This seminar takes place within the scope of the master's course "Seminário em Matemática Pura". This is a public session where a presentation is made by the student.
 
Room 4.6, Building VIII

Abstract:
For germs of plane curves, Zariski proved that an irreducible plane curve germ is analytically equivalent to an irreducible plane curve germ with finite Puiseux parametrization. Germs of plane curve germs represent the simplest instance of quasi-ordinary hypersurfaces in dimension two. Zariski’s algebraic techniques cannot be applied to the general case. We show that, for some types of quasi-ordinary surfaces, these techniques can indeed be applied in the context of contact geometry. This is an ongoing work for my thesis.

Online seminar

Abstract:
Coding theory, originated in the late 1940s, is driven by the need toensure reliable communication over noisy channels. Linearerror-correcting codes, in particular, became central to the fielddue to their algebraic structure and practical utility. These codescan be studied via combinatorial, algebraic, and geometric methods:to each code one associates a matroid from its generator orparity-check matrix, and the independent sets of the matroid define asimplicial complex whose Stanley–Reisner ring captures the code’scombinatorial structure. The Betti numbers of this ring encode keyinvariants of the code. Computing them is difficult in general, butthey reflect important parameters and offer new perspectives on thecode’s structure. In this talk, we will focus on the homologicalinvariants of certain families of BCH codes. BCH codes are regardedas one of the most useful codes in the theory of error-correctingcodes. Despite their prominence, basic properties such as dimensionand minimum distance remain unresolved in many cases. Timepermitting, we will discuss open problems such as Charpin’sconjecture regarding the minimum distance of primitive BCH codes.

Room: 4.6, ed. VIII

Abstract: The concept of a determinant associated with a finite group originates in the work of Dedekind and Frobenius in the late 19\textsuperscript{th} century. This idea was later extended to finite semigroups, where the determinant of the semigroup algebra captures deep structural information. For commutative semigroups, Steinberg provided a factorization of the semigroup determinant, and more recently, the theory has been developed for broader classes, such as semigroups in the pseudovariety $\ensuremath{\mathsf{ECom}}$, where all idempotents commute.

In this talk, we trace the development of computing determinants for finite semigroups, from its classical origins to more recent results. We focus on semigroups whose structure enables determinant computation via partial orders and canonical decompositions, particularly using the notion of $\ll$-smoothness. These developments highlight both the possibilities and limitations in extending the theory beyond commutative and idempotent-commuting settings.

We also discuss recent progress in identifying broader classes of semigroups where determinant computations remain tractable, even when full $\ll$-transitivity is absent. This opens new directions for understanding the algebraic and combinatorial properties that govern the behavior of semigroup determinants.

Tensor computation extends the principles of linear algebra and numerical analysis to higher-dimensional data structures, allowing for efficient processing of complex data. Tensors play a central role in a variety of disciplines, from machine learning to scientific simulations. Tensors are among the most versatile and powerful mathematical tools available, with applications in many disciplines such as physics, computer science, engineering, graphs, and machine learning.

The mini-course is designed as a comprehensive introduction to tensors and their applications, bridging theory and practice. It seeks to demystify the subject for beginners while offering valuable insights for those with more advanced knowledge. Our focus is twofold: 

Conceptual Understanding: By presenting tensors in a clear and accessible manner, we aim to equip the  course attendees with a solid grasp of the core principles. 

Practical Applications: With numerous examples and case studies, we plan to illustrate how tensors are used to address real-world challenges, from simulating physical systems to enabling breakthroughs in artificial intelligence.

Registration can be completed here.

Tensor computation extends the principles of linear algebra and numerical analysis to higher-dimensional data structures, allowing for efficient processing of complex data. Tensors play a central role in a variety of disciplines, from machine learning to scientific simulations. Tensors are among the most versatile and powerful mathematical tools available, with applications in many disciplines such as physics, computer science, engineering, graphs, and machine learning.

