Adriano Jorge Cardoso Moreira is an Associate Professor with Habilitation at the Department of Information Systems, School of Engineering, Universidade do Minho, Portugal. He is also a Senior Researcher at the Algoritmi Research Centre and Scientific Coordinator of the Urban and Mobile Computing department at Centro de Computação Gráfica. His research focuses on indoor positioning , mobile and context-aware computing , urban computing , and simulation of wireless networks . Research Interests : Indoor Positioning, Mobile Computing, Urban Mobility, Sensor Networks, Wi-Fi and UWB Localization, Smart Cities. Leadership : Coordinated the Computer Communications and Pervasive Media Group (2008-2016), Scientific Committee member (Director of MAP-tele PhD program in multiple terms), and leads the Master in Telecommunications and Informatics since 2021. Publications : Over 100 papers, including IEEE Transactions and Sensors journal articles, with an h-index of 23 and 2136 citations. Awards : First and second prizes in EvAAL-ETRI Indoor Localization Competitions (2015, 2016, 2017).
Maria Leonilde Rocha Varela is an Associate Professor with Habilitation at the School of Engineering, University of Minho, Portugal, where she also serves as a Senior Researcher at the Algoritmi Research Centre. She has been an integrated member of the Algoritmi Research Centre since 2012 and works in the Department of Production and Systems. Dr. Varela earned her degree in Production Engineering from the University of Minho in 1994, completed a Master's in Computer Integrated Production at DPS-UMinho in 1999, and received her Ph.D. in Production and Systems from the University of Minho in 2007. Her primary research focuses on Manufacturing Management, particularly Production Planning, Control and Optimization, and Collaborative Paradigms, Networks and Decision Making Models. She maintains extensive international collaborations with institutions worldwide including the National Institute of Industrial Engineering, VSB-Technick Univerzita Ostrava, University of Belgrade, and others. Her research spans Web Applications and Services for supporting Engineering and Production Management, with increasing emphasis on Artificial Intelligence, Robotic Process Automation, and Industry 4.0/5.0 applications. She has made significant contributions to scheduling algorithms, optimization techniques, and decision support systems for manufacturing environments. Analysis of her recent publications reveals a strong trend toward integrating Artificial Intelligence with traditional manufacturing processes, particularly in Robotic Process Automation applications. Her research increasingly focuses on sustainable manufacturing practices, with numerous publications addressing energy efficiency, environmental sustainability, and resource optimization. There is a clear emphasis on multi-objective optimization approaches to solve complex manufacturing problems, particularly in distributed job shop scheduling. Her work demonstrates an evolution from traditional production planning methods to more advanced AI-driven approaches for Industry 4.0 and 5.0 environments. Dr. Varela has held significant academic leadership roles, currently serving as the director of the master's course in Engineering and Quality Management at DPS-UMinho. She previously coordinated the industrial management and systems subgroup from 2012 to 2021 and was part of the steering committee for the master's course in systems engineering between 2016 and 2019. She has successfully supervised more than 70 MSc projects, with over 15 currently ongoing, focusing on Production and Systems Engineering. Her supervision encompasses collaborative management models, traditional decision approaches, and web-based platforms incorporating AI techniques. She coordinates research projects including 2 concluded Ph.D. projects and 6 ongoing ones. She collaborates as a research member in several R&D projects with national and international industrial enterprises and institutions, and in international Erasmus projects. Dr. Varela is an active participant in the academic community, serving on editorial boards of several international journals and as a member of organizing and scientific committees for numerous international conferences. She is a member of several prestigious research networks including the Euro Working Group of Decision Support Systems (EWG-DSS), Institute of Electrical and Electronics Engineers (IEEE), Industrial Engineering Network, and the Institute of Industrial and Systems Engineers (IISE).
