Nuno Correia is an Associate Professor in Digital Transformation at Tallinn University , with affiliations including Aalto University (visiting lecturer) and ITI/LARSyS (associated researcher). He holds a PhD in Art and Design in New Media from Aalto University (2013) and has taught at multiple institutions globally since 2000. Research Interests : Human-Computer Interaction (HCI), Sound and Music Computing, Multisensory User Experience, Media Art and Design. His work bridges interactive technology with dance, digital art, and AI applications, focusing on performance ecologies, screen scores, and VR environments. Scientific Awards : Best paper award at ACM DIS 2022 Tallinn University best article in exact sciences 2022 Recent Trends in Articles : 2024 papers on AI-driven dance interaction; 2023 work on multisensory feedback systems; 2022 studies on body mapping and composite animation; 2021 contributions to hackathons, screen scores, and VR design; 2020 projects on live motion capture and glitch workflows. Creative Contributions : Co-founder of SIIDS symposium; organizes art-science residencies (e.g., Bio Elektron, MODINA project); collaborates with Eesti Kontsert on brain-wave visualization performances.
Rafik Goubran is a Professor in the Department of Systems and Computer Engineering at the Faculty of Engineering and Design, Carleton University. He holds the distinguished title of Chancellor’s Professor and currently serves as the Vice-President (Research and International). He earned his Ph.D. from Carleton University and is a licensed Professional Engineer (P.Eng.). His research expertise spans digital signal processing, biomedical engineering, audio processing, and the development of smart environments for senior independent living, with applications in patient monitoring, sensor systems, and real-time analytics. Dr. Goubran's recent publications highlight a strong focus on applying machine learning and sensor technologies to healthcare challenges, particularly in gerontechnology. His work involves non-invasive monitoring of sleep apnea, cognitive decline, driving behavior in older adults, and ambient health monitoring using smart homes and IoT systems. He explores innovative methods such as using pressure mats, audio analysis, and video magnification for vital sign detection and behavioral assessment. Life Fellow, IEEE Fellow, Canadian Academy of Engineering (CAE) Chancellor’s Professor, Carleton University Dr. Goubran has co-supervised 24 Ph.D. and 72 Master’s students and has secured significant research funding from NSERC, CIHR, NCE, and OCE for projects related to aging, health monitoring, and smart technologies. He is the co-leader of the TAFETA project and was the founding Director of the Ottawa-Carleton Institute for Biomedical Engineering. His work involves extensive collaboration with institutions like the Bruyère Research Institute and industry partners such as QNX and BlackBerry. He leads a research lab focused on technology-assisted environments, developing systems for patient monitoring, fall detection, and cognitive assessment, contributing significantly to the field of assistive and ambient intelligence for healthcare.
Professor Georgios Leontidis is a Professor of Machine Learning at the University of Aberdeen, where he serves as the Interdisciplinary Institute Director for AI & Big Data and co-Director of the £10.9M UKRI AI CDT SUSTAIN. He is a member of the ELLIS Society and a Turing Academic Liaison, actively shaping national and international AI research agendas. His research expertise lies at the intersection of theoretical and applied machine learning, with key interests in capsule networks, domain adaptation, self-supervised learning, federated learning, and generative AI. His work addresses real-world challenges in environmental monitoring, agrifood sustainability, industrial systems, healthcare, and space science. The recent publications highlight a strong trend in developing novel AI architectures (e.g., OmniNet, Masked Capsule Autoencoders), advancing federated and self-supervised learning methods, and applying AI to sustainability (e.g., greenhouse gas accounting, yield forecasting) and scientific discovery (e.g., lunar radar analysis). His work increasingly integrates ethics, policy, and human-AI interaction, as seen in studies on bias amplification and AI copyright. TMLR - Action Editor ICLR 2025 - Area Chair NeurIPS 2024, 2025 - Area Chair Best Area Chair award, NLDL 2025 Shortlisted for Outstanding Contribution to Accessibility and Inclusivity in Blended Learning (2021) Ranked in Top 4% of EPSRC Full Peer Review College NeurIPS top 10% Reviewer (2020, 2023) Best PhD Paper Award at FISA 2019 (supervised student) Leontidis supervises 14 PhD students and manages 4 research fellows. He leads or co-leads major funded projects from UKRI, EPSRC, EU, and industry partners including Siemens and Tesco, with total funding exceeding £10 million. His collaborative network spans institutions in the UK, Sweden, Switzerland, Greece, Spain, and the Czech Republic. He is actively involved in research infrastructure and policy, serving as External Examiner at Cranfield and Hull Universities, member of the EPSRC Full College, and contributor to the UK AI Council’s Data Working Group. He also co-organized BMVC 2023 and chairs the BMVA Summer School.