The mini-course is designed as a comprehensive introduction to tensors and their applications, bridging theory and practice. It seeks to demystify the subject for beginners while offering valuable insights for those with more advanced knowledge. Our focus is twofold: 

Conceptual Understanding: By presenting tensors in a clear and accessible manner, we aim to equip the  course attendees with a solid grasp of the core principles. 

Practical Applications: With numerous examples and case studies, we plan to illustrate how tensors are used to address real-world challenges, from simulating physical systems to enabling breakthroughs in artificial intelligence.

Registration can be completed here.

Seminarof Analysis

Speaker: Prof. Lahcen Laayouni (School of Science and Engineering, Al AkhawaynUniversity).

Date/time: 25/06/2025 (Wednesday), from 14:15 to 15:15.

Location:  Room 4.6, Building VIII.

Title:  Optimized Schwarz Methods: Challenges andPromises at Continuous and Algebraic Levels

Abstract:  Optimized Schwarz methods are a class ofdomain decomposition techniques designed to improve the convergence ofiterative solvers for partial differential equations (PDEs) by imposingoptimized transmission conditions. This talk explores the challenges and promisesof these methods at both continuous and algebraic levels. At the continuouslevel, we address the design of effective transmission conditions, theirdependence on problem-specific parameters. At the algebraic level, we examinethe construction of algebraic block transmission conditions for robustpreconditioners. Through theoretical and numerical results, we show thepotential of optimized Schwarz methods to handle large-scale PDE problems.

Statistics and Risk Management Seminar

Department of Mathematics, NOVA MATH/FCT NOVA

Title: Illuminating Distributions: Wavelet-Based Quantile Density Estimation with Applications in Auction Theory

Speaker: Hassan Doosti, Macquarie University's School of Mathematical and Physical Sciences, Sidney, Australia

Date | Time: June 26, 2025 | 14:00

Zoom: https://videoconf-colibri.zoom.us/j/88333359956

Abstract: Quantile density functions, which capture the local structure of probability distributions, have emerged as powerful tools in fields ranging from risk analysis to economic modeling. In this talk, we delve into advanced nonparametric strategies for estimating quantile density functions, spotlighting the versatility and precision of wavelet-based techniques. We investigate a range of estimators—including linear, hard thresholding, and block thresholding approaches—within both unbiased and length-biased sampling frameworks. A key focus is placed on the challenges introduced by sampling bias and the use of adaptive wavelet methods for effective bias correction. Through the lens of auction theory, we demonstrate how quantile-driven insights can unravel bidder behavior and valuation dynamics. Supported by simulation studies and real-world case examples, the presentation underscores the power of wavelet methods in handling complex and irregular data landscapes.

Short Bio: Dr. Hassan Doosti is a Senior Lecturer in Statistics at Macquarie University's School of Mathematical and Physical Sciences. He also serves as the Program Director for the Master of Data Science program. Dr. Doosti specializes in flexible modeling techniques, particularly in nonparametric curve estimation, focusing on scenarios involving incomplete or biased data. His research encompasses areas such as probability density, quantile density, and regression functions. With a prolific publication record exceeding 70 research papers, he has contributed significantly to the field. Dr. Doosti has also edited volumes, including Flexible Nonparametric Curve Estimation and Ethics in Statistics: Opportunities and Challenges. His work bridges theoretical advancements with practical applications across various domains, including medical studies and business analytics.

Organizers: Isabel Natário and Mina Norouzirad

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This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 (https://doi.org/10.54499/UIDB/00297/2020) and UIDP/00297/2020 (https://doi.org/10.54499/UIDP/00297/2020) (Center for Mathematics and Applications)

Seminar of Analysis

Speaker: Prof. João Carvalho (Centre for Mathematics, University of Porto &Prince Henry Portucalense University).

Date/time: 04/07/2025 (Friday), from 14:15 to 15:15.

Location:  Room 4.7, Building VIII.

Title: Nonlinear dynamics and bifurcationsin epidemic models

Abstract:  In thefirst part we analyze a periodically forced SIR model. We prove that for $R0< 1$ the system exhibits multiple endemic equilibria -- backwardbifurcation. Using the theory of strange attractors, we prove the persistenceof strange attractors for an open subset in the parameter space where R0 < 1.

