Find Academic Supervisors

• Medical Statistics
• Biostatistics
• Epidemiology
• +3 more

Ruth Keogh is a Professor of Biostatistics and Epidemiology at the London School of Hygiene & Tropical Medicine (LSHTM), affiliated with the Medical Statistics Department within the Faculty of Epidemiology and Population Health. She is Co-Director of the Centre for Data and Statistical Science for Health (DASH) and serves as Departmental Research Degrees Coordinator. Her academic career has spanned roles from Lecturer (2012–2015) to Associate Professor (2015–2019) before attaining her current rank in 2019. Keogh holds advanced degrees including a DPhil in Medical Statistics/Epidemiology (University of Oxford, 2007), MSc in Applied Statistics (Oxford, 2003), and BSc in Mathematics and Statistics (University of Edinburgh, 2002). Her research focuses on causal inference, clinical trial emulation using real-world data, and applications in cystic fibrosis, infectious diseases, and public health. She leads projects on lung function trajectories, vaccine efficacy, and healthcare policy analysis. Her work integrates biostatistical methods with epidemiological studies, emphasizing rigorous analysis of observational data to inform clinical decisions. Notable areas include evaluating antibiotic treatments for cystic fibrosis patients, assessing diagnostic test accuracy for dengue and leptospirosis, and modeling vaccine effectiveness during the COVID-19 pandemic. She teaches courses in survival analysis, electronic health records, and health data science at LSHTM. Keogh has held leadership roles in the International Biometric Society and the STRATOS Initiative, and she has delivered keynote addresses at international conferences on trial emulation and biostatistical methods. Her contributions bridge methodological innovation and practical health challenges, with over 190 publications and active engagement in global health research networks.

• Artificial Intelligence for Power Systems
• Smart Grids
• Energy Management
• +4 more

Zita Vale is a Full Professor at the Institute of Engineering (ISEP) of the Polytechnic of Porto (IPP), where she holds the first Full Professor position since 2017. She is a co-founder of GECAD (1999) and coordinates GECAD's Power and Energy (PES) activities. GECAD is recognized by FCT since 2004 and classified as Excellent. She has served as GECAD director (2010-2017), vice-director (1999-2009, 2017-present), and is a member of the administration board. She is also co-founder and member of the coordination board of the National Associated Laboratory on Intelligent Systems. Her educational background includes a PhD (1993) and Agregação/Habilitation (2003) in Electrical and Computer Engineering from the University of Porto. She began her academic career at the University of Porto as a Teaching Monitor (1985), Assistant (1985-1993), and Professor (1993-1998) before moving to ISEP in 1998. Zita Vale's research focuses on the design and development of artificial intelligence-based models for Power and Energy Systems. Her work spans knowledge-based systems, multiagent systems, machine learning, metaheuristics, and semantics, with applications in smart grids, energy management, electricity markets, and renewable energy integration. She has an extensive international network and has participated in 80 R&D projects, raising over 22 million Euros for GECAD. Her recent publications demonstrate a strong emphasis on optimization techniques, explainable AI, energy storage systems, and the integration of distributed energy resources in power systems. She serves as Editor-in-Chief of Applied Energy (Elsevier), a leading journal in the field with an Impact Factor of 11.2. Her citation metrics are impressive, with over 17,000 citations on Google Scholar and an H-index of 64. Editor-in-Chief of Applied Energy (Elsevier) Over 17,000 citations on Google Scholar H-index of 64 Zita Vale has supervised 29 PhD students (25 completed) and 72 MSc students (66 completed), demonstrating her strong commitment to academic mentorship. She has also been involved in numerous international and national evaluation processes, including project proposals, faculty positions, and PhD juries across 15+ countries. She has contributed to over 225 evaluation processes from 2018-2023, including 150+ project proposals/execution, 50+ Faculty/Researchers positions, 2 Habilitation juries, and 25+ PhD juries. She leads GECAD's involvement in several major research initiatives, including the National Associated Laboratory on Intelligent Systems and various European projects such as IoTalentum, TRADERES, DOMINOES, and EcoRural-IoT from Horizon 2020, as well as PRODUTECH EU DIH from Horizon Europe. Her leadership extends to international organizations where she serves as President of Intelligent Systems Applications in Power (ISAP) and Technical Committee Program Chair of IEEE PES Analytic Methods for Power Systems Committee.

