Category: News

  • Helena Moniz, INESC-ID Researcher was nominated President of the EAMT and Vice-President of the IAMT

    Helena Moniz, INESC-ID Researcher was nominated President of the EAMT and Vice-President of the IAMT

    Helena Moniz, INESC-ID Researcher was nominated President of the European Association for Machine Translation (EAMT) and Vice-President of the International Association for Machine Translation (IAMT).

    “I am humbly grateful for such an amazing committee consider me as one of them. It is a true honour and a responsibility. I surely hope I may assist the EAMT diverse community of translators, end users of Machine Translation, NLP scientists, and industry partners. The present offers great challenges and opportunities to our community. My motto has been the balance between AI technologies and the human factor and I believe this is very much needed in such exciting times for (M)T!”, mentioned Helena Moniz.

    Helena Moniz is an Assistant Professor at the School of Arts and Humanities at the University of Lisbon, where she teaches Computational Linguistics, Computer Assisted Translation, and Machine Translation Systems and Post-editing.

    She received a PhD in Linguistics at FLUL in cooperation with the Technical University of Lisbon (IST), in 2013. She has been working at INESC-ID/CLUL since 2000, in several national and international projects involving multidisciplinary teams of linguists, speech, and NLP scientists. Within this fruitful collaborations, she participated in 16 national and international projects.

    Since 2015-, She is also the PI of a Protocol between INESC-ID and Unbabel, a translation company combining AI + post-editing, working in AI Research Projects.

    She is currently the vice-coordinator of the Human Language Technologies Lab at INESC-ID and responsible for the WG3 of the COST Action Multi3Generation (CA18231).

  • 2021 European Researchers’ Night

    2021 European Researchers’ Night

    How can Science contribute to the knowledge about the causes and effects of climate change and to climate neutrality by 2050?

    The European Researchers’ Night is an initiative funded by the European Commission, through Marie Curie Actions, aiming to celebrate Science and reduce the gap between researchers and citizens. The European Researchers’ Night translates into a series of activities happening throughout the year culminating in a night of celebration of Science, taking place in several European cities.

     

    The European Researchers’ Night 2021 (ERN2021) will take place on 24th September across Europe. The consortium’s activities, such as lectures, workshops, among others, under the theme “Climate Science“, will take place from 4 p.m. to 11 p.m., in a hybrid format, i.e., with reduced face-to-face activities and a parallel programme fully online.

    INESC-ID will participate in the following activities:

    • “Understanding the risks is key to preparedness.” | Game, Apps and Challenges

    In this game we will help you understand warnings and how to be prepared and respond in case of earthquake and tsunami.

    Knowing the risks is essential to being prepared. In this game you will learn to know the alerts and what to do to be prepared and respond in case of earthquake and tsunami. It is intended to make the population aware of natural risks, namely seismic and tsunami risks, in order to increase the resilience of communities. Educating and informing about risk prevention and mitigation is essential for promoting a risk culture.

    Organised by: Instituto Superior Técnico /CERIS and INESC-ID

    Researcher: Mónica Amaral Ferreira

    Thematic area: Architecture, Art and Design, Natural and Environmental Sciences, Technology

    • “Do you know how satellites help to know how the weather’s like?”  | Quizzes

    The activity presents some of the methods used to assess the Earth’s climate based on satellite technology, and challenges the visitor to answer a quiz to test their knowledge.

    Organised by: INESC-ID

    Researcher: Rui Policarpo Duarte

    Thematic area: Technology.

     NEI2021 online programme  

    More information.

  • INESC-ID researchers awarded the INFORUM Award for Best student article

    INESC-ID researchers awarded the INFORUM Award for Best student article

    The article “Non-consensual cryptocurrencies at Ethereum” by researchers Paulo Silva, Miguel Matos and João Barreto was awarded the prize for Best Student Article.

    INFORUM – Symposium on Information Technology took place on 9 and 10 September 2021 at ISEL, in Lisbon.