In the second part, we address a modified SIRmodel with a constant vaccination strategy and the bifurcations it unfolds. Weexplicitly prove that the endemic equilibrium is a codimension two singularityin the parameter space (R0, p), where R0 is the basic reproduction number and pis the proportion of susceptible individuals successfully vaccinated at birth.The analytical expressions of the bifurcation curves as a function of R0 and pestimate the proportion of vaccinated susceptible individuals necessary for thedisease to be eliminated from the population.

In the third part we present our ongoing work.We focus on two main topics: (i) in the absence of seasonality, the endemic(and unique) equilibrium point undergoes supercritical and subcritical Hopfbifurcations; (ii) in the presence of seasonality, we conjecture that, via thetorus breakdown theory, the system exhibits chaotic dynamics.

In the fourth and final part, we present arecent model describing the coinfection dynamics of HIV and SARS-CoV-2 underhighly active antiretroviral therapy (HAART). Unlike previous models, ourformulation incorporates the effect of HAART on both infections. We derive thebasic reproduction numbers for each virus and show that transcriticalbifurcations occur when these values cross the threshold of one. We alsoestablish stability conditions for the disease-free equilibria. Numericalsimulations reveal that HAART, although targeting HIV, may also reduceSARS-CoV-2 proliferation in coinfected individuals -- suggesting a potentialindirect benefit not widely addressed in the existing literature.

This is joint work with Professor Alexandre Rodrigues (ISEG).

Room 1, Building XI
 
Abstract:
In 2022, East and Ruškuc published the congruence lattice of the infinite twisted partition monoid. As a by product, they established the congruence lattices of the finite $d$-twisted partition monoids. This talk is a first step in adapting the work of East and Ruškuc to the setting of the Brauer and Temperley-Lieb monoid. Specifically, it presents the newly established congruence lattice of the $0$-twisted Brauer and Temperley-Lieb monoids. With simple to grasp visual multiplication and applications in theoretical physics and representation theory, the family of diagram monoids are of particular interest to a number of fields as well are of stand alone interest.

Statistics and Risk Management Seminar & Thematic Line MatHBioS (Mathematics for Health and BioSciences)

Department of Mathematics, NOVA MATH/FCT NOVA

Title: Remodelling Selection to overcome Selective Depletion Biases

Speaker: Gabriela Gomes, University of Strathclyde and NOVA Math

Date | Time: July 10, 2025 | 14:30

Location: VIII-3.4

Abstract: Every population consists of individuals that vary in many traits, and each trait may or may not be associated with fitness. Variation in fitness traits lends population studies prone to selective depletion biases. When an ageing cohort exhibits declining mortality, it could be individuals becoming healthier or selective depletion of the frail. In an epidemic, when growth in cumulative infections decelerates, it could be individuals cautiously changing behaviour or selective depletion of the most susceptible. In microbial populations, when an isogenic population is stressed by antimicrobial treatment and some cells survive, this could be due to individual cells switching between normal and persister phenotypes or antibiotic selectively killing cells that divide faster. In each case, the first explanation invokes individuals changing (1), while the second posits selection on pre-existing variation changing (2). While explanations of type (1) are intuitive and widely adopted, those of type (2) are more neutral and rarely considered due to cognitive biases and challenges in estimating all variation that matters. While both are plausibly operating in most real systems, neglect of (2) leads to over-attribution of results to (1), wrong predictions, bad policy decisions and poor reproducibility, negatively impacting science, economics and ethics. To overcome this selective depletion bias, I have been proposing a pragmatic approach to study design and analysis whereby we infer distributions of characteristics that respond to selection and reframe theories accordingly. The approach is based on remodelling selection (mathematically by introducing key parametric distributions into population dynamic models, and empirically by measuring quantities of interest along selection gradients) and statistical inference (by fitting mathematical models to data). The procedure is being tested in systems where trait distributions can be inferred from population trends as well as reconstructed directly from individual measurements. Results of this ongoing research will be presented, and the wider applicability discussed. 
Prospects for conducting some of this research at NOVA School of Science and Technology are being assessed. Please join the discussion if you find the topic interesting…