Leid ZejnilovicView profile

Assistant Professor

• Technology and Innovation Management
• Human-Computer Interaction
• Machine Learning
• +3 more

Leid Zejnilovic is an Assistant Professor at Nova School of Business and Economics (Nova SBE), where he co-founded the Data Science Knowledge Center and serves as Academic Director, and co-founded the Open and User Innovation Knowledge Center as Scientific Deputy Director. He also co-founded the Patient Innovation platform, enabling patients and caregivers to share self-made healthcare solutions. With a double PhD from Carnegie Mellon University and Católica-Lisbon School of Business and Economics, his career spans over 20 years of international consulting, academic entrepreneurship, and teaching at institutions like Imperial College Business School and Ludwig Boltzmann Institute. PhD in Strategy, Entrepreneurship and Technological Change (Carnegie Mellon University / Catholic University of Portugal, 2014) Master in Engineering and Public Policy (Carnegie Mellon University, 2012) Master in Information Technology (Dzemal Bijedic University, 2007) Bachelor in Telecommunications (University of Sarajevo, 2002) His research focuses on Technology and Innovation Management, Human-Computer Interaction, and data-driven solutions across healthcare, tourism, and education. He has published extensively in journals like California Management Review , PLoS ONE , and Marine Policy , with recent work analyzing big data in tourism, machine learning for oral health, and pandemic impacts on fisheries. As an Associate Editor for Data & Policy Journal , his contributions bridge academic research and real-world applications. Co-founding the Data Science for Social Good Foundation and leading over 100 talks in industry and academia, Zejnilovic's career emphasizes translating innovation into social and economic impact through platforms, policy, and education.

• Biotechnology
• Biocatalysis
• Enzyme Engineering
• +4 more

Pedro Carlos De Barros Fernandes is an Associate Professor at Universidade Lusófona , Deputy Director of the 1st cycle in Biotechnology, and an integrated researcher at the Institute of Bioengineering and Biosciences (iBB-IST). He holds a PhD in Biotechnology (1999) and a Master in Biotechnology/Biochemical Engineering (1994) from Universidade Técnica de Lisboa (IST), along with a Chemical Engineering degree from IST (1989). A member of the Order of Engineers (ID 24667), he co-founded Biotrend, a Portuguese bioprocess development company. Education PhD in Biotechnology (1999), Universidade Técnica de Lisboa MSc in Biotechnology (1994), Instituto Superior Técnico BSc in Chemical Engineering (1989), Instituto Superior Técnico Research Interests span biocatalysis, enzyme immobilization for food and pharmaceutical applications, marine biotechnology, microfluidic device development for biosensing, and steroid bioconversions using mycobacterial systems. His work integrates process engineering principles with sustainable bioprocessing techniques. Publication Trends show a focus on microreactor technology, enzyme stabilization in non-conventional media, marine-derived biocatalysts, and food waste valorization. Key themes include biocatalytic process intensification, aqueous two-phase systems for biomolecule purification, and sustainable carbon sources for biopolymer production. Scientific Awards UTL/Santander Totta Scientific Award in Biological Engineering (2011) Advising has included supervision of 5 doctoral theses and over 32 master’s theses. His expertise extends to peer-reviewing scientific articles and evaluating R&D projects. Labs & Teams are associated with iBB-IST (Institute of Bioengineering and Biosciences) and BioRG (Universidade Lusófona), with contributions to the Ciência Viva program for science dissemination.

