PhD Defense in Informatics Engineering (ProDEI): ”Time-To-Event Prediction”

Candidate
Maria José Gomes Pedroto

Date, Time and Location
July 22, 10:00, Sala de Atos of FEUP

President of the Jury
Carlos Miguel Ferraz Baquero-Moreno (PhD), Full Professor, Faculdade de Engenharia, Universidade do Porto

Members
Myra Spiliopoulou (PhD), Full Professor of Business Information Systems da Faculty of Computer Science da Otto-von-Guericke-University Magdeburg, Alemanha;
Manuel Filipe Vieira Torres dos Santos (PhD), Associate Professor with Habilitation, Department of Information Systems, Escola de Engenharia, Universidade do Minho;
Alípio Mário Guedes Jorge (PhD), Full Professor, Department of Computer Science, Faculdade de Ciências, Universidade do Porto (Supervisor);
Rui Carlos Camacho de Sousa Ferreira da Silva (PhD), Associate Professor, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto.

The thesis was co-supervised by João Pedro Carvalho Leal Mendes Moreira (PhD), Associate Professor in the Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto.

Abstract

This work is centered on modeling and predicting Time-to-Event (TTE) episodes, and has two distinct purposes. The first purpose is to explore the usage of genealogical data for time to event prediction. Additionally, this work aims to aid medical professionals in improving the diagnosis and prognosis of patients afflicted with Hereditary Transthyretin Amyloidosis (ATTRv amyloidosis). This is a genetic disease with a strong historical background in the fishing villages of Póvoa do Varzim, northern Portugal. In order to explore the value of genealogical data for time-to-event prediction, this work has contributions in feature engineering, namely within the area of feature construction and selection. To this end, it explores and compares a summarizing approach focused on manually extracting meaningful features from genealogical trees with a more automated one using embeddings. It contributes to model construction by creating a multivariate data-oriented approach that tracks a patient’s risk of developing disease onset through different ages. It also explores the impact of combining different age models of neighboring time windows. Finally, it contributes to model evaluation by addressing the implementation issues of a business based

approach to evaluate the expected return of changing clinical guidelines. It also presents robust evaluation schemas that assist the multivariate data-oriented approach in selecting the best model. The application is focused on patients with ATTRv Amyloidosis. To present and characterize the work done, this thesis is structured into four main sections. It begins with an introduction and a presentation of ATTRv Amyloidosis from a medically historic perspective. Then it presents the relevant background by dwelling into the connection of time to event prediction with feature engineering, model construction and model evaluation, as well as introducing key concepts of genealogical studies. After this, it presents its technical contributions, in the form of the main publications that constitute this work (one paper by chapter). It ends with an epilogue section which overviews the work performed, shares the main conclusions, and, finally, discusses the thesis from a technical and clinical perspective.

Keywords: Time-to-Event Data; Data Modeling; Regression Models

PhD Defense in Informatics Engineering: ”Symmetry, hierarchical structures and shallow neural networks: Advancing reinforcement learning for humanoids”

Candidate:
Miguel António Mourão de Abreu

Date, Time and Location
July 19, 15:00, room Professor Joaquim Sarmento (G129), DEC, Faculdade de Engenharia da Universidade do Porto

President of the Jury:
Rui Filipe Lima Maranhão de Abreu, PhD, Full Professor, Faculdade de Engenharia, Universidade do Porto

Members:
Francisco António Chaves Saraiva de Melo, PhD, Associate Professor with Habilitation, Department of Computer Science and Engineering, Instituto Superior Técnico, Universidade de Lisboa;
Carlos Fernando da Silva Ramos, PhD, Full Professor, Department of Informatics Engineering, Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto;
Abbas Abdolmaleki, PhD, Senior Scientist at Google DeepMind;
Luís Paulo Gonçalves dos Reis, PhD, Associate Professor with Habilitation, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto (Supervisor);
Henrique Daniel de Avelar Lopes Cardoso, PhD, Associate Professor, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto;
Armando Jorge Miranda de Sousa, PhD, Associate Professor, Department of Electrical and Computer Engineering, Faculdade de Engenharia, Universidade do Porto.

The thesis was co-supervised by José Nuno Panelas Nunes Lau, PhD, Associate Professor in the Department of Electronics, Telecommunications and Informatics at the Universidade de Aveiro.