Short Bio: Gabriela Gomes graduated in Applied Mathematics from the University of Porto in 1987 and completed her MSc and PhD in Mathematics from the University of Warwick in 1990 and 1993, respectively. In 1999, she switched to biology with a Wellcome Research Training Fellowship in Mathematical Biology. In 2002, she established an independent research group at the Gulbenkian Science Institute (IGC), initially supported by a Marie Curie Excellence Grant, with a spectrum of projects ranging from fundamental mathematical concepts to the management of population and ecosystem health, public engagement in science and development of research infrastructures. She subsequently led research programmes in the Research Centre for Biodiversity and Genetic Resources (CIBIO-InBIO), the Liverpool School of Tropical Medicine (LSTM), and is now a Professor of Mathematics and Statistics at the University of Strathclyde. Gabriela in a member of NOVA Math since 2023 where she leads the participation of the centre in the European project Inno4Vac (Innovations to accelerate vaccine development and manufacture).

Gabriela Gomes has published around 100 peer-reviewed research papers in international journals, initially in Mathematics and Physics and later in Biology, Ecology and Epidemiology. She has been a member of Editorial Boards for Nature Scientific Reports, Journal of Mathematical Biology and Journal of Theoretical Biology, and integrated the Board of Directors of the Portuguese Mathematical Society twice. She held various visiting positions in the USA and Brazil and is a Fellow of the Institute of Mathematics and its Applications (FIMA) in the UK.

Organizers: Isabel Natário and Paula Patrício

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This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 (https://doi.org/10.54499/UIDB/00297/2020) and UIDP/00297/2020 (https://doi.org/10.54499/UIDP/00297/2020) (Center for Mathematics and Applications)

Room 1, Building XI
 
Abstract:
We provide a brief introduction to (C1,C2)-clonoids, which are sets of functions of several arguments closed under right composition with a clone C1 and under left composition with another clone C2. Our primary focus is on clonoids of Boolean functions, and we present classifications of (C1,C2)-clonoids in the spirit of Post's classification of clones. Moreover, we propose refinements and strengthenings to Sparks's theorem on the cardinalities of clonoid lattices.

Statistics and Risk Management Seminar

Department of Mathematics, NOVA MATH/FCT NOVA

Title: Exploring Household Income in EU Countries: A Three-Parameter Distribution Perspective

Speaker: Kamila Trzcińska, University of University of Lodz, Poland

Date | Time: July 24, 2025 | 14:00

Location: VIII-3.4

Abstract: Household income is a key economic variable that reflects the living standards and material well-being of different social groups. Understanding its distribution is essential for analyzing inequality and economic structure. This study applies three-parameter income distribution models, known for their flexibility and strong statistical properties, to data from EU countries.The focus is on evaluating how well these theoretical models, including the Zenga distribution (2010), approximate empirical income data. The goodness of fit is assessed using measures such as the coefficient of similarity, the Mortara index, and a newly proposed metric based on the comparison of empirical and theoretical cumulative distribution functions. Additionally, basic statistical characteristics derived from the models are compared with their empirical counterparts.

Short Bio: Kamila Trzcińska is Assistant Professor at the Faculty of Economics and Sociology, University of Lodz. Her academic work focuses on the statistical analysis of income and wealth distributions, with particular emphasis on measuring and understanding income inequality, poverty, and the concentration of wealth among households. She conducts in both theoretical and applied research, contributing to the broader discussion on socio-economic disparities and their quantitative assessment. Her studies explore statistical tools to analyze income dynamics and economic well-being.