• Textile Engineering
• Smart Textiles
• Electronic Textiles
• +7 more

André Catarino is an Assistant Professor in the Department of Textile Engineering at the University of Minho, Portugal, and Deputy Director of the 2C2T – Center for Textile Science and Technology since 2022. He is an integrated researcher at the center, with a strong focus on interdisciplinary research at the intersection of textiles, electronics, and materials science. Education: Postgraduate Specialization in Digital Business, University of Porto, Porto Business School (2020–2021) Ph.D. in Textile Engineering, University of Minho (2005) M.Sc. in Textile Engineering, University of Minho (1998) B.Sc. in Electrical and Computer Engineering, University of Porto (1992) Research Interests: André Catarino's research spans a wide range of domains, including smart and electronic textiles , wearable sensor systems , materials engineering , and functional textiles for health and sports . His recent work also delves into digital marketing and the application of artificial intelligence in textile systems. His expertise encompasses electronics, instrumentation, programming, fabric manufacturing, and textile characterization. He has led or participated in over 25 national and international research projects , including EU-funded initiatives like BE@T, GreenAuto, and Fashion Alive. His work has resulted in 4 Portuguese patents and 1 European patent , alongside numerous prototypes and technology transfers. Publications and Impact: With over 115 scientific publications , including journal articles, book chapters, and conference proceedings, his research output is both broad and impactful. His recent publications focus on smart vests for posture monitoring, textile-based EMG electrodes, and consumer behavior in fashion marketing. Student Supervision: He has supervised or co-supervised more than 45 master’s and doctoral dissertations , covering topics from wearable health monitoring systems to sustainable fashion design and digital marketing strategies. Labs and Teams: As Deputy Director of the 2C2T – Center for Textile Science and Technology , he leads a multidisciplinary team of researchers and engineers. The center is a hub for innovation in textile science, with a strong emphasis on integrating electronics, sustainability, and human-centered design into textile applications.

Juho LeeView profile

Associate Professor

• Bayesian deep learning
• Bayesian inference
• meta learning
• +5 more

Juho Lee is an Associate Professor at the Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST). Previously, he worked as a research scientist at AITRICS and completed his PhD in Computer Science & Engineering at Pohang University of Science and Technology (POSTECH) under Professor Seungjin Choi, followed by postdoctoral research at University of Oxford with Professor François Caron. His research focuses on: Bayesian deep learning Bayesian inference Meta learning Generative models Uncertainty quantification Graph representation learning Professor Lee's work bridges theoretical Bayesian methods with practical deep learning applications. His recent publications demonstrate significant contributions to neural processes, Bayesian optimization, and scalable inference methods. He has developed novel architectures like Set Transformer for permutation-invariant modeling and advanced techniques for uncertainty quantification in deep networks. His research shows a clear trajectory toward making Bayesian principles applicable to large-scale, real-world machine learning problems. Notable contributions include: Set Transformer: A framework for attention-based permutation-invariant neural networks (ICML 2019) Bootstrapping neural processes (NeurIPS 2020) Deep amortized clustering (NeurIPS 2019 workshop) Learning to pool in graph neural networks for extrapolation Professor Lee actively mentors graduate students and has advised numerous PhD candidates who co-author papers with him across NeurIPS, ICML, and ICLR. His research group SIML@KAIST develops scalable and interpretable machine learning methods with strong theoretical foundations.

Armando Jorge Domingues SilvestreView profile

Professor

• Chemistry
• Polymer Science
• Renewable Materials
• +3 more

Armando J. D. Silvestre is a Full Professor at the Department of Chemistry, University of Aveiro. He holds academic degrees including a Licenciatura in Chemistry (1990), PhD in Chemistry (1994), and Agregação in Chemistry (2008) from the University of Aveiro. His research focuses on renewable materials, circular economy, and functional biomaterials. Research interests include: Development of biopolymer-based functional materials Valorization of biological residues for value-added chemicals Novel polymeric materials from renewable resources Sustainable nanocomposites and coatings Professor Silvestre has supervised 18 MSc and 11 PhD students to completion and currently mentors 3 PhD and 3 MSc candidates. Research projects include EU-funded initiatives like AFORE (Forest Biorefineries) and national projects on membrane technology and biomass valorization. Scientific contributions include over 180 SCI journal publications and patents on extraction methods. He serves on editorial boards for Industrial Crops and Products and actively participates in academic activities including Erasmus coordination and Bologna process implementation.

• Convivial informatics
• Digital sustainability
• Participatory design
• +9 more