Abstract:
In the rapidly evolving field of robotics, reinforcement learning (RL) has become an essential tool. However, as tasks become more complex, traditional RL methods face challenges in terms of sample efficiency, inter-task coordination, stability, and overall solution quality. To address this problem, we investigated various strategies. Initially, we explored ways of enriching the state space while learning skills from scratch with RL, resulting in excellent individual behaviors. However, integrating these behaviors proved challenging, as they often explored the vast action space in a non-structured manner. To address this, we shifted to a structured approach, starting by abstracting the robot’s locomotion model with an analytical controller, and improving the upper body efficiency.
Gradually, the learning component was extended to the entire robot, making the analytical controller a starting point in the learning process, rather than a restriction. We studied realistic external perturbations and ways of leveraging the robot’s symmetry to speed up the optimization. This led to an extension to PPO’s objective function called Proximal Symmetry Loss, with which we created
a fully functional omnidirectional walk with push-recovery abilities. Building on this knowledge, we devised a new symmetry-enriched learning framework based on Skill-Set-Primitives — a novel hierarchical structure that captures commonalities across different skills, easing transitions. This framework simplified the policy into a shallow neural network, significantly improving sample efficiency and stability. Applying this framework, we completely redesigned our simulated soccer team, achieving cohesive high-quality behaviors that secured victory in the RoboCup World Championship in 2022 and 2023. This team included a new localization algorithm with unprecedented accuracy, custom algorithms for path planning, role management, teammate communication, and more. We released the codebase to the RoboCup community, offering a robust Python foundation for new teams. Our work received recognition in scientific challenges, earning awards for introducing
he league’s first running skill, pioneering an agile close control dribble, and developing the most accurate localization algorithm. The contributions extend beyond RoboCup with Adaptive Symmetry Learning, a method of leveraging symmetry  to improve sample efficiency, even in robots not perfectly symmetric by design or those with asymmetrical flaws. A natural next step is to assess how this approach could benefit real humanoid robots, which inherently have imperfections.

Keywords: Reinforcement Learning; Humanoid Robots; Symmetry; Locomotion; Skill-Set-Primitives; Hierarchical Structures; Shallow Neural Networks; RoboCup; Robotic Soccer.

PhD Defense in Digital Media: ”Unlocking the Virtual World: A study on the influence of multisensory stimuli on users’ emotional responses and vividness of mental imagery in the context of virtual tourism”

Candidate:
Mariana de Oliveira Magalhães

Date, Time and Location:
July 8, 10:00, Sala de Atos (I-105)  DEEC, FEUP

President of the Jury:
João Manuel Paiva Cardoso, PhD, Full Professor, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto.

Members:
Alfredo Manuel dos Santos Ferreira Júnior, PhD, Associate Professor, Departamento de Engenharia Informática, Instituto Superior Técnico da Universidade de Lisboa;
Maria Beatriz Alves de Sousa Santos, PhD, Associate Professor with habilitation, Departamento de Eletrónica, Telecomunicações e Informática, Universidade de Aveiro;
Mário Sérgio Carvalho Teixeira, PhD, Assistant Professor, Departamento de Economia, Sociologia e Gestão, Universidade de Trás-os-Montes e Alto Douro;
António Fernando Vasconcelos Cunha Castro Coelho, PhD, Associate Professor with habilitation, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto (Supervisor);
António Augusto de Sousa, PhD, Associate Professor, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto.

The thesis was co-supervised by Doutor Maximino Bessa, Associate Professor with Habilitation, Universidade de Trás-os-Montes e Alto Douro.