Vitor Sencadas is an Associate Professor at the Department of Materials and Ceramic Engineering, University of Aveiro, Portugal. His research focuses on advanced materials for biomedical, energy, and environmental applications, with a strong emphasis on nanotechnology and additive manufacturing. He leads projects such as 3S4Leather, addressing leather waste valorization and sensorized additive manufacturing solutions. He has supervised multiple PhD students and contributed to over 150 publications in journals like Advanced Functional Materials and ACS Applied Materials & Interfaces. His research interests include biomimetic materials, flexible electronics, wearable sensors, and sustainable materials. Notable achievements include developing piezoelectric and luminescent solar concentrators, and contributions to Stanford’s 2022/2024 World Top 2% Scientists list. His work bridges materials science with practical applications in healthcare, energy harvesting, and environmental biorefinery processes. He collaborates extensively with CICECO – Aveiro Institute of Materials, contributing to interdisciplinary research and innovation in smart materials and biomedical devices. His group explores multifunctional materials for healthcare monitoring, energy systems, and sustainable manufacturing.
Pedro R. M. Inácio is an Associate Professor at the University of Beira Interior (UBI) , where he teaches information assurance, cybersecurity, and computer simulation courses in undergraduate and graduate programs. He serves as Pro-Rector for the Digital University and Data Protection Officer at UBI, and leads the Cross Cutting Skills Lab and the Network Security research group at Instituto de Telecomunicações. His work bridges academia and industry, including a PhD at Nokia Siemens Networks Portugal.
Sinh Thoi Mai is a faculty member at the Instituto Superior de Economia e Gestão (ISEG) within the University of Lisbon (ULisboa). He holds a Doctorate of Business Administration (2024) from Abo Akademi University (Finland) and a Master of Science in Business Administration and Finance (2018) from University College Cork (Ireland). His academic role includes coordinating courses such as Contabilidade e Análise Financeira for the Master’s program in Direito e Gestão. His research focuses on monetary policy transmission mechanisms , financial uncertainty , and applications of machine learning in economics . Key areas include analyzing cryptocurrency market dynamics, corporate strategic responses to economic shocks, and the impact of policy frameworks on firms and public fundraising. Dr. Mai contributes to research initiatives through ISEG’s labs, including the Data Lab and Futures Lab , which explore cutting-edge topics in economics and management. His work bridges theoretical economic analysis with practical applications in finance and corporate strategy. While no formal awards or grants are explicitly listed, his active research portfolio reflects ongoing engagement with contemporary economic challenges. Advising and student mentorship are integral to his role, though specific student names are not documented here.
Dr. Teresa Melo is an Assistant Professor in the Department of Mineral and Energy Resources Engineering at the Instituto Superior Técnico (University of Lisbon). Her research focuses on hydrogeology, groundwater management, and environmental geochemistry, with a particular emphasis on climate change impacts and ecosystem sustainability. She is affiliated with the CERIS research unit, specializing in sustainable civil engineering innovations. Her teaching portfolio includes courses such as 'Hydrogeology,' 'Groundwater Pollution and Protection,' and 'Advanced Topics in Water Resources and Environment.' She actively contributes to the AQUADAPT project, addressing climate-resilient riverine ecosystems and groundwater-dependent vegetation mapping. Key research themes include groundwater-surface water interactions, natural background level assessments, and the socio-economic valuation of groundwater protection. She collaborates internationally on projects such as the FREEZE initiative, investigating submarine groundwater discharge and coastal aquifer dynamics. Her publications span over three decades, with recent work emphasizing wildfire impacts on groundwater recharge, microbial diversity in aquifers, and ethical dimensions of contaminated groundwater management. She has advised numerous interdisciplinary studies on environmental risk assessment and policy frameworks.
José Manuel Ferreira Machado is a Full Professor at the Department of Informatics, School of Engineering, University of Minho, where he has been affiliated since 1988. His research integrates Artificial Intelligence, Medical Informatics, and Data Mining, with applications in healthcare, industrial systems, and public services. He founded ALGORITMI's 'Knowledge Engineering' group and served as Director of the ALGORITMI R&D Center (2018-2024). Education: Agregado in Informatics (AI), Universidade de Trás-os-Montes e Alto Douro (2011-2012) PhD in Informatics (AI), Universidade do Minho (1995-2002) Licenciatura in Systems and Informatics Engineering, Universidade do Minho (1982-1988) Research Interests: Machado's work focuses on intelligent systems for healthcare (e.g., AIDA medical platform), industrial automation, and smart cities. He emphasizes real-world applications, including clinical decision support, predictive maintenance, and sustainable urban infrastructure. Publications: His recent articles (2022-2025) demonstrate a strong focus on healthcare AI (e.g., disease prediction, COVID-19 analytics) and smart systems (e.g., traffic optimization, energy sustainability), utilizing data mining and machine learning. Awards: Hospital of the Future (2007, 2008, 2009) Good Practices in Health (2014) Portugal Digital Awards (2016) IHF Awards (2021) Advising & Grants: Supervised 16 PhD, 101 MSc, and 4 post-doc students. Leads sub-projects in PRR agendas GReenAuto and Be.Neutral. Secured funding from FCT, EU, and industry partners (e.g., Bosch) for 50+ projects. Labs & Teams: Coordinates the 'Knowledge Engineering' research group at ALGORITMI, focusing on intelligent decision support and interoperability in healthcare and industry.