Aurélien Tabard is an Associate Professor at LIRIS (Laboratoire d'InfoRmatique en Image et Systèmes d'information), a joint research unit between Université Claude Bernard Lyon 1 and CNRS. His academic career spans over a decade with positions at prestigious institutions including the IT University of Copenhagen, University of Munich, and INRIA. He completed his PhD at Université Paris-Sud in 2009, focusing on supporting lightweight reflection on familiar information. Tabard's research centers on convivial informatics, exploring alternatives to computational platforms that consider digital limits and foster sufficiency, maintenance, autonomy, and durability. His work emphasizes participatory approaches to designing resilient infrastructures and tools for rapid prototyping by non-designers. He investigates software obsolescence, digital sufficiency, and the materiality of data physicalization through projects like Limites Numériques and PC4-Congrats within PEPR eNSEMBLE. His recent publications reveal strong trends toward sustainability in computing, examining how digital systems can be designed with longevity and environmental impact in mind. There's a clear progression from technical HCI research toward broader societal implications of digital technology, particularly focusing on how users experience aging devices and negotiate digital limits collectively. Honorable mention award for 'Obsolescence Paths: living with aging devices' at ICT4S 2023 Student Lea Mosesso received the prize for best MSc thesis from Conseil National du Numérique Tabard actively mentors PhD students including Maëva Calmettes (working on skill and expertise sharing), Edlira Nano (studying software obsolescence), and Lea Mosesso (researching digital sufficiency). He collaborates extensively with researchers across France and internationally, particularly with Inria Lille where he spent a sabbatical in 2023. His current projects involve understanding software obsolescence, digital sufficiency, and the interplay between micro design decisions and systemic forces shaping ICT. He leads the Limites Numériques team, which investigates how to design computational platforms that take digital limits into consideration. The team recently developed an exhibit on water in the digital sector that will travel to Rhône-Alpes in spring 2025. Tabard also contributes to participatory design tools and critical approaches to participatory design, working with colleagues like Nolwenn Maudet, Thomas Thibault, and Romain Rouvoy.

• Graphic Design
• Design Criticism
• Visual Communication
• +3 more

Francisco Laranjo is a Portuguese graphic designer, researcher, and educator with a PhD in Design Methods and Criticism from the University of the Arts London. He holds an MA in Visual Communication from the Royal College of Art and a BA from ESAD – Escola Superior de Artes e Design. Currently serving as Assistant Professor at Lusófona University, he also works as an Associate Lecturer at Central Saint Martins and Co-director of the Shared Institute. PhD in Design Methods and Criticism MA in Visual Communication BA in Communication Design His work bridges graphic design with critical theory, focusing on design pedagogy, ethical implications of data-driven design, and the role of critique in professional practice. Publications span design criticism in Design Observer , Eye Magazine , and academic journals, while his teaching has reached institutions across 8 countries including CalArts, Sandberg Institute, and Zürich University of the Arts. Recent publications demonstrate a trajectory toward critical design theory, post-pandemic design adaptation, and curatorial practices. Key themes include the intersection of design and politics , digital-physical hybridity , and pedagogical innovation in graphic design education. As Editor of Modes of Criticism and co-director of Shared Institute, Laranjo fosters critical discourse through curatorial projects like the 2022 'Designers Troublemakers' exhibition and the upcoming 2025 'Graphic Collection – 50 years of design in Portugal' at the Polytechnic University of Porto.

• Natural Language Processing
• Machine Learning
• Text Mining
• +10 more

Fernando Manuel Marques Batista is an Associate Professor at ISCTE – University Institute of Lisbon, Department of Information Science and Technology, and an integrated researcher at INESC-ID Lisbon. He serves as the Executive Coordinator of the Human Language Technologies (HLT) Scientific Area at INESC-ID and is a member of its Scientific Council. He previously held leadership roles including President of the Pedagogical Council of ISCTE-IUL (2017–2019) and member of its Standing Committee (2015–2017). Research Interests: Natural Language Processing Machine Learning Text and Speech Processing Sentiment and Emotion Analysis Hate Speech Detection Social Media Analytics Automatic Speech Recognition and Transcription His recent publications reflect a strong focus on applying NLP and machine learning to social media, with particular emphasis on hate speech detection, sentiment analysis, and user behavior modeling. He has also contributed significantly to speech processing, including punctuation restoration and prosody modeling, and to digital humanities through medieval text analysis. His work spans both technical innovation and real-world applications in tourism, finance, and public discourse. Scientific Recognition: Senior Member of IEEE (since 2016) Member of ISCA (International Speech Communication Association) Fernando Batista actively advises numerous PhD and Master’s students, supervising research in areas such as generative AI, hate speech detection, sentiment analysis, and economic forecasting. He has coordinated research projects like SPEDIAL and AppRecommender and is involved in organizing major conferences including PROPOR, EAMT, IPMU, and the Lisbon Machine Learning Summer School (LxMLS), where he has served in editorial and technical roles. Research Labs and Teams: He is a key member of the HLT@INESC-ID research group, contributing to its leadership and scientific direction. This group focuses on human language technologies, including speech processing, natural language understanding, and multilingual systems.