Abstract
This thesis aims to explore how multisensory experiences in virtual reality influence users’ emotional responses and the vividness of their mental imagery, focusing on the impact of the demographics of gender and age. This thesis is driven by the recent rapid development of virtual reality in tourism, characterized by increasingly immersive multisensory experiences. It addresses the knowledge gap related to the limited understanding of how multisensory stimuli impact users’ emotional responses and their mental imagery ability, considering the particular case of virtual tourism.
Two immersive virtual experiences were developed for this purpose. Multisensory combinations of visual, auditory, haptic, olfactory, and taste stimuli were strategically integrated at specific stages of the two experiments, after being previously validated in a focus group session. One of these virtual experiences included a scenario intended to elicit positive emotions in the user by resorting to a selection of pleasant multisensory stimuli, designated as the “positive IVE” (positive Immersive Virtual Environment). The other experience sought the contrary: to induce negative emotions in the user through a combination of unpleasant multisensory stimuli, which was labeled as the “negative IVE” (negative Immersive Virtual Environment). The basic combination of visual and auditory stimuli was consistently used during the entire experiment. Additional stimuli – taste, haptic, and smell – were introduced one by one, sequentially. Finally, all these stimuli were combined for a comprehensive experience. A between-subjects experimental design was developed to explore and compare the users’ emotional responses and vividness of visual imagery after each stimuli combination in the two virtual experiences, resorting to in-VR questionnaires for data collection. Key findings include the impact of different positive and negative multisensory stimuli combinations on the users’ emotional responses, and how they, in turn, influence mental imagery. This research further suggests an inverse relationship between the intensity of the user’s emotions and their mental imagery ability. Nevertheless, neither age nor gender was found to influence this relationship in either the positive or negative scenarios. Additionally, this investigation provides insights into the specific emotions triggered by the used multisensory stimuli combinations, addressing a need long identified by various researchers in the field. This thesis contributes to understanding multisensory stimuli in virtual reality, highlighting its potential for application in various fields. It provides insights for future research in creating user-centered virtual reality tourism applications and understanding individual differences.

Keywords: Multisensory Virtual Reality; Virtual Reality; Emotional Responses; Vividness of Mental Imagery; Virtual Tourism.

PhD Defense in Digital Media: ”Science Communication strategy inspired by transmedia: Involving scientists in a collaborative effort to communicate science through a video game”

Candidate
Diogo Fernandes Santos

Date, Time and Location  
June 25, 14:30, Sala de Atos FEUP

President of the Jury
António Fernando Vasconcelos Cunha Castro Coelho, PhD, Associate Professor with habilitation, Faculdade de Engenharia, Universidade do Porto.

Vogais
Lynn Rosalina Gama Alves, PhD, Associate Professor, Instituto de Humanidades, Artes e Ciências Professor Milton Santos, Universidade Federal da Bahia, Brasil;
António Maria Salvado Coxito Granado, PhD, Associate Professor, Departamento de Ciências da Comunicação, Faculdade de Ciências Sociais e Humanas, Universidade Nova de Lisboa;
Liliana Filipa Vale Costa, PhD, Associate Professor, Departamento de Comunicação e Arte, Universidade de Aveiro;
Cátia Ferreira, PhD, Assistant Professor, Faculdade de Ciências Humanas, Universidade Católica Portuguesa;
João Carlos de Matos Paiva, PhD, Associate Professor with Habilitation, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto;
Carla Susana Lopes Morais, PhD, Assistant Professor with Habilitation, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto (Supervisor).

The thesis was co-supervised by Professor Nelson Troca Zagalo, Full Professor at the Universidade de Aveiro.

Abstract
The adoption of multimedia tools and objects came with challenges and opportunities for everyone involved in science communication and science learning initiatives. People interacting with the content, with the producer, or even the transformation of the consumer in a producer. Participation and dialogue become staples in science communication, with scientists and research units having to embrace this brave, but not so new world. In this experience, transmedia served as a guideline to think about science communication from within a research unit in the multimedia space.
In this work that was designed within Chemistry Research Unit of University of Porto (CIQUP) and shaped by ideas like participation, collaboration, dialogue, and interactivity, scientists were invited to co-create a fun serious video game to communicate their science (nanoparticles for drug delivery). To combine a serious portrait of science with fun elements that are typical of games, scientists were crucial to define theme, systems, mechanics, and narrative. It was developed a prototype (Nano Entregas) aimed to communicate about nanoparticles for drug delivery. The prototype was played by 170 participants from the 7th to the 11th school level in an experience aimed to measure the potential of the tool in two domains: as a science communication object capable of transmitting knowledge about nanoparticles and other scientific concepts associated with the subject; and as a game. To do so, data was collected through the implementation of a questionnaire and through the application of a serious game evaluation scale. The video game was also played by researchers and chemistry teachers, from whom observations were collected. Before the core gaming experience, the prototype was tested with the target audience (27 of the 170 participants), and three participants with no previous connection with the project (one teacher, one researcher, and one doctor). The prototype developed has shown potential to be used in multiple scenarios (formal and informal) where nanoparticles can be a subject to present. Most players (from the 170 students) have captured the basic information that was delivered. One was the metaphor used to introduce the size of nanoparticles within the real world scale of things, with 66,5% of the participants being able to deduce it from the bits of dialogue between the in-game characters. The percentage of correct answers were also higher in the three scientific questions: 85,3%, 78,2%, and 58,2%, respectively. The prototype was well received by the audience, with the 11 Factors in the scale collecting positive notes. The experience shows that scientists are eager to collaborate in challenging and innovative strategies to communicate with the audience, with the metaphor that shaped the prototype in terms of theme, narrative, systems, and mechanics, emerging directly from their contribution. The prototype shows that science can be portraited with seriousness in a video game that aimed for fun. Dialogue can be key to quickly find a common ground between researchers and communicators or developers, which then can result in the development of engaging tools to communicate about complex topics. Younger generations understand video games’ language. And, through it, scientists, communicators, teachers, and parents, can present and share scientific knowledge in a fun and interactive learning exercise.

