that the control is applicable in real time. The main technique proposed is one-step-ahead optimal control, which will be formulated as a mathematical programming problem. Examples of debt amortization, cash balance, control of supply chains, dynamic advertising games, among others, will be presented.