• Manufacturing Management
• Production Planning
• Production Control
• +14 more

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).

Iolanda Costa GalinhaView profile

Assistant Professor

• Subjective Well-Being
• Cognitive Function
• Happiness
• +12 more

Iolanda Costa Galinha is an Assistant Professor at the Faculty of Human Sciences, University of Porto, and a researcher at the Research Centre for Psychological - Family and Social Wellbeing (CRC-W). She holds a PhD in Psychology from the University of Porto, awarded in 2006, with a focus on cognitive, temperamental, and contextual factors of subjective well-being. Institution: University of Porto School: Faculty of Human Sciences Research Unit: Research Centre for Psychological - Family and Social Wellbeing (CRC-W) Academic Rank: Assistant Professor Her research is centered on psychological and social well-being, with a strong emphasis on subjective well-being, authenticity, cognitive function, and socioemotional development across the lifespan. She investigates both children and older adults, applying intervention-based methodologies such as guided imagery for schoolchildren and community singing programs for the elderly. Recent publications (2023–2025) reflect a consistent trend in randomized controlled trials assessing psychosocial and physiological outcomes of behavioral interventions. Her work integrates psychological theory with public health applications, particularly in educational and community settings. Keywords across her research include socioemotional learning, cognitive function, mental health, authenticity, and intervention efficacy. While no formal awards are listed in the provided text, her extensive publication record and leadership in multiple RCTs indicate significant scholarly impact. She has not received any explicitly mentioned scientific awards in the source material. Iolanda Costa Galinha supervises research and contributes to academic training, though specific student names are not listed. She has secured research activity over two decades, with continued output through 2025. Her work involves interdisciplinary collaboration, particularly in health psychology, gerontology, and education. She is involved in research labs and teams focused on psychological well-being, including the CRC-W, where she contributes to projects on mental health, cognitive development, and community-based interventions. Her recent trials (e.g., MindRegulation, Sing4Health) suggest leadership in designing and evaluating innovative psychosocial programs.

• Artificial Intelligence
• Medical Informatics
• Data Mining
• +3 more

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.

• Education
• Pedagogy
• Teacher Education
• +10 more

J.F. Matos is a Professor at the Faculty of Social Sciences, Education and Administration (FCSEA) of Lusophone University, Portugal. His work focuses on education, pedagogy, teacher training, and digital education , with a strong emphasis on integrating technology into teaching practices and curriculum design. Education: PhD in Mathematics Education, University of Lisbon (1988–1991) Research Interests: Matos is active in research methodology, educational technology, virtual reality pedagogy, and policy analysis . His projects like ReMASE and EDU-LAB explore innovative frameworks for teacher training, work-based learning, and labor market alignment. Scientific Output Trends: Recent work includes immersive virtual reality pedagogical models, digital textbook implementation in Madeira, and collaborative research on educational methodologies in Portugal. His publications span peer-reviewed journals, commissioned reports, and books , reflecting interdisciplinary collaborations. Projects: EDU-LAB (2022–2027): Focus on work-based learning and investment policy. ReMASE (2022–2023): Analyze research methods in advanced education studies. Collaborations: Matos works with institutions like the European Research Executive Agency and COFAC , leveraging international networks to address educational challenges in Portugal and beyond.

Rui PradaView profile

Professor

• Artificial Intelligence
• Game Development
• Affective Computing
• +4 more

Rui Prada is a Full Professor at the Department of Computer Engineering, Instituto Superior Técnico, University of Lisbon. His research focuses on Artificial Intelligence , Game Development , and Human-Machine Interaction , with emphasis on socially intelligent agents and affective computing. His work explores Multi-Agent Systems , XR Testing , and Educational Game Design , particularly for neurodiverse populations. Recent publications highlight Procedural Content Generation , Human-AI Collaboration , and Social Power Dynamics in agent-based systems. Scientific contributions include the Best Poster Award and leadership in projects like PartiPlay and RAGE , advancing Inclusive AI and Game Technologies Marketplace frameworks.