Keywords: science communication; game development; transmedia; research units; chemistry; nanoparticles.

PhD Defense in Digital Media: ”Playing Differently: Designing asymmetry in games”

Candidate
Abel João Gavinho Vaz Tavares Neto

Date, Time and Location
June 20, 14:30, Sala Professor Joaquim Sarmento (G129), DEC, FEUP

President of the Jury
António Fernando Vasconcelos Cunha Castro Coelho, PhD, Associate Professor with Habilitation, Departamento de Engenharia Informática, Faculdade de Engenharia da Universidade do Porto.

Members
Miguel Angel Sicart Vila, PhD, Full Professor, Digital Design Department da IT University of Copenhagen, Denmark;
Teresa Isabel Lopes Romão, PhD, Associate Professor, Departamento de Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa;
Nelson Troca Zagalo, PhD, Full Professor, Departamento de Comunicação e Arte, Universidade de Aveiro;
Pedro Jorge Couto Cardoso, PhD, Assistant Professor, Departamento de Comunicação e Arte, Universidade de Aveiro (Supervisor);
Rui Pedro Amaral Rodrigues, PhD, Associate Professor, Departamento de Engenharia Informática, Faculdade de Engenharia da Universidade do Porto.

Abstract
Asymmetry is widely present in contemporary games, allowing players to enjoy different experiences by playing the same game through diverse perspectives or by assuming alternative player roles. However, both scholars and game designers tend to discuss asymmetry only in its most pronounced expressions and to ignore instances in which it plays a more nuanced role in diversifying gameplay experiences. In this research, we offer a holistic approach to asymmetry. Asymmetry Bricks is a conceptual framework for the analysis of asymmetry in games, in regard to the ways it can express itself and the mechanisms through which it can emerge during play. The framework also acts as a design tool to guide designers in the process of ideation of asymmetric gameplay mechanics.
The findings of this study aim to broaden discussions of asymmetry, offering a lens through which scholars can analyse it. The proposed terminology contributes to facilitating communication among game designers, players and other agents, while the design tool inspires all to explore asymmetry in new and interesting ways.

Keywords: Asymmetry; Asymmetric Gameplay; Gameplay Mechanics, Game Design.

PhD Defense in Digital Media: ”Mitigating Information Asymmetry in the 5G Era: unveiling practices that restrict users”

Candidate
Hermann Bergmann Garcia e Silva

Date, Time and Location
June 18, 10:30, Sala de Atos FEUP

President of the Jury
António Fernando Vasconcelos Cunha Castro Coelho, PhD, Associate Professor with Habilitation, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto.

Members
Rodrigo Moreno Marques, PhD, Adjunct Professor, Departamento de Teoria e Gestão da Informação, Escola de Ciência da Informação, Universidade Federal de Minas Gerais, Brasil;
Paulo Alexandre Ferreira Simões, PhD, Associate Professor, Departamento de Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade de Coimbra;
António Manuel Raminhos Cordeiro Grilo, PhD, Associate Professor, Departamento de Engenharia Eletrotécnica e de Computadores, Instituto Superior Técnico, Universidade de Lisboa;
Ana Cristina Costa Aguiar, PhD, Associate Professor with Habilitation, Departamento de Engenharia Eletrotécnica e de Computadores, Faculdade de Engenharia, Universidade do Porto;
Manuel Alberto Pereira Ricardo, PhD, Full Professor, Departamento de Engenharia Eletrotécnica e de Computadores, Faculdade de Engenharia, Universidade do Porto (Supervisor).