Dr. Alvitta Ottley is an Assistant Professor in the Department of Computer Science & Engineering at Washington University in St. Louis, with a courtesy appointment in the Department of Psychological & Brain Sciences. Her research focuses on interdisciplinary approaches to visualization systems, machine learning, and cognitive science to enhance decision-making in healthcare, intelligence analysis, and scientific discovery. She leads the AIR-D Summer Science Camp, a program aimed at underrepresented high school students in STEM. Education: PhD and MS in Computer Science from Tufts University (2016, 2013). Research Interests: Developing adaptive visualization systems that account for users' cognitive traits and goals. Her work integrates AI-driven insights with human factors to create context-aware interfaces. Recent studies explore trust dynamics in visualizations, cross-cultural visualization literacy, and the impact of chart types on legal decision-making. Awards: NSF CRII Award (2018), NSF Career Award, EuroVis Early Career Award (2022), and multiple best paper recognitions at top visualization conferences. Grants & Advising: Active in mentoring students and securing grants such as the NSF CAREER Award for context-aware systems. Her work on medical decision-making visualization received NSF support in 2018. Labs & Teams: Affiliated with the Division of Computational & Data Sciences and the Center for Trustworthy AI in CPS, focusing on ethical AI integration in visual analytics.
Astrid Heidemann Lassen is an Associate Professor at the Department of Materials and Production, Faculty of Engineering and Science, Aalborg University. Her research focuses on Industry 4.0, manufacturing innovation, digital transformation, and knowledge transfer, particularly in SME contexts. She leads and participates in projects such as The Circular Factory - CIFA and Innovation Factory North , emphasizing sustainable production and workforce upskilling. Lassen has co-authored over 174 publications and received the Broman Foundation Scholarship in 2024. Her work bridges academic research with practical industry challenges, addressing topics like exoskeletons in construction, robotization of manufacturing, and barriers to digital transformation. She actively contributes to peer review for journals like Sustainability and Journal of Manufacturing Technology Management . Research Interests: Her primary areas include Industry 4.0 implementation, manufacturing process innovation, and the impact of digitalization on SMEs. She explores themes such as absorptive capacity enhancement, learning factories, and the integration of IoT and robotics in production systems. Recent work highlights challenges in adopting exoskeleton technology and the thematic analysis of robotization's societal implications. Publications Trends: Her articles (2023–2025) address Industry 4.0's challenges, SME digitalization barriers, and the role of learning factories in upskilling. Notable themes include heuristic models for innovation processes, pharmaceutical manufacturing insights, and thematic analyses of manufacturing work dynamics. Over 42 downloads of her 2025 Manufacturing Innovation for Industry 4.0 paper underscore its relevance. Grants & Awards: The 2024 Broman Scholarship recognizes her contributions to research and entrepreneurship. She coordinates projects worth millions in funding, including AddSmart (2022–2025) and CICMa (2025–2026), focusing on circular industrial materials and smart production systems. Labs & Collaborations: Engaged in cross-disciplinary initiatives like the Innovation Factory North , she collaborates with industry partners to design practical solutions for manufacturing challenges. Her work often involves case studies and thematic analyses to address real-world implementation gaps.
Ralf Hagemann is a Lecturer/Research Associate at Osnabrück University of Applied Sciences, specifically within the Faculty of Engineering and Computer Science . His academic work combines Embedded Systems , Software Engineering , and innovative teaching methods like Problem-Based Learning . He actively develops educational hardware and tools for engineering education. Embedded Systems Board design (STMNucleo32-Baseboard) Problem-oriented curriculum development for computer science students Qt-based visualization frameworks for algorithm training His research spans geometric algorithms (2013 dissertation), digital signal processing (1991 thesis), and domain-specific programming languages (1997 PIPL invention). Recent publications focus on multicultural engineering education and cost-effective product development . As a part-time faculty member , he leads technical workshops and contributes to European Project Semester initiatives. His 1991 Diplomarbeit at Fachhochschule Bielefeld laid foundations for his work in hardware-software integration . He regularly demonstrates his MpC-Bildschirmstellwerk software at international model railway exhibitions (2008-2016) and has published in journals like MIBA digital Extra and Eisenbahn Kurier .