João Magalhães is a Full Professor in the Department of Computer Science at the Faculty of Science and Technology, Universidade NOVA de Lisboa, Portugal. He serves as Group Coordinator of the Multimodal Systems Group at the NOVA Laboratory for Informatics and Computer Science and leads the NOVASearch research group at FCT/UNL. His research focuses on vision and language information understanding, with particular emphasis on multimodal information understanding, multimodal conversational AI, multimedia search and summarization, temporal and memory models, and social media information quality. His work spans both theoretical foundations and practical applications across web, social media, and clinical domains. Analysis of his recent publications reveals a strong trajectory in multimodal conversational AI systems, with increasing sophistication in handling both voice and visual inputs. His research has evolved from foundational work in cross-modal embeddings to advanced large language models for dual-goal conversational settings, demonstrating consistent innovation in the field of multimodal understanding. 1st prize winner of the second Alexa TaskBot Challenge (2023) Award-winning solution in the Alexa TaskBot Challenge (2022) Best paper award at the Portuguese NLP conference (PROPOR) (2020) Best paper nominations at ACM conferences (2018) Professor Magalhães has advised numerous graduate students through the NOVASearch group and has secured substantial research funding through projects including Amazon Alexa TaskBot Challenge (2021-2023), iFetch (2020-2023), SmartyFlow (2017-2020), COGNITUS (2016-2019), GoLocal (2016-2020), QSearch (2012-2015), ImTV (2010-2013), and CS4SE (2010-2013). He actively serves the research community as ACM Multimedia 2026 Program Committee Chair and has held leadership roles in numerous conferences including ACM Multimedia 2022 General Chair and ECIR2020 General Chair. He leads the Multimodal Systems Group within the NOVA Laboratory for Informatics and Computer Science, where his team develops cutting-edge solutions for multimodal understanding with applications in conversational AI, multimedia search, and social media analysis.
Amelia Compagni serves as Associate Professor in the Department of Social and Political Sciences at Bocconi University and Director of CeRGAS (Center for Research on Health and Social Care Management) at SDA Bocconi. Previously Director of the World Bachelor in Business program, she teaches healthcare management and public management across undergraduate, graduate, and PhD programs at Bocconi University alongside MIHMEP and MIMS master programs at SDA Bocconi. Her academic foundation includes a Biology degree specializing in Genetics and Molecular Biology from the University of Pavia, followed by a PhD in Genetics from Vienna's Institute of Molecular Pathology (1995-2000). After a post-doctoral fellowship at Cancer Research UK in London (2000-2004), she transitioned to management through a Master in Healthcare Management, Economics and Policy from SDA Bocconi. Compagni's research centers on healthcare management dynamics and innovation within professional healthcare groups , with expanding focus on digital transformation and AI applications . Her work bridges biological sciences with management perspectives to address systemic healthcare challenges, particularly examining organizational behavior in clinical settings and policy implementation. Recent publications (2024-2025) reveal concentrated exploration of telemedicine efficacy, healthy ageing metrics, AI adoption barriers, and environmental sustainability in healthcare systems. These studies demonstrate interdisciplinary methodology spanning systematic reviews, empirical surveys of healthcare organizations, and patient-centered outcome research published in top-tier journals. Award recognition includes: Excellence in Research Award (Bocconi University, 2024) Excellence in Teaching Innovation Award (2019) Academy of Management Best Reviewers Award (2018) Research Excellence Award (2015) International “Vivisalute” Research Award (2012) SDA Bocconi Best Teacher Award (2010) Through CeRGAS leadership, she directs national and international collaborations analyzing healthcare organization effectiveness, with recent projects examining Lombardy's AI implementation and comparative sustainability models between Italy and England. Her advisory work focuses on translating research into practical management frameworks for healthcare institutions.