Abstract
Since John Barlow’s declaration of cyberspace independence over two decades ago, many transformations have unfolded in the digital ecosystem. The utopian vision of free space has given way to a reality where information flows are shaped by the Internet architecture, its communication protocols, and the intervention of network operators, which influence the behavior and autonomy of users.
Nowadays, the fifth generation of mobile communications systems (5G) materializes a programmable network that provides the flexibility and scalability required to handle the exponential growth of data traffic and the heterogeneity of use cases. Central to the 5G technology, network slicing introduces new traffic differentiation paradigms that segment users, applications, and services into customized logical domains with dedicated radio and computational resources.
This 5G feature potentially conflicts with the net neutrality principle, which seeks to ensure that Internet communications are treated in the same manner, without discrimination. In this context, it has become an issue of public interest to assess traffic differentiation mechanisms implemented by Internet service providers (ISPs) that could interfere with the flow of information and the freedom of choice in the virtual locus.
Thus, this study aims to characterize the practices employed by ISPs that discriminate Internet traffic, examine the regulations established to discipline these practices, discuss the net neutrality principle, and analyze the contradictory nature of network slicing and net neutrality. The first contribution of this thesis involves the portrayal of ISPs’ practices that restrict users’ Internet access to applications, services, and legal content. The second contribution showcases a comparative analysis of the regulations implemented to discipline these practices. The third contribution presents an innovative application of the standardized Network Data Analytics Function (NWDAF), designed to enable the evaluation of Internet Traffic Management Practices (ITMPs) through the controlled exposure of information to regulatory authorities. Via the NWDAF, regulators obtain direct and automated access to performance metrics in 5G networks.
As the methodological pathway, this study adopted an interdisciplinary approach, combining three dimensions of analysis: informational, technical, and legal. The results obtained show a divergence in regulating the zero-rating practice, indicate that net neutrality can be evaluated from an intra-slice perspective in 5G networks, and demonstrate the NWDAF’s ability to extract key performance indicators (KPIs). The NWDAF may be a relevant tool for improving network transparency and supporting regulatory oversight, which are indispensable elements to guarantee the coexistence of network slicing and net neutrality.

Keywords: Internet governance; Information policy; Net neutrality; 5G; Network slicing.

PhD Defense in Digital Media: ”Images as data and metadata: management practices to promote Findability, Accessibility, Interoperability and Reusability of research data”

Candidate
Joana Patrícia de Sousa Rodrigues

Date, Time and Location 
June 17, 14:00, Sala de Atos FEUP

President of the Jury
António Fernando Vasconcelos Cunha Castro Coelho, PhD, Associate Professor with Habilitation, Faculdade de Engenharia, Universidade do Porto.

 Members
Cláudia Maria Bauzer Medeiros, PhD, Professor, Departamento de Sistemas de Informação, Instituto de Computação, Universidade Estadual de Campinas, Brasil;
Maria Manuel Lopes de Figueiredo Costa Marques Borges, PhD, Associate Professor with Habilitation, Departamento de Filosofia, Comunicação e Informação, Faculdade de Letras, Universidade de Coimbra;
José Luís Brinquete Borbinha, PhD, Full Professor, Departamento de Informática do Instituto Superior Técnico da Universidade de Lisboa;
Cândida Fernanda Antunes Ribeiro, PhD, Full Professor, Departamento de Ciências da Comunicação e da Informação, Faculdade de Letras, Universidade do Porto;
Maria Cristina de Carvalho Alves Ribeiro, PhD, Associate Professor, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto;
Carla Alexandra Teixeira Lopes, PhD, Assistant Professor, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto (Supervisor).