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Organizers: Isabel Natário and Mina Norouzirad and Frederico Caeiro

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This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 (https://doi.org/10.54499/UIDB/00297/2020) and UIDP/00297/2020 (https://doi.org/10.54499/UIDP/00297/2020) (Center for Mathematics and Applications)

Statistics and Risk Management Seminar

Department of Mathematics, NOVA MATH/FCT NOVA

Title: Ambiguity When Comparing Brands: Caution and Monopolistic Competition

Speaker: Jaime Velasco Sanchez, PhD at the University of Surrey, United Kingdom

Date | Time: September 4, 2025 | 15:00

Location: To be announced

Abstract: When consumers are not sure how to compare brands, caution creates monopolistic competition. This is addressed by looking at an exchange economy with countably many differentiated goods and analyzing the price impact of a coalition of countably many agents withholding their endowments. Such impact persists even when making the coalition smaller and smaller.

Organizers: Isabel Natário and Mina Norouzirad and Marta Faias

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This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 (https://doi.org/10.54499/UIDB/00297/2020) and UIDP/00297/2020 (https://doi.org/10.54499/UIDP/00297/2020) (Center for Mathematics and Applications)

Statistics and Risk Management Seminar

Department of Mathematics, NOVA MATH/FCT NOVA

Title: Directional Statistics in modelling high volatility

Speaker: Ashis SenGupta, CSIR Emeritus Scientist, Govt of India; Augusta University, Georgia, USA; METU, Turkey

Date | Time: September 18, 2025 | 14:30

Location: To be announced

Teams: https://www.google.com/url?q=https://teams.microsoft.com/l/meetup-join/19%253ameeting_NDJjM2M4YzYtZTNhMC00OGJiLThiYmYtOGMwMGI5MWY5OTMx%2540thread.v2/0?context%3D%257b%2522Tid%2522%253a%2522ae7e50a2-ed26-41f7-bd75-f49683f2433a%2522%252c%2522Oid%2522%253a%25224fb0e073-941c-4a18-993a-8d7d76f8978e%2522%257d%26launchAgent%3DGSuiteAddOn%26correlationId%3D41bdd273-e8bf-4abd-b9ce-a371e68581bc&sa=D&source=calendar&usg=AOvVaw0cnzRZzZVob8K6dY8HOBr8

Abstract: Modern data in many areas of applied science are characterized by high volatility, e.g. long tails as well as high kurtosis or peakedness. They also exhibit asymmetry and multimodality. Classical families of distributions with well-defined probability density functions are inadequate to model such data. On the other hand, families that may be good contenders for modelling high volatility do not in general admit probability density functions on the Euclidean manifold. But these families often can be mapped onto non-Euclidean manifolds, through deep results involving characteristic functions, for which the densities can have elegant Fourier series representations. This connection also immensely helps in statistical inference for the associated parameters. Also, on their own these families provide ample flexibilities in modelling data on non-Euclidean manifolds. We first develop the related theories for deriving these highly flexible families. Next, optimal inference procedures are outlined. Finally, emerging real-life examples from both Euclidean and non-Euclidean manifolds are presented to illustratethe results.

Short Bio: Professor Ashis Sengupta holds a Ph.D. from Ohio State University, under the supervision of Professor C. R. Rao. He advised 17 Ph.G. students in India, turkey and USA and he has more than 120 publications, including 12 books and volumes in Multivariate Analysis, Directional Statistics, Statistical Machine Learning, Financial Statistics and Reliability Inference. He is an Emeritus Scientist at the Indian Institute of Technology, Kharagpur, Advisor/Consultant at the Indian Statistical Institute, Adjunct Professor at Augusta University, Georgia, USA, a Distinguished Professor at the Middle East Technical University in Turkey and an Advisor at Analythium, Canada. He was a Visiting Professor in several Universities, including Stanford University, University of California-Santa Barbara and Riverside, University of Wisconsin-Madison, University of Missouri- Columbia, Michigan State University, Concordia University, Institute of Statistical Mathematics and Keio University (Japan), Haceteppe University (Turkey), University of Malaya (Malaysia), Daegu University (South Korea), Academia Sinica (Republic of China), as well as other Universities in Canada, Belgium, Sweden, Germany and Israel. He is an ex Editor-in-Chief of Environmental and Ecological Statistics (Springer, USA), and of the Journal of the Indian Society for Probability and Statistics and an Associate Editor for the Book series of the Forum of International Mathematics, Springer. He visited mainland China as Citizen Ambassador from American Statistical Association and is the recipient of several International and National recognitions, including 2 Lifetime Achievements and Distinguished Statistician Awards. He was elected President of the Mathematical Sciences section of the Indian Science Congress in 2011-2012 and he is an Elected Member of the International Statistical Institute, Fellow of the National Academy of Sciences, India and, of the Indian Society for Probability and Statistics and of the American Statistical Association – currently the only working statistician in India with this recognition. 