    More information at https://inforum.org.pt/en/premios

     

     

     

    [PT]

    Investigadores do INESC-ID recebem Prémio INFORUM Melhor artigo de estudante

     

    O artigo “Consensusless cryptocurrencies in Ethereum” dos investigadores Paulo Silva, Miguel Matos e  João Barreto foi premiado com a galardão de Melhor artigo de estudante

    O INFORUM – Simpósio de Informática teve lugar a 9 e 10 de Setembro de 2021 no ISEL, em Lisboa.

    Mais informação em https://inforum.org.pt/en/premios

  • 3 INESC-ID researchers win Universidade de Lisboa/ Caixa Geral de Depósitos Scientific Awards

    3 INESC-ID researchers win Universidade de Lisboa/ Caixa Geral de Depósitos Scientific Awards

    3 INESC-ID researchers were recognised in the 2020 edition of Universidade de Lisboa/ Caixa Geral de Depósitos Scientific Awards (ULisboa/CGD Scientific Awards) . The awards ceremony took place on 26th July.

    Joaquim Jorge, researcher at INESC-ID and professor at the Department of Computer Science and Engineering (DEI) at Instituto Superior Técnico, received the award in Computer Science and Informatics Engineering scientific area.

    Leonel Sousa, researcher at INESC-ID and professor at Department of Electrical and Computer Engineering (DEEC), won an honourable mention, in Electrical Engineering and Aerospace Engineering (Avionics) scientific area.

    Rui Gameiro de Castro, professor at the Department of Electrical and Computer Engineering (DEEC) and researcher at INESC-ID, received an honourable mention in Environmental and Energy Engineering scientific area.

    The ULisboa/CGD Scientific Awards reward scientific research activity and encourage the practice of publishing in international journals of recognised quality. These awards consist of a diploma and a €6.500 cash prize.

    The CEO of CGD highlighted the importance of ULisboa in society and shared CGD’s willingness to continue supporting and investing in knowledge, particularly in universities. “We believe that the University, with its endless freedom of spirit, is an essential bulwark for knowledge dissemination”, he said.

    The ceremony is available on ULisboa YouTube channel.

    Source: Instituto Superior Técnico

  • ILU: A technology to help improve Urban Mobility

    ILU: A technology to help improve Urban Mobility

    INESC-ID is developing a project in partnership with National Civil Engineering Laboratory, Câmara Municipal de Lisboa (Lisbon Municipality), and the major public carriers in the Lisbon metropolitan area with the aim of aligning urban mobility plans with the emerging traffic dynamics.

    The ILU project (Integrative Learning from Urban Data and Situational Context for City Mobility Optimization) aims to improve mobility in Lisbon by analyzing heterogeneous sources of traffic data produced by ticketing systems, stationary road sensors, and mobile devices; therefore: 1) supporting the transparency of urban mobility plans to the citizen; 2) offering a solid ground for coordination efforts among municipalities and public transport operators; and 3) ensuring the public transport system responds to the ongoing city transformations and changes observed in a pandemic context.

    To this end, the ILU APP, a pioneer recommendation system that integrates the main computational contributions of the project, is being developed. ILU APP offers a multimodal, dynamic and context-sensitive analysis of urban traffic, combining five main features:

    • automatic consolidation of urban data sources from public transport operators and PGIL (platform for intelligent management in Lisbon) with potential impact on the city traffic analysis, with particular attention to the provision of: efficient cross-modal spatiotemporal queries, Big Data visualization utilities, dynamic updates, mappings into data structures conducive to the subsequent machine learning tasks, and the inference of incomplete traffic flows, including alighting stop estimates in the CARRIS network;
    • descriptive analytics for detecting vulnerabilities and ongoing changes to mobility in the city, focusing on:

    – statistically significant traffic patterns, including: (a) frequent and periodic patterns indicative of overcrowding or congestion; (b) emerging traffic patterns that may reveal future vulnerabilities; (c) deviant patterns including anomalous variations in demand; (d) multimodal traffic synergies; and (e) correlations present in multiple sources of urban traffic;

    – dynamic inference of multimodal origin-destination matrices, allowing the detection of vulnerabilities in the network, including transfer needs and long journey times;

    • predictive analytics of traffic flows from various data sources, using innovative associative learning and deep learning principles. The facilities are provided within a solid statistical frame, enabling forecasts of road traffic or demand on the public transport network to be made with guarantees of significance and variability;

     

    • analytics sensitive to different sources of situational context, in particular the extension of the previous description and forecasting facilities for the study of traffic dynamics in the presence of historical and prospective context, including: (a) planned events (such as sport matches and cultural events), (b) weather forecasts, and (c) interdictions on public roads;

     

    • optimization facilities based on the previous data-centric models of traffic for: (a) adjusting the public transportation network by revising vehicle routing and frequency; and (b) designing intelligent traffic light control systems at specific city junctures. In this context, the ILU project is combining control and micro-simulation principles with advances from deep reinforcement learning.

