Hubert Zangl is a Professor at the University of Klagenfurt and Head of the Institute for Intelligent System Technologies . He serves as Chairman of the Information Technology Curricular Commission and participates in the Faculty Conference of the Faculty of Technical Sciences. Key research areas include: Sensor technology Electrical measurement technology Robotics Signal processing Electronics Recent research trends focus on: High-fidelity FMCW radar simulation frameworks Energy-efficient sensor systems Printed electronics for structural health monitoring Uncertainty propagation in measurement science Modular robotics with secure transducer identification Capacitive tactile sensing for robotic grasping Contact: Hubert.Zangl@aau.at
Hedvig Kjellströmeröm is Professor at KTH Royal Institute of Technology and affiliated with the Max Planck Institute for Intelligent Systems. Her research develops methods for interpreting human and animal behavior through computer vision, with applications in computational aesthetics, communicative behavior analysis, and embodied AI. She serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025.
Victoria C. Ramenzoni is an Assistant Professor in Marine Policy and Social Science at Rutgers University, leading the Coastal Communities Adaptation Lab. Her research focuses on socioecological systems, adaptation strategies, and environmental policy, with fieldwork in the U.S., Cuba, and Indonesia. She investigates how households adapt to environmental and socioeconomic uncertainty, emphasizing resource governance and nutritional health. Ramenzoni has secured grants from the NSF and NOAA, including a 2021 Coast and People grant studying climate adaptation in Northeast U.S. marginalized communities. She previously served as Executive Secretary of the Interagency Working Group on Ocean Social Sciences (IOSSWG) and contributed to NOAA’s socioeconomic indicator frameworks. Her work bridges anthropology, ecology, and policy to address climate change impacts on coastal livelihoods. Her research spans multiple regions: in the Northeast U.S., she examines commercial fishing adaptations during the pandemic and urban development pressures. In Cuba, she collaborates with Universidad de La Habana on dietary health and hurricane resilience in Yaguajay. In Indonesia, her studies in Flores and Kalimantan explore overfishing, peatland degradation, and traditional ecological knowledge. She employs ethnographic methods, nutritional assessments, and institutional analyses to evaluate long-term adaptation pathways. Ramenzoni’s grants include a National Academies-funded study on offshore extractive activities’ impacts in the Gulf of Mexico and a Texas Commission-backed project on socioecological indicators. She advocates for co-governance models and has published extensively on adaptation frameworks, socioecological monitoring, and the paradoxes of development in oil-dependent regions.
Ingrid E.J. Heynderickx is a Professor in Applied Visual Perception at the Human-Technology Interaction group within the Faculty of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (TU/e), where she also serves as Dean of the Department. She holds a part-time Visiting Research Professor role at Southeast University (China) since 2005. Her research focuses on optimizing display and lighting systems through understanding human visual perception, emphasizing both fidelity and preference in design, with attention to age and cultural variability. Academically, she earned her PhD in Physics from the University of Antwerp (1986) and spent 18 years at Philips Research, leading visual perception research. She became a Philips Research Fellow in 2005 before joining TU/e as Full Professor in 2013. She holds Fellow status with the Society for Information Displays (SID) and received the Otto Shade Prize (2015). Her recent work explores lighting solutions for office environments, roadway safety systems, and LED artifact mitigation. Notable projects include the Brainbridge initiative (2015–2016) on spectral lighting effects. Over 236 publications and 4 datasets reflect her contributions to lighting science and human-centric design. She advises on sustainable lighting technologies and collaborates globally, with recent media engagements discussing departmental leadership and smart lighting trends. Key research themes include visual attention modeling, illuminance preferences, and dynamic viewing behavior—issues critical for next-generation human-technology interfaces.
Lu Su is an Associate Professor at the School of Electrical and Computer Engineering , Purdue University , with prior appointments at SUNY Buffalo . His research spans Internet of Things , cyber-physical systems , mmWave sensing , and crowd-sourced data validation , focusing on quality-of-information aware distributed sensing and security in autonomous systems . Ph.D. in Computer Science (2013) and M.S. in Statistics (2012) from University of Illinois at Urbana-Champaign M.E. and B.E. from Harbin Institute of Technology Research Interests: IoT , cyber-physical systems , crowd sensing , security and privacy , and machine learning for sensor networks. His work addresses quality-aware information integration , adversarial attacks in autonomous vehicles , and privacy-preserving crowd-sourced systems . Recent publications focus on mmWave-based sensing (e.g., 3D pose reconstruction), federated learning (driver monitoring), and data poisoning attacks in crowd-sourced systems. His research also extends to traffic optimization and human activity recognition using wireless networks. Professional Roles: Workshop Chair (INFOCOM 2023, 2022) TPC Vice Chair (INFOCOM 2021) Program Committee Member for top conferences Editorial Board, ACM Transactions on Sensor Networks Teaching: Courses on Embedded Systems , Internet of Things , and Network Concepts at both undergraduate and graduate levels.