Abstract
The evolution of the use and production of images is notorious. Technological development favors the emergence of images. This scenario is also applicable in the field of scientific research, where more and more instruments are used to facilitate image capture. With this context as a motto, and knowing that images have particular characteristics, this work explores the dynamics of images in research according to two scenarios: images as data and images as metadata. From a perspective of images as data, the aim is to understand how they can sufficiently represent the data obtained, favoring description. From the perspective of images as metadata, the aim is to understand how they can be used as a tool capable of faithfully describing a dataset and promoting its adequate contextualization and interpretation. Through exploratory research, several experiments with images as data and as metadata wereconducted, based on the dynamics and principles of Research Data Management (RDM). The work begins with an overview of the literature on the subject, in which the management of research data and its relationship with the use and production of images is explored, namely a study of the evolution of the image in the context of scientific, going through its challenges and opportunities, to the way it is treated by researchers, always with RDM as a guiding line. Subsequently, we move on to a view of the informational behavior of those who use and produce images in the context of research, namely in the search to identify behavior patterns in four studies. The first study starts from the perspective of a specific research project and the remaining three studies take a perspective that includes more stakeholders from different research domains. Thus, the scenarios of images as data and as metadata are explored, through the presentation of experiences that mostly involved researchers. For the case of images as data, four studies are presented, with specific contributions, starting with the proposal of a new metadata model for describing data in image format and their respective controlled vocabularies. The remaining three studies focus on automatic image processing, the publishing and sharing of data, and, finally, the definition of guidelines for using and producing images in the context of research. For the case of images as metadata, we conducted two studies, the first exposing a new perspective on data description, through the use of images as metadata. It is this new perspective that challenges us to take a new approach, which culminates in the second study, which is based on an experience developed with researchers and aims to alert and raise awareness of the use of other types of documents in the scientific process. This work has made it clear that images do not always have a formal, standardized role in research data management. However, researchers are open to including images more formally in the scientific process. Furthermore, it is clear that researchers can identify advantages in the use and production of images. The general trend of exponential growth in the production and use of images (motivated by technological developments and new sharing and dissemination tools) is also seen in the context of research, as the various participants in the studies carried out identified it as such, which points to an imminent need to make the role of images representative in the context of research data collection. The contributions obtained from this work are reflected in the response to the need for including images in the RDM. Starting from a more conceptual approach, a consistent overview was obtained about the habits of those who use and produce images through the analysis carried out in the literature, namely through the systematic review carried out and which includes several analysis variables, up to studies carried out through questionnaires and surveys and which allowed direct contact with researchers, thus allowing us to relate what theory tells us with what practice does. In the context of images as data, the metadata model and controlled vocabularies are a significant contribution, as they explore new possibilities of description, much more focused on the type of data in question (images). Furthermore, studies of sharing platforms, as well as the possibilities of automatic description of images, made it possible to generate a starting point and determine the path to follow. Still, in the context of images, it is important to highlight the guidelines for the use and production of images that appear as a contribution to the scientific community, in the sense that they guide specific image practices and needs. In the context of images as metadata, the great contribution lies, precisely, in the presentation of an innovative approach to data description, where the particular characteristics that images have are highlighted and that position them as allies of researchers in the data description process and present practical examples of how this description through images could occur.

Keywords: Image; Image as Data; Image as Metadata; Information Behavior; Research Data; Management.

PhD Defense in Digital Media: ”Narratives of Our Age: Intergenerational Digital Storytelling and Cultural Identity”

Candidate
Juliana Carolina Campos Monteiro

Date, Time and Location 
June 4, 14h30, Room Professor Joaquim Sarmento (G129), DEC, FEUP

President of the Jury
António Fernando Vasconcelos Cunha Castro Coelho, PhD, Associate Professor with Habilitation, Faculdade de Engenharia, Universidade do Porto.

Members
Paulo Nuno Gouveia Vicente, PhD, Associate Professor, Departamento de Ciências da Comunicação, Faculdade de Ciências Sociais e Humanas, Universidade Nova de Lisboa;
Daniel da Cruz Brandão, PhD, Assistant Professor, Departamento de Ciências da Comunicação, Instituto de Ciências Sociais, Universidade do Minho;
Teresa Margarida Loureiro Cardoso, PhD, Assistant Professor, Departamento de Educação e Ensino à Distância, Universidade Aberta;
Dinis Miguel de Almeida Cayolla Ribeiro, PhD, Assistant Professor, Departamento de Ciências da Arte e do Design, Faculdade de Belas Artes, Universidade do Porto;
Carla Susana Lopes Morais, PhD, Assistant Professor, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto (Supervisor).