Organizers: Isabel Natário and Mina Norouzirad and Carlos Agra Coelho

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This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 (https://doi.org/10.54499/UIDB/00297/2020) and UIDP/00297/2020 (https://doi.org/10.54499/UIDP/00297/2020) (Center for Mathematics and Applications)

In recent decades, differential equations with nonstandard growth conditions have attracted increasing attention from researchers. Such problems arise in various branches of applied mathematics and physics, including image restoration and digital processing, electrorheological or thermo-rheological fluid flows, and elasticity. At the intersection of these areas lies the study of problems involving the p(x)-bilaplacian operator. In this seminar, we investigate a parabolic partial differential equation with the p(x)-bilaplacian operator. By performing a change of variables, the original problem is reformulated as a system of two second-order equations. We discretize this system with respect to the variables t and x, leading to the semidiscrete and discrete problems, respectively. We establish existence, uniqueness, and a priori estimates for both the semidiscrete and the discrete solutions. Furthermore, we prove that the resulting system of second-order equations admits a unique weak solution. A detailed study of the convergence order of the semidiscrete and discrete solutions toward the weak solution is also presented. Finally, we present numerical examples in one-dimensional and two-dimensional spatial domains using MATLAB software.

My talk is about the effects of small-scale turbulence on large-scale motion by using a stochastic scaling and singular limits. Many works have been done in recent years using the scaling limit in both scalar and vector cases. The second one is characterized by the presence of stretching, which is  an incremental detail over the scalar case. Our (with F. Flandoli) aim in [arXiv:2410.00520] is to understand the stretching mechanism of stochastic models of turbulence acting on a simple model of polymer. Namely, we investigate a scaling limit problem, under suitable intensity assumption. The polymer density equation, initially an SPDE converges (in the first step) weakly to a limit deterministic equation with a new degenerate term with some singular parameter. Recently, in [arXiv:2503.18143] we investigate the singular limit in the spirit of the hydrodynamic limit techniques. One consequence is that the limiting density shows a power-law decay in the polymer length, which is consistent with physical predictions.

The activities mentioned herein were performed in the framework of the project: EU-HORIZON EUROPE ERC-2021-ADG "Noise in Fluids" (NoisyFluid), no. 101053472

This talk provides an overview of Evolutionarily Stable Strategies (ESS) in population games and addresses some common misconceptions found in the classical literature. We focus specifically on Locally Superior Strategies (LSS), which represent a very special case of ESS, examining them in contexts with both finite and infinite action sets. Locally Superior Strategies are particularly significant among evolutionary stability concepts because they act as attractors under the Replicator Dynamic. The main result I will present unifies the finite and infinite frameworks by establishing a necessary and sufficient condition for an ESS to be a LSS.

We have been studying compartmental models of infectious disease spread, considering voluntary vaccination. The law governing the dynamics of voluntary vaccination is defined such that each individual chooses whether or not to be vaccinated, influenced by their perception of the choices of other individuals and the state of the disease in the system. This is known in the literature as imitation dynamics. I will present a simple model that explains the main ideas behind the construction of this type of model. The use of imitation dynamics in this model led to the emergence of chaotic behavior. I will also present two other models, one with an age structure and the other with loss of immunity.

Free transmission problems form a class of free boundary problems in which the solution-dependent discontinuity occurs at the level of the operator. Arising naturally in the modelling of heterogeneous diffusion and related processes, these problems present genuine mathematical difficulties, especially in the fully nonlinear setting. I will discuss recent progress on the existence of viscosity solutions and on their optimal regularity, both in the interior and up to the (fixed and free) boundary. I also plan to mention a few results on the development of numerical schemes tailored to this class of problems. Time permitting, I will conclude with a selection of open questions and possible directions for future research.