Wei Pang is a Professor of Computer Science and Bicentennial Research Leader at the School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh. He leads the BCML Lab and is affiliated with the Edinburgh Centre for Robotics and National Robotarium. His expertise spans bio-inspired computing, machine learning, and AI applications in healthcare, robotics, and sustainability. Pang holds a PhD in Computing Science from the University of Aberdeen, with prior roles including Senior Lecturer at the University of Aberdeen and research fellowships in systems biology. Affiliations: Heriot-Watt University, Edinburgh Centre for Robotics, National Robotarium Education: PhD in Computing Science (2009), MEng (by research), BSc (Jilin University, China) Research Interests: Bio-inspired computing (e.g., artificial immune systems, swarm intelligence), machine learning (deep learning, explainable AI), healthcare applications (medical imaging, disease detection), and interdisciplinary projects in robotics and environmental science. His work addresses challenges in robust AI, fairness, and accountable machine learning. Recent Projects: EPSRC-funded RAIns and MI projects, CRUK-funded Endo.AI, and PRIME project on minority ethnic communities' digital experiences. His research has secured over £10M in grants, including £3.5M institutional funding. Awards: Scottish Crucible Award (2015), ADMA Best Paper Runner-Up (2016), EPSRC PRIME Award (2024) Grants/Advising: Supervised 12 PhD completions; contributed to £10M+ external funding. Labs/Teams: BCML Lab (focusing on bio-inspired AI), collaborations with Oxford, Cambridge, and industrial partners like Weather2 and Data2Text.
Prof. George Magoulas is a Professor of Computer Science at the University of London's School of Computing and Mathematical Sciences and Director of the Birkbeck Knowledge Lab. He specializes in machine intelligence, machine learning algorithms, and AI system architectures, with applications in healthcare (e.g., neurodegenerative disease diagnosis) and educational technologies. His research has received awards from IEEE, ACM, and others. He holds a PhD in Nonlinear Optimization for Neural Networks and a PGCE in Higher Education. Education: BEng/MEng (Integrated Master's in Systems & Control Engineering), University of Patras, Greece PhD in Nonlinear Optimization for Neural Networks Learning, University of Patras, Greece PGCE in Teaching and Learning (Higher Education) Research & Leadership: He leads the Birkbeck Knowledge Lab, focusing on AI's impact on learning and communication. His work includes designing learning algorithms for psychophysiological data modeling and developing the cloudUPDRS app for Parkinson's disease assessment. He has supervised over 12 PhD students and contributed to 200+ publications. Awards & Recognition: Stanford’s “World’s top 2% of Scientists” (2024) Best Paper Awards at IEEE, ACM, and EUNITE Keynote speaker at major AI and e-learning conferences Honorary membership in the Hellenic Artificial Intelligence Society Administrative Roles: Director of Teaching & Learning Quality (2016–2023) Chair of Postgraduate Programmes Exam Board (2010–2022) Editor-in-Chief, International Journal on Artificial Intelligence Tools Teaching: He teaches courses on Artificial Intelligence, Neural Networks, and Project Management at both undergraduate and postgraduate levels. Labs & Collaborations: He directs the Birkbeck Knowledge Lab and is a member of the Data Science and AI Research Group. His projects include analyzing violent cycles using AI and collaborating on EU-funded initiatives.
Joel Mero is an Associate Professor at the School of Business and Economics, University of Jyväskylä , leading the Digital Marketing and Communication (DMC) research group and directing the International Master's Program in Digital Marketing and Corporate Communication (DMCC) . He holds a D.Sc. (Econ.) from Jyväskylä University (2016) and has designed over 20 courses across 10 institutions, covering all academic levels from Bachelor to Doctoral. His research focuses on B2B digital marketing management , particularly leveraging digital data and technologies in business markets. Notable achievements include two Best Paper Awards (2017 & 2019) in the Industrial Marketing Management journal. His work explores topics such as influencer marketing, big data analytics, marketing agility, and AI-driven strategies. Current research groups include the Sound Science Lab (music perception) and Digital Marketing and Communication (DMC) . He collaborates on projects like the Finnish Quantum Flagship , aiming to advance quantum technology applications. Mero emphasizes practical applications of digital tools, bridging academic insights with industry needs. Publications span conceptual frameworks, empirical studies, and industry guides, with a focus on B2B customer journeys, AI in content creation, and data-driven decision-making. His teaching and research highlight agility, innovation, and the ethical use of emerging technologies in marketing.
Peter K. Bol is the Charles H. Carswell Professor of East Asian Languages and Civilizations at Harvard University. His research focuses on China's cultural elites from the 7th to 17th centuries, geospatial analysis, and digital humanities projects including the China Historical Geographic Information Systems (CHGIS) and China Biographical Database (CBDB). His research interests include: Intellectual transitions in Tang and Sung China Neo-Confucianism and its historical context Geospatial analysis in historical research Biographical database development Digital approaches to Chinese history Bol has led significant university-wide initiatives including the establishment of Harvard's Center for Geographic Analysis in 2005 and has served as Vice Provost (2013-2018) overseeing HarvardX, the Harvard Initiative in Learning and Teaching, and online learning research.
Prof. Constantin A. Rothkopf is a W3 Professor at the Department of Psychology, Technische Universität Darmstadt, and a secondary member of the Department of Computer Science. He serves as Founding Director of the Centre for Cognitive Science and founding member of the Hessisches Zentrum für Künstliche Intelligenz (hessian.ai). He is also part of the European Laboratory for Learning and Intelligent Systems (ELLIS) and the DAAD Konrad Zuse Schools of Excellence in Artificial Intelligence (ELIZA). His research focuses on the interplay between perception and action, using computational models and experimental studies in humans. Current work includes eye-tracking studies in naturalistic environments, inverse optimal control models, and developing algorithms for virtual agents. Education: Ph.D. in Neuroscience and Informatics from the University of Rochester, followed by postdoctoral research at Frankfurt Institute for Advanced Studies (FIAS). He has held visiting professorships at Central European University (2017) and Columbia University (2023). Awards include an ERC Consolidator Grant (2022) and SCENE Project Funding (2025). Research Interests