Abstract
The expansion of digital tools and participatory media created unprecedented possibilities for the maintenance and sharing of social memory and cultural identity knowledge. These possibilities are expanding in parallel with a context of an increasingly aged society, where elders are privileged keepers of regional cultural knowledge but often don’t have the opportunity to pass it on to future generations, making it prone to shortly disappear. This research approaches digital storytelling during intergenerational exchanges as a stage for a participatory contribution to the maintenance of cultural identity. We sought to determine how intergenerational dynamics can give place to cultural identity narratives, as well as how digital media can support the maintenance of cultural identity. For that purpose, we promoted the project NOOA: Narratives Of Our Age, with the premise of bringing generations together in sharing stories on topics such as Memories, Crafts, Myths, and Traditions, to endorse the continuity of the cultural identity of the Vale do Sousa region, using the potential of digital media in this process. With an action research design and an ethnographic approach, from 2018 to 2021, this project reunited three intergenerational groups, composed of participants aged 16 to 85 years old, in a set of activities designed to foster intergenerational dynamics. We sought to gather qualitative perceptions about the phenomenon of storytelling in the participatory maintenance of cultural identity through intergenerational dynamics. To this end, our research was based on data collected through detailed observations and through the application of semi-structured interviews and group discussions. We developed a five-step intergenerational storytelling framework to encourage the exchange of cultural identity knowledge, including digital registration, dissemination, and discussion in-person and online. This framework was submitted to a cyclical evaluation and its adjustments, in accordance with the action-research method, and it was implemented in three phases: phase one corresponded to a group dynamic component, through brainstorming and story planning; phase two corresponded to the creation of digital stories; phase three corresponded to dissemination, with the publication and sharing of these stories in the project’s digital spaces. These steps were conducted through in-person digital storytelling activities, in which cultural identity knowledge was shared and discussed in intergenerational partnerships, resulting in the participatory creation of 35 digital stories, that were afterwards shared and also discussed on the Project’s digital spaces. The outcomes of the activities, as well the enthusiasm and the reflections that occurred during the process, highlight the investment of participants in the transmission and maintenance of knowledge related to their experiences and knowledge acquired throughout life, in a family and community context. The observations of intergenerational dynamics, as well as the results of the semi-structured interviews, suggested a growing curiosity, involvement and overall understanding and retention of the stories of cultural identity, by both seniors and juniors, as well as a growing curiosity of senior participants regarding the pervasive digital reality presented to them by the juniors. Likewise, we observed the importance of empowering groups with spaces of sharing, both face-to-face and online, to enhance intergenerational exchanges around the knowledge of cultural identity. By promoting opportunities for intergenerational dialogue and empowering groups with face-to-face and online sharing spaces, we contributed with the development and application of a storytelling framework and digital spaces to safeguard, discuss and disseminate some of the specific cultural knowledge of the region of Vale do Sousa in Portugal. We observed the potential of using digital storytelling dynamics to break through barriers of communication between generations and to perpetuate and value cultural identity knowledge, acquired throughout life. This research goes beyond the aim of documenting the envisaged cultural identity knowledge, by combining creativity during the digital storytelling processes with connectivity among the participants on a community level, by sparking the dialogue between generations and enhancing the social impact of cultural identity knowledge and the self-knowledge value that generations are able to share through stories. We examined the opportunities and challenges of digital media as a platform and a catalyst for cultural identity maintenance, situating the problematic of cultural literacy in a contemporary setting. We conducted a thorough assessment of the stakeholders involved in participatory cultural identity maintenance in our present context, adding the observation of their synergies in a real context. This allowed us to examine the diversity of outcomes and the multiplicity of variables that contribute to it, as well as to grasp the impact that this new information flow paradigm may have on how we currently approach cultural identity maintenance.

Keywords: Intergenerational Digital Storytelling, Cultural Identity, Cultural Literacy, Participatory Action-Research.

PhD Defense in Digital Media: ”Computing by going back in time: Composing video sequences through multimodal generative coordination”

Candidate:
Luís Henrique Pinto Arandas

Date, Time and Place:
June 03, 14:30, Sala de Atos FEUP

President of The Jury:
António Fernando Vasconcelos Cunha Castro Coelho, PhD, Associate Professor with Habilitation, Faculdade de Engenharia, Universidade do Porto.