    The recommendation system will be delivered in the form of a functional prototype to the project’s public partners – CML, CARRIS and METRO – to support their: (a) strategic decisions related to the city mobility; and (b) real-time operational decisions, including the signaling of the ongoing vulnerabilities in the mobility system.

    These contributions are expected to reveal untapped multimodal synergies and promote a sustainable urban mobility, giving priority for public transport options and the integration of active travel modes. Moreover, the modular, dynamic, and online nature of the devised contributions ensures their interoperability and scalability to other cities in the current pandemic era.

     

     

    [pt]

    ILU: A tecnologia a contribuir para melhorar a Mobilidade Urbana

    O INESC-ID está a desenvolver um projeto em parceria com a Câmara Municipal de Lisboa e o Laboratório Nacional de Engenharia Civil que visa contribuir para melhorar a Mobilidade Urbana.

    O projeto iLU (Integrative Learning from Urban Data and Situational Context for City Mobility Optimization) visa melhorar a mobilidade em Lisboa a partir da análise de dados da circulação automóvel e de transportes públicos. Pretende-se descobrir padrões de circulação na cidade, antecipar problemas e fazer recomendações.

    O INESC-ID está a desenvolver um projeto em parceria com o Laboratório Nacional de Engenharia Civil, a Câmara Municipal de Lisboa, e transportadoras na área metropolitana de Lisboa com o objetivo de alinhar os planos de Mobilidade Urbana com as emergentes dinâmicas de tráfego.

    O projeto ILU (Integrative Learning from Urban Data and Situational Context for City Mobility Optimization) visa melhorar a mobilidade em Lisboa através da análise de dados de tráfego produzidos por sistemas de bilhetagem na rede de transportes públicos, sensores rodoviários estacionários, e dispositivos móveis; visando: 1) apoiar a transparência dos planos de mobilidade urbana para o cidadão; 2) fortalecer a coordenação entre municípios e operadoras de transporte público a partir das vistas centradas nos dados; e 3) garantir que o sistema de transporte público responde às transformações em curso na cidade e às mudanças estruturas observadas em contextos pandémicos.

    Para tal, foi desenvolvida a ILU APP, um sistema de recomendação pioneiro que integra as principais contribuições computacionais do projeto. A ILU APP oferece uma análise multimodal, dinâmica e sensível ao contexto do tráfego urbano, combinando cinco características principais:

    • consolidação automática de fontes de dados urbanos presentes nos operadores de transportes públicos e disponibilizados na PGIL (plataforma para gestão inteligente em Lisboa), tendo particular atenção à disponibilização de facilidades de visualização, procuras eficientes, atualização dinâmica dos dados, mapeamentos em estruturas de dados conducivas às subsequentes tarefas de aprendizagem, e à inferência de fluxos de tráfego incompletos, incluindo estimativas do desembarque por passageiro na rede CARRIS;

     

    • analítica descritiva para detectar vulnerabilidades e contínuas alterações à mobilidade na cidade, com foco em:

     

    – padrões de tráfego estatisticamente significativos, incluindo: (a) padrões frequentes e periódicos indicativos de congestionamento ou sobrelotação; (b) padrões emergentes capazes de antecipar vulnerabilidades futuras; (c) padrões desviantes incluindo variações anómalas na procura; (d) sinergias multimodais no tráfego; e (e) correlações presentes nas múltiplas fontes de tráfego urbano;

     

    – inferência dinâmica de matrizes de origem-destino multimodais, permitindo a detecção de vulnerabilidades na rede, incluindo necessidades de transbordo e durações elevadas de viagem;

     