Caterina Moruzzi is a Chancellor's Fellow in Design Informatics at the University of Edinburgh's School of Design and a BRAID Research Fellow. Since 2024, she has led the research cluster 'Creativity, AI, and the Human' at the Edinburgh Futures Institute, examining the intersection of philosophy, art, and artificial intelligence to advance responsible human-AI co-creativity. Her educational background includes: PhD in Philosophy, University of Nottingham (2018) Artist Diploma in Piano Performance, Conservatorio G.B. Martini, Bologna (2014) Moruzzi's research investigates shared agency between humans and AI systems, disruptive impacts of technology on creative labor, and ethical frameworks for AI integration in artistic practices. She analyzes how emerging technologies transform creative workflows while developing methodologies to ensure AI tools uplift rather than undermine creative professionals, with particular focus on embodiment and aesthetic value in human-machine co-creation. Her 2025 publications reveal converging trends in AI creativity research: critical examination of provenance data ethics, philosophical foundations of imagination-creativity relationships, and systemic analysis of AI's role in creative domains. These works collectively address authenticity challenges in AI-generated content, value systems for creatives, and human-centric design principles. Her scientific recognition includes: Best Paper Award at C&C 2025 for 'Content Authenticities' Moruzzi directs significant research initiatives including the AHRC-DFG-funded 'Embodied Agents in Contemporary Visual Art' project with Goldsmiths College, and leads collaborations with the Oxford Internet Institute and Adobe Research investigating public attitudes toward algorithmic content creation. These projects examine societal implications of AI through interdisciplinary lenses, securing sustained funding for ethical AI development. She co-founded the 'Creativity, AI, and the Human' research cluster at Edinburgh Futures Institute and organized the 2022 International Conference of Computational Creativity workshop 'The Role of Embodiment in Human & Artificial Creativity'. Her BRAID fellowship facilitates cross-institutional collaboration between Edinburgh College of Art and the School of Informatics, driving experimental work in embodied AI-art interfaces.
Xiangyang Xue is a Professor at Fudan University in Shanghai, China, with an extensive research portfolio spanning computer vision, machine learning, and artificial intelligence. His work demonstrates significant contributions to object-centric representation learning, 3D reconstruction, person re-identification, and semantic segmentation. With over two decades of publication history from 1999 to present, he maintains an active research program with numerous collaborations, particularly with researchers like Yanwei Fu, Bin Li, and Yu-Gang Jiang. Professor Xue's research interests focus on advancing computer vision through innovative approaches to object-centric representation learning, 3D scene understanding, and multi-modal learning. His recent work explores the integration of large vision-language models with 3D understanding, diffusion models for data synthesis, and brain-inspired approaches to robotic scene understanding. His research bridges theoretical advances with practical applications in robotics, autonomous systems, and security. Analysis of his recent publications (2023-2026) reveals a strong trend toward multi-modal learning, with increasing integration of vision-language models, 3D understanding, and diffusion-based generation techniques. His work shows a progression from traditional computer vision problems toward more complex, embodied AI challenges that require understanding of both visual scenes and their semantic interpretations. Key themes include object-centric representations, cross-modal alignment, and the application of these techniques to robotics and security domains. Professor Xue has mentored numerous researchers through collaborative projects, with extensive co-authorship indicating a strong advising presence. His work spans multiple funding areas including NSF-supported research in computer vision, AI security, and robotics applications. His publications appear consistently in top venues including CVPR, ICCV, ECCV, AAAI, and IEEE TPAMI. His research group appears to focus on computer vision and machine learning, with particular emphasis on object-centric scene understanding, 3D reconstruction, and person re-identification systems. The team works at the intersection of theoretical computer vision and practical applications, with projects spanning autonomous driving, robotics, security systems, and human-computer interaction. Recent work suggests active exploration of large vision-language models and their integration with 3D scene understanding.
Fazleena Badurdeen is a Professor of Mechanical Engineering and Director of Graduate Studies for the Manufacturing Systems Engineering Program at the University of Kentucky , where she leads research in sustainable manufacturing and supply chain systems. She holds a Ph.D. and M.S. in Industrial Engineering from Ohio University, an M.B.A. from the Post Graduate Institute of Management, and a B.Sc. in Engineering from the University of Peradeniya. Research Interests: sustainable manufacturing, lean systems, supply chain modeling, and sustainable product design. Awards: Earl Parker Robinson Chair Professor in Mechanical Engineering. Notable Contributions: development of frameworks for product sustainability, circular economy integration, and risk assessment tools using Bayesian networks and simulation. Her recent Google Scholar publications focus on additive manufacturing , digital product passports , and real-time defect detection , with keywords spanning sustainable manufacturing, systems engineering, and environmental metrics. She has also contributed to education through curriculum development in systems thinking and graduate program leadership.