Members:
Luísa Maria Lopes Ribas, PhD, Assistant Professor, Departamento de Design de Comunicação, Faculdade de Belas-Artes, Universidade de Lisboa;
David Fernandes Semedo, PhD, Assistant Professor, Departamento de Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa;
André Sier, PhD, Invited Assistant Professor, Departamento de Artes Visuais e Design, Universidade de Évora;
José Miguel Santos Araújo Carvalhais Fonseca, PhD, Full Professor, Faculdade de Belas Artes, Universidade do Porto (Supervisor);
Gilberto Bernardes de Almeida, PhD, Assistant Professor, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto.

The thesis was co-supervised by Professor Mick Grierson, Professor in Computing, and research leader at the Institute of Creative Computing at the University of the Arts, London.

Abstract
This project proposes a set of methods, inspired by the human experience of vision and time, for developing video sequences using trained generative models. The methods serve the production of video sequences, with patterns derived from trained models found in literature on metacreation and in the artworld. This project defines possible futures where the now pervasive generative models can be reused in computer simulations that focus on the human experience of video and mental images; models which, because of how they are trained through archives and records representing both the human and the physical world, can capture media themselves and represent specific moments in time.

The research outputs are in film and audiovisual installation, proposing that practice can further benefit from self-reference, using deep generative models as synthesisers of video, sound, and text. The methods produced take advantage of natural language guidance and deep generative models in ways that can be understood as sampling, sequencing, and translation, following computing literature and AI design. Each result can be understood in larger domains such as: 1) short films from text inputs, in the film Irreplaceable Biography; 2) discursive installations from video datasets, in the installation Time as meaning; and 3) short films from video inputs, in the film Man lost in the convergence of time and the collaboration all YIN no YANG. This research extends on the use of generative practice following a construct of language in the human mind, behaviour, and visual experience as inspiration for the experience of video. These projects further define what can be a broader understanding of directionality and representation of the past using systems of memory that learn, are networked and produced following structure found in nature and human experience.

Keywords: Video composition; Deep generative models; Time-travelling; Human visual experience; Predictive representations.

PhD Defense in Informatics Engineering: ”Enhancing Forecasting using Read & Write Recurrent Neural Networks”

Candidate
Yassine Baghoussi

Date, Time and Place
May 29, at 09:30, Sala de Atos FEUP

President of the Jury
Pedro Nuno Ferreira da Rosa da Cruz Diniz, PhD, Full Professor, Department of Informatics Engineering, Faculty of Engineering, University of Porto.

Members
Joydeep Chandra, Phd, Associate Professor, Department of Computer Science and Engineering, Indian Institute of Technology, Patna, Índia;
Mykola Pechenizkiy, PhD, Full Professor, Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands;
Luís Filipe Pinto de Almeida Teixeira, PhD, Associate Professor, Department of Informatics Engineering, Faculty of Engineering, University of Porto;
João Pedro Carvalho Leal Mendes Moreira, PhD, Associate Professor, Department of Informatics Engineering, University of Porto (Supervisor).

The thesis was co-supervised by Professor Carlos Manuel Milheiro de Oliveira Pinto Soares, Associate Professor at the Department of Informatics Engineering, University of Porto.

Abstract

“Machine Learning (ML) relies on both data and algorithms for optimal functioning. While conventional ML research often emphasizes algorithmic improvements, the significance of data processing is frequently overlooked. In contrast, preprocessing data stands as a distinct task, executed before feeding it into algorithms. The diversity of preprocessing methods tailored for various ML algorithms underscores its importance. However, the feedback loop between algorithms and data is often neglected. Data-related issues pose significant challenges for predictive ML algorithms, adversely affecting forecasting accuracy. These challenges arise because problems in data are inherently unpredictable, lacking a discernible pattern. In this doctoral thesis, we introduce Read and Write Machine Learning (RW-ML), an innovative paradigm enhancing time series forecasting accuracy by integrating data modification techniques into the learning process. The RW-LSTM, an adaptation of the backpropagation algorithm, unifies preprocessing with recurrent neural networks (RNNs), significantly outperforming traditional models such as LSTM. RW-LSTM enables the transition from read-only RNNs, which merely learn from data, to RW-ML, allowing direct alterations for improved predictions. Expanding the framework, the Corrector Long Short-Term Memory (cLSTM) addresses the limitations of read-only RNNs, demonstrating enhanced forecasting accuracy through empirical verification and extensive experiments. The final chapter provides a real-world evaluation, highlighting the competitive advantage of cLSTM over LSTM models in various scenarios.”

This research was carried out as part of SonaeIM.Lab@FEUP, involving Inovretail.