    • análise preditiva de fluxos de tráfego a partir de várias fontes de dados, usando princípios inovadores de aprendizagem associativa e aprendizagem profunda. As facilidades disponibilizadas têm um enquadramento estatístico sólido, permitindo realizar previsões do tráfego rodoviário ou de procura na rede pública de transportes com garantias de significância e variabilidade;

     

    • análises sensíveis a diferentes fontes de contexto situacional, em particular estendo as anteriores facilidades de descrição e previsão para o estudo da dinâmicas de tráfego na presença de contexto histórico e prospectivo, incluindo: (a) eventos planeados (desportivos e culturais), (b) registos e previsões meteorológicas, e (c) interdições em vias públicas;

     

    • optimizadores com base nos modelos de tráfego centrados em dados anteriores para: (a) ajustar a rede de transporte público revendo o roteamento e a frequência dos veículos; e (b) desenhar sistemas de controle de semáforos inteligentes em cruzamentos específicos na cidade. Nesse contexto, o projeto ILU combina princípios de controlo e micro-simulação com avanços em aprendizagem profunda com reforço.

    O sistema de recomendação será entregue sob a forma de um protótipo funcional aos parceiros públicos do projeto – CML, CARRIS e METRO – por forma a apoiar: (a) decisões estratégicas ligadas ao planeamento da mobilidade na cidade; e (b) decisões operacionais em tempo real, incluindo a sinalização de vulnerabilidades ou necessidades de reforço à oferta.

    Esperamos que estas contribuições revelem sinergias multimodais desconhecidas, promovendo uma mobilidade urbana mais sustentável, prioritizando as opções de transporte público e a integração de meios de transporte ativo (mobilidade pedonal, cicloviável, e partilhada). Além disso, a natureza modular e dinâmica das contribuições garante a sua extensão a outras cidades de Portugal e no mundo.

  • H  |  Visions of the Future |  The first issue of the e-magazine of INESC Brussels HUB

    H | Visions of the Future | The first issue of the e-magazine of INESC Brussels HUB

    Discover our newest publication: Visions of the future, the first issue of the e-magazine of INESC Brussels HUB.

     

    It brings you fresh ideas on the most important issues in scientific research and technology today, together with the stories of those who will develop the technological innovations of tomorrow. It focuses on the stories and the projects of the people who work in INESC, and of INESC’s international present and potential partners.

     

    For this issue, we wanted to give our contribution to the Conference on the Future of Europe, through a thematic publication on the future of technology

     

    Learn about the new perspectives and challenges of artificial intelligence, robotics, telecommunications, the energy transition, health technologies, and more.

     

    Read here

     

  • INESC-ID researchers awarded ACM SIGSOFT Distinguished Paper

    INESC-ID researchers awarded ACM SIGSOFT Distinguished Paper

    A joint team of researchers including INESC-ID researchers Vasco Manquinho and Pedro Orvalho will receive an ACM (Association for Computing Machinery) SIGSOFT Distinguished Paper Award for their work on a new analysis engine for the popular Alloy modeling language.

    The paper “AlloyMax: Bringing Maximum Satisfaction to Relational  Specifications” has been chosen to receive an ACM SIGSOFT Distinguished Paper Award at  upcoming ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021).

    The team of authors is composed by Changjian Zhang (CMU), Ryan Wagner (CMU), Pedro Orvalho (INESC-ID/IST, Universidade de Lisboa), David Garlan (CMU), Vasco Manquinho (INESC-ID/IST, Universidade de Lisboa), Ruben Martins (CMU), and Eunsuk Kang (CMU).

    Distinguished papers are given to at most 10% of the papers accepted at  an ACM SIGSOFT-sponsored conference. The winners were chosen by the  program co-chairs from those papers that had either a nomination for  distinguished paper award, or at least two accept scores and no  negative scores.  In total eight papers were recognized this year.

    “The Alloy language is widely used in software engineering for verification, automatic generation of test cases, or security analysis. Considering that the software is currently pervasive on any device we use, some defects can result in serious failures in the operation and safety of the devices”, mentioned Vasco Manquinho.