José Paulo Afonso Esperança is a Full Professor of Finance at ISCTE Business School, ISCTE - University Institute of Lisbon. He previously served as Pro-Rector for International Relations and Entrepreneurship (2010-2013), Dean of ISCTE Business School, and Vice-President of FCT (Foundation for Science and Technology). He co-founded Building Global Innovators (BGI), a MIT Portugal technology transfer accelerator, and chaired AUDAX-ISCTE, an entrepreneurship center focused on family business. His educational background includes: Agregação (2003) from ISCTE-Instituto Universitário de Lisboa PhD in Economics (1993) from the European University Institute, Florence Licenciatura in Organization and Business Management (1980) from ISCTE-IUL Professor Esperança's research centers on entrepreneurship and small business financing , corporate governance , and language commonality in international business . His work bridges theoretical frameworks with empirical analyses of emerging economies, examining financial inclusion mechanisms, SME credit constraints, and linguistic influences on foreign direct investment. He has published extensively in top-tier journals including Annals of Operations Research and Journal of Business Finance and Accounting. His publication trends reveal increasing focus on financial technology applications, behavioral aspects of lending, and Lusophone economic integration. Recent work analyzes prosocial crowdlending dynamics and socio-technical credit evaluation frameworks, reflecting interdisciplinary approaches to financial inclusion challenges. Key recognitions include: Best IBS Case for the FAE-MOVVO Competition: Location-Based Big Data Marketing (2015) Best IBS Case for the FAE-Science 4You Competition (2014) He secured significant research funding as Principal Investigator for the project 'Corporate Governance in Medium Income Countries: The Case of Portugal' (2007-2011). His leadership extends to entrepreneurship initiatives through AUDAX-ISCTE and BGI, where he developed technology transfer frameworks. Since 2014, he has served as National Delegate for the H2020 SME Instrument at FCT, advising on European innovation funding. Professor Esperança maintains active involvement in Lusophone economic networks through the New Atlas of the Portuguese Language project and CPADA (Portuguese Federation of Environmental Associations), where he serves on the board.
Minjoon Seo is an Associate Professor at KAIST AI, Korea Advanced Institute of Science and Technology. He holds a BS in Electrical Engineering & Computer Science from UC Berkeley and previously worked as a software engineer at Oracle. His research focuses on natural language understanding, large-scale end-to-end question answering, and multimodal AI systems combining language and vision. Research Interests: His work spans Natural Language Processing, Machine Learning, Deep Learning, and Language-Vision integration. He develops neural network architectures for machine comprehension and multimodal understanding, with applications in question answering systems and diagram interpretation. Publications: His research demonstrates a consistent focus on multimodal AI systems, with recent works advancing neural approaches to machine comprehension and diagram understanding. Publications show strong emphasis on NLP-CV integration and practical applications in healthcare and education. Awards: Best Paper Nomination at UbiComp 2014 for BiliCam research Professional Activities: Maintains active open-source contributions through GitHub repositories related to question answering systems and NLP research. Co-founded Config Intelligence while maintaining academic position.
Simo Hosio is an Academy Research Fellow (2022-2027) and Professor of Computer Science and Engineering at University of Oulu's Center for Ubiquitous Computing, where he leads the Crowd Computing Research Group. He also maintains a visiting position at University of Tokyo, Japan. Having graduated as the first Finnish scholar under Microsoft Research Cambridge's Ph.D. scholarship program, he has published over 150 peer-reviewed scientific articles spanning two decades of research. Hosio's research spans three primary domains: crowdsourcing methodologies, human-computer interaction, and digital health applications. His work pioneers novel approaches to online labor markets, investigates the suitability of crowdsourcing for diverse applications, and explores HCI aspects of digital health solutions for chronic conditions. His research group, founded in 2020, has secured nearly two million USD in funding, demonstrating significant research impact and recognition. Analysis of Hosio's recent publications reveals a strong trend toward interdisciplinary research at the intersection of crowdsourcing, healthcare technology, and emerging AI systems. His work increasingly focuses on practical applications of crowd computing in health contexts, with growing attention to mental health, women's health, and workplace well-being solutions. The integration of AI and machine learning techniques with traditional HCI approaches represents another significant trajectory in his recent scholarship. Distinguished Paper Award (2024) Best Paper Honourable Mention Award (2022) PMCJ Best Research Paper (awarded in 2024) Best Paper Award (2022) Best Full Paper Award (2015) Honorable Mention Award (2014) Best Paper Presentation award (2010) As an educator, Hosio has taught Human-Computer Interaction (2019-2025) to over 260 students in 2024, Social Computing (2018-2021) to approximately 60 students annually, and Applied Computing (2015-2018) to around 50 students each year. His research group's nearly two million USD in secured funding demonstrates significant grant acquisition success, supporting innovative work at the intersection of crowd computing, health technology, and human-centered AI systems. The Crowd Computing Research Group, founded by Hosio in 2020, represents a significant research infrastructure focused on advancing methodologies for crowd-powered systems. The group's work spans from fundamental research on crowd labor markets to applied projects in healthcare, workplace well-being, and social computing, demonstrating a strong commitment to both theoretical advancement and practical impact.