Carlos Zednik is an Assistant Professor for Philosophy of Artificial Intelligence at Eindhoven University of Technology , affiliated with the Industrial Engineering and Innovation Sciences department. He leads the Eindhoven Center for Philosophy of AI and participates in the alignAI (ERC) and ROBUST AI (NWO) consortia. His work bridges philosophy with AI and neuroscience, focusing on explainable AI (XAI), mechanistic explanation, and cognitive modeling. Education: BSc in Computer Science and Philosophy, Cornell University MSc in Philosophy of Mind, University of Warwick PhD in Cognitive Science, Indiana University Bloomington Zednik’s research investigates philosophical questions about biological and artificial intelligence, emphasizing: Methodological principles in cognitive psychology and neuroscience Norms and best practices for XAI in machine learning Knowledge representation in transformer models and large neural networks His recent publications explore the integration of cognitive models into XAI, the role of Bayesian reverse-engineering in cognitive science, and the mechanistic explanation of network neuroscience. Zednik also contributes to international standardization efforts through ISO/IEC TS 6254 and DIN SPEC 92001 . Scientific Awards include fellowships from: DAAD Alexander-von-Humboldt Foundation StandICT Fellowship Zednik supervises PhD students Zeynep Kabadere , Michela Ghezzi , Céline Budding , Miriam Gorr , and Hannes Boelsen , while mentoring postdocs Manuel Barbosa de Oliveira and Philippe Verreault-Julien . His teaching spans philosophy of AI, ethics of machine learning, and decision theory, with innovation projects on generative AI in higher education.
Dr. José María Alonso Moral is an Associate Professor at the Department of Electronics and Computation of CiTIUS-USC (Research Center for Intelligent Technologies) at the University of Santiago de Compostela. With a PhD in Telecommunication Engineering from Universidad Politécnica de Madrid (2007) and a 'Doctor Europeus' distinction, he has held prestigious positions including Ramón y Cajal researcher (2018-2022), Juan de la Cierva postdoctoral researcher (2012), and served as President of the European Society for Fuzzy Logic and Technology (EUSFLAT) and Vice-Chair of IEEE Computational Intelligence Society's Explainable Fuzzy Systems Task Force. IEEE Senior Member Associate Editor: IEEE Computational Intelligence Magazine (Q1) and International Journal of Approximate Reasoning (Q2) Board Member: ACL SIGGEN (2019-2022) His research focuses on Explainable AI and Trustworthy Artificial Intelligence , particularly through interpretable fuzzy systems and natural language generation. Key contributions include the ExpliClas web service for decision tree explanations and JFML library for IEEE 1855-2016 fuzzy system modeling. Recent publications examine counterfactual explanations, fuzzy temporal constraint networks, and feature attribution faithfulness metrics. He leads projects like TRUST (Trustworthy AI) and ReproHum (NLP Evaluation Reproducibility), emphasizing human-centered AI design and cross-disciplinary applications in healthcare and education. As an educator, he developed high school workshops on explainable AI fundamentals through CiTIUS-USC's STEM outreach program. His technical work includes developing explainable classifiers for Alzheimer's disease progression and implementing fuzzy logic systems in embedded platforms like Arduino and Raspberry Pi.
Professor Peter Roßbach is an academic at the Frankfurt School of Finance & Management , specializing in General Business Administration with emphasis on Applied Business Informatics and Information Technology. His career spans over three decades in academia and banking IT research. Diploma in Economics from Philipps University Marburg (1985) Doctorate in Business Administration (1990) Habilitation in Business Informatics (1998) His research focuses on Database Technologies , Machine Learning , IT Security , and Blockchain , with over 30 publications addressing financial technology, cybersecurity, and data analytics. Recent work explores algorithmic interpretability, blockchain security, and human factors in cybersecurity. Key publication trends include: Machine Learning applications in banking (2017-2020) Blockchain implications for financial systems (2016-2018) IT Security in online banking (2012-2015) Crowdfunding and fintech innovations (2013) Regulatory compliance in banking (2014) Roßbach is actively involved in academic societies: Deutscher Hochschulverband , VHB , and WKWI . He teaches courses in Digital Business Security , Analytics , and Business Modeling , with office hours available by appointment.