    The work, in collaboration with the CMU team, extends the Alloy modeling language to enable the generation of optimal solutions according to a given optimization criterion. For example, it enables to obtain solutions that maximize the performance or security of systems. The INESC-ID research team has a long-term collaboration  with Prof. Rúben Martins (CMU) in the development of new  optimization algorithms using computational logic.

    “This distinction is important because it allows greater visibility to our work in the field of computational logic. Reality is demonstrating the importance of this area in numerous engineering contexts”, adds the INESC-ID researcher.

  • CIMPLE: Countering Creative Information Manipulation with Explainable AI

    CIMPLE: Countering Creative Information Manipulation with Explainable AI

    What’s the role that Artificial Intelligence can play in fighting misinformation?

    CIMPLE project aims to research and develop innovative social and knowledge driven creative AI
    explanations, and testing it in the domain of detection and tracking of manipulated information, while
    taking into account social, psychological, and technical explainability needs and requirements.

    “Our domain is the manipulation of information that we see on social media, in the news… it is about
    the dissemination of information or news that is factually wrong because it does not tell the truth or it has been manipulated, misleading the public”, mentioned  Sofia Pinto, the INESC-ID Researcher involved in the project.

    The CIMPLE project is all about Explainable Artificial Intelligence (XAI) requirements related to AI-driven misinformation detection, XAI by design using Knowledge Graphs and XAI models for detecting
    information manipulation. The Researchers involved aim to be able to generate creative and engaging
    explainability visualisations and personalize XAI to end-users skills and topic affinity.

     

    “INESC-ID’s role is to look for ways to explain the manipulation of information, in a way that the interlocutor has the ability to listen and to question himself. It is more than just presenting facts, as it is very difficult to convince someone else who believes something otherwise. And this is where creativity comes in. We are going to work on this explanation of manipulation using computational creativity to attract people’s attention, so that they can visualize where there was manipulation and so that they can reach to their own conclusions”, adds the researcher.

     

    Explainability is of significant importance in the move towards trusted, responsible and ethical AI, yet
    remains in its infancy. Most relevant efforts focus on the increased transparency of AI model design and
    training data, and on statistics-based interpretations of resulting decisions (interpretability).
    Explainability considers how AI can be understood by human users. The understandability of such
    explanations and their suitability to particular users and application domains received very little
    attention so far. Hence there is a need for an interdisciplinary and drastic evolution in XAI methods.

    CIMPLE will draw on models of human creativity, both in manipulating and understanding information,
    to design more understandable, reconfigurable and personalisable explanations. Human factors are key
    determinants of the success of relevant AI models. In some contexts, such as misinformation detection,
    existing XAI technical explainability methods do not suffice as the complexity of the domain and the
    variety of relevant social and psychological factors can heavily influence users’ trust in derived
    explanations.

    Past research has shown that presenting users with true / false credibility decisions is inadequate and
    ineffective, particularly when a black-box algorithm is used. Knowledge Graphs offer significant potential to better structure the core of AI models, using semantic representations when producing explanations for their decisions. By capturing the context and application domain in a granular manner, such graphs offer a much needed semantic layer that is currently missing from typical brute-force machine learning approaches.

    To this end, CIMPLE aims to experiment with innovative social and knowledge driven AI explanations,
    and to use computational creativity techniques to generate powerful, engaging, and easily and quickly
    understandable explanations of rather complex AI decisions and behavior. These explanations will be tested in the domain of detection and tracking of manipulated information, taking into account social,
    psychological and technical explainability needs and requirements.

     

    The Project is a Partnership between INESC-ID, EUROCOM (Paris, France), The Open University (UK),
    University of Economics and Business (Prague, Czech Republic) and WebLyzard technology, WLT
    (Vienna, Austria).

    CIMPLE was one of the CHIST-ERA projects approved under the 2019 call “Explainable Machine
    Learning-based Artificial Intelligence”.

    CHIST-ERA is a network of funding organisations in Europe and beyond supporting long term research on digital technologies with a high potential impact. It selects every year two new topics of emerging
    importance and launches a call for transnational research projects on these topics.

  • Lusa and Inesc-ID invite citizens to support the construction of a tool against misinformation

    Lusa and Inesc-ID invite citizens to support the construction of a tool against misinformation

    The Lusa agency and Inesc-ID invite citizens to participate in the construction of a tool that will help fight misinformation, by answering a survey to assess the perception of credibility of news content.