João Miguel Lobo Fernandes is a Full Professor at the Department of Informatics, School of Engineering, University of Minho. He holds a 5-year degree in Informatics Engineering (1991), a Master's in Informatics (1994), and a Ph.D. in Informatics/Computer Engineering (2000) from Universidade do Minho, with a thesis on An object-oriented methodology for embedded systems development . Research interests: Software Modeling, Requirements Engineering, Embedded Software, Software Process, Bibliometrics International collaborations: University of Bristol, Turku Centre for Computer Science (Finland), Aarhus University (Denmark), Universidade Federal de Santa Catarina (Brazil), and others Key projects: iFlow and DIABO logistics platforms (awarded by APLOG) His 160+ peer-reviewed publications focus on software methodologies, embedded systems, and industry collaborations. Recent work includes applications of machine learning in automotive software, feature modeling, and remote work impact studies. He serves on editorial boards for Journal of Information Technology Research and Open Computer Science . 2016 & 2022 Logistics Excellence Awards (APLOG) Organized international events: ACSD, DIPES, GTTSE, PETRI NETS, ICSOB, MOMPES As an academic leader, he directed the 5-year Systems and Informatics Engineering degree (2004-06), Master's in Informatics Engineering (2011-12), and served on Scientific Council of the School of Engineering (2013-16).
Paulo Jorge Freitas de Oliveira Novais is a Full Professor of Computer Science at the Department of Informatics, School of Engineering, Universidade do Minho, where he also holds a Habilitation in Computer Science. He leads the Synthetic Intelligence Lab at ALGORITMI Centre and coordinates the research line on Ambient Intelligence for Well-Being and Health Applications. His research spans Intelligent Systems, Machine Learning, Multi-Agent Systems, and their applications in Smart Cities, Health Informatics, and AI Ethics. PhD in Computer Science, Universidade do Minho, 2003 Habilitation in Computer Science, Universidade do Minho, 2011 Research interests include Ambient Intelligence, Ambient Assisted Living, Intelligent Environments, AI and Law, Conflict Resolution, and Explainable AI. His work focuses on enhancing system intelligence and reliability through novel architectures and ethical frameworks. Recent publications highlight applications in wastewater energy prediction, violence detection, student risk modeling, and urban logistics. Awards include multiple Best Paper and IBM Excellence recognitions across 2015–2023, plus a 2022 Career Recognition Award from the Ibero-American Society of Artificial Intelligence. Senior IEEE Member Chair of IEEE Computational Intelligence Chapter, Portugal IFIP TC 12 Artificial Intelligence Working Group Leadership He has supervised 132 PhD and Master’s students and contributed to editorial boards of journals like JAISE and ComSIS . His leadership roles include coordinating LASI – Intelligent Systems Associate Laboratory and serving as former president of APPIA.
Pedro Duarte Silva is an Associate Professor at Católica Porto Business School, Universidade Católica Portuguesa. His research focuses on statistical methods for distributional and interval data, developing parametric models and classification techniques. Recent work includes developing the MAINT.Data R package for interval data analysis and investigating outlier detection methodologies. As part of the Research Center in Management and Economics (CEGE), he contributes to methodological advances in data analysis with applications to management science. Current projects examine optimization approaches for classification problems and symbolic data analysis for official statistics.