Jürgen Ziegler is a Senior Full Professor at the Department of Computer Science and Applied Cognitive Science within the Faculty of Computer Science at the University of Duisburg-Essen. He leads the Interactive Intelligent Systems Group, focusing on human-computer interaction, recommender systems, and explainable AI. His work emphasizes transparency, user control, and interdisciplinary collaboration with industry partners. He earned his doctoral degree from the University of Stuttgart, specializing in formal user interface design methodology. Prior to his current role, he headed the Competence Center for Software Technology and Interactive Systems at the Fraunhofer Institute for Industrial Engineering (IAO) in Stuttgart. He also served as Editor-in-Chief of the journal i-com - Journal of Interactive Media from 2001 to 2021. Ziegler’s research bridges academic and industrial domains, with applications in e-commerce, health, social media, and automotive systems. He investigates how to make intelligent technologies more transparent and user-controllable, particularly in conversational recommender systems, personalized interfaces, and social media analytics. His work integrates visualization techniques and semantic data models to enhance user experience. His recent publications focus on multistakeholder evaluation frameworks, explainable AI, and the integration of conversational agents with traditional interfaces. These studies explore domains like health promotion, smart environments, and education, using methods such as knowledge graphs, generative AI, and interactive sliders for feature dependency visualization. Ziegler founded and co-chairs the German Special Interest Group on User-Centred Artificial Intelligence. He has contributed to funded projects like SPIDER, FairWays, and PAnalytics, which address polarization in social networks, interactive recommendation, and health support systems. His leadership roles include organizing international workshops on explainable user models and user-centered AI. He supervises PhD students and advises on projects related to recommender systems, mental models, and user interaction preferences. His team collaborates on multi-method approaches for transparent decision support and the development of tools for measuring user perception of recommendation transparency. Labs and teams under his direction include the Interactive Intelligent Systems Group, which develops demonstrators like AR-based shopping advisors and hybrid recommendation frameworks. His work emphasizes both theoretical advancements and practical implementations across diverse application scenarios.
Utz Roedig is a Full Professor of Computer Science at University College Cork (UCC), Ireland, and a Principal Investigator at the CONNECT Centre. Previously, he served as Professor at Lancaster University, UK, leading the Academic Centre of Excellence in Cyber Security Research (ACE-CSR), and held research positions at UCC and Darmstadt University of Technology, Germany. Education: Dipl.-Ing in Engineering from Darmstadt University of Technology Dr.-Ing (Doctor of Engineering) from Darmstadt University of Technology His research spans computer networks and network security , with over 150 publications in IoT security, industrial control systems, 5G networks, and voice assistant vulnerabilities. Recent work integrates machine learning for intrusion detection and fault prediction while addressing human factors in secure coding. Industry collaborations have yielded multiple patents. Analysis of 2023-2025 publications reveals dominant themes in industrial IoT security (e.g., resilient time-sensitive networking), 5G infrastructure protection, and voice assistant threats (wake word jamming/spoofing). His team develops countermeasures using protocol design and ML-driven anomaly detection, with growing emphasis on human-centric security challenges. Scientific Awards: No specific awards are documented, though research impact is evidenced by patents and sustained funding from major international bodies. Advising and Grants: Secured funding from EU, EPSRC, and industry partners. Serves as grant reviewer for EPSRC (UK), ESF (EU), and FWO (Belgium), and on TPCs for DCOSS, EWSN, and IPSN conferences. Student supervision details are unavailable, but research leadership implies active mentoring. Grants: EU, EPSRC, Industry Review Roles: EPSRC, ESF, FWO Labs and Teams: Leads research at UCC's CONNECT Centre (telecommunications security). Previously directed Lancaster University's ACE-CSR, a UK government-designated cybersecurity research hub.
Christoph Rosenkranz is a Professor of Information Systems at the Faculty of Management, Economics and Social Sciences , University of Cologne. He serves as Academic Director of the Bachelor's program in Business Informatics and Deputy Managing Director of the Cologne Institute for Information Systems . His research focuses on agile software development , digital transformation , and socio-technical systems , with applications in healthcare and business process management. Academic Director, Bachelor's program 'Wirtschaftsinformatik' (2021–present) Founding Director, Master's program 'Business Analytics and Econometrics' (2019–2021) Visiting Researcher at Towson University and Rochester Institute of Technology (2018) His work bridges information systems , project management , and digital innovation , with empirical studies on: Agile practices in software development Time pressure and software quality Communication theory in IS design Electronic healthcare systems Service network effects Recent publications analyze digital market offerings , ethics in machine learning , and psychological safety in teams . He contributes to the ECONtribute: Markets & Public Policy cluster, researching digital transformation's societal impact. Collaborative projects include: HPDnet (DFG-funded child healthcare networks) C-SEB (Social and Economic Behavior research)