    The survey, which is available at http://inforadar.inesc-id.pt/inquerito/#artigo, is part of a larger project, under development, to build a tool whose ultimate goal is to stimulate the critical spirit of readers and thus contribute to their media literacy.

    “The purpose of the application we intend to create is based on the idea that users should make informed decision on the information they consume  and share, providing readers with a set of relevant indicators that allow them to critically evaluate the credibility of the information they are about to to consume”, explains Inesc-ID researcher Paula Carvalho.

    The objective of this initiative, reinforces Paula Carvalho, “is not to censor, it is to empower readers, to provide them with the means that allow them to make informed decisions”.

    In a first stage of development of this application, which is being developed by the Lusa agency and Inesc-ID, it was carried out an annotation study of a variety of news articles by a restricted group of communication professionals, which allowed the identification of relevant indicators to distinguish news credible from not credible.

    As the tool is not specifically aimed at communication professionals, but at the general public, who are less sensitive to the principles and rules of journalistic writing, it was considered “essential that the previously identified credibility indicators by journalists are also assessed by common readers, to verify its relevance and consider its integration into the tool under development”, she said.

    By participating in the survey, available online, which will be more successful the more people who participate, citizens will be checking aspects such as the strategies used in the news headlines, the mention in the text of credible sources, the author’s degree of impartiality, usually in line with the use of neutral and objective language, a coherent discourse, which does not resort to fallacies, etc.

    “What we intend to investigate is the relative importance that users attach to each of these aspects, in order to select the attributes considered most relevant and informative to determine the credibility of the content they are confronted with”, explains the researcher from Inesc-ID .

    Many works have focused on finding strategies to distinguish credible news from non-credible or fake news (known as `fake news`), but, according to the researcher, “this approach is very reductive, seeking to group together a very heterogeneous set of news content, and, ultimately, journalistic styles, in just two categories”.

    Using the metaphor of colors, Paula Carvalho simplifies that “not everything is white or black. On the contrary, gray rules. Therefore, what we consider most appropriate is to assume that textual content can present different degrees of credibility, depending on the analysis of the indicators that seem relevant for a specific case.”.

    For example, if the reader is confronted with a news article that reveals a low degree of linguistic rigor, use `clickbait` strategies in the title, to attract his  attention and generate clicks, do not cite reliable sources and evokes the author’s opinions and sentiment, ” we believe that he will have no difficulty in making his own judgments about the credibility of the text”.

    The aim of this tool is to understand which textual characteristics are more associated with rigorous journalistic content, on the one hand, and misinformation, on the other, from the perspective of a common reader.

    Regarding the structure of the survey, each respondent is asked to read a text (randomly assigned) and answer a short questionnaire, consisting of a set of closed questions about that text.

    This questionnaire highlights textual aspects that must be considered when critically judging the credibility of an article, having also a didactic character.

    The researcher from Inesc-ID says she believes that, “by answering these questions, the reader is exercising his critical thinking, and it may happen that, in some cases, the initial intuition on the text credibility changes, after reflecting on the aspects he was confronted with”.

    This is one of the objectives of the project: “The tool to be made available will increase readers’ awareness and critical thinking, and thus contribute to their media literacy”, she pointed out.

    As the responses to this survey will be reflected in the tool, one may assume that readers will actively contribute to the definition of the “ingredients” that should make up the news nutrition labels.

    The survey is included in the 5th module of the Ciberinformado Citizen Course, https://www.nau.edu.pt/pt/curso/cidadao-ciberinformado/, developed by the Lusa agency and the Centro Nacional de CiberSegurança, but it can be answered independently, without having to do the entire course. The Cyber-informed Citizen is now in its second edition, having so far had more than eight thousand participants.
    The new module of the “Cyber-informed” course helps the trainee to understand and analyze the “nutritional information” of a news, considering all its content, from the credibility of the sources, the origin or if the text has a high emotional charge or subjectivity .

    The “Ciberinformed Citizen” course lasts an average of four hours, is free, is intended for all citizens who consult online information and is available until August 31, 2021.