Speaker: Prof. Marta Gomes, Instituto Superior Técnico, University of Lisbon

Date | Time: December 5, 2025 | 14h30

Place:NOVA FCT, Departamento de Informática , sala232

Title: Spatialmulti-criteria decision analysis for rehabilitation priority ranking: acollaborative application to heritage workforce housing sites ( Co-authors: AnaPaula Falcão, Rita Machete, Alexandre B. Gonçalves )

Abstract: This workpresents a methodology to rank heritage sites regardingrehabilitation,considering both the characteristics of building sites and ofthe urban environment in the surrounding area. The objective is to aid thedecision process of building rehabilitation byranking the sites according totheir potential for re-emergence in the affordable housing rental market. Thedeveloped methodology is based on a combination of multi-criteria decisionanalysis (MCDA) and spatial analysis of geographical data, in order toconstruct an index, the “rehabilitation potential”, which is understandable byrehabilitation technicians and land managers and is applicable to support a listof priorities of building rehabilitation interventions. The methodology wasapplied to a case study consisting of aset of 33 heritage sites of theworkforce housing typology in Lisbon. These were built in the early industrialage in Portugal and are owned by the city municipality. The application ofMCDAwas a collaborative process that brought together the expertise of the academyand of the public administration. The results included a sensitivity analysisand gave form to a recommendation of five sites, selected from the totalworkforce housing set, to be rehabilitated in the near future.

Short bio: Prof. Marta Gomes is anAssistant Professor at Instituto Superior Técnico (IST), Department of CivilEngineering, Architecture and Environment, and a researcher at CERIS. She holdsa PhD in Systems Engineering (2007) from IST and has extensive expertise inoperations research, optimization, discrete-event simulation, multi-criteriadecision analysis, and large-scale data analytics, with applications acrosscivil engineering, industrial engineering, mechanical and aerospace systems.Her career includes a strong record of publications and collaborative research projects inmaintenance optimization, transport systems, pavement engineering, and urbanand environmental planning. 

MatHBioS Workshop

Title: Initiation to Neural Networks with PyTorch.

Speaker: Prof. Hamza El Mahjour (Abdelmalek Essaâdi University, MA).

Date: December 9, 2025 | from 10:00 to 12:00 and from 14:30 to 15:30.
          December 10, 2025 | from 10:00 to 12:00.
          December 11, 2025 | from 14:30 to 15:30.

Place: Room 2.23 - Building IX.

Abstract: This training is designed for PhD students with prior Python experience. It is a five-hour workshop that introduces participants to the practical implementation of neural networks using PyTorch, with a strong emphasis on hands-on coding and real-time model development. Designed for those already familiar with Python, the sessions will guide you from foundational concepts to building, training, and evaluating deep learning models. Through interactive exercises, participants will gain confidence in using PyTorch as a flexible and powerful framework for research applications.

*Those who are interested are invited to complete the form at this link: (https://docs.google.com/forms/d/e/1FAIpQLSckWV1aZjUmXXaW8xieqpTDuxkQSl74OqzZM6cmgQvWWeqdkw/viewform?pli=1)

In this talk, we revisit compartmental models, given by systems of ordinary differential equations, that describe the transmission dynamics of specific infectious diseases. These models are then generalized through hybrid frameworks and complex networks, enabling their application to a large number of evolution problems in fields such as sociology, economics, geography and epidemiology. Optimal control methods are applied to these models and complex networks aiming to mitigate epidemic outbreaks. In the second part of the talk, we propose a controlled complex network of Lotka-Volterra systems, where the strength of the migrations of biological populations are represented by control functions, reproducing the implementation of ecological corridors. We establish synchronization-type results, and the solutions to the optimal control problems demonstrate the potential to restore biodiversity in heterogeneous habitats. This is achieved by reaching either a global coexistence equilibrium or, in a more favorable scenario, a global limit cycle-ensuring sustained biological oscillations and vibrant ecological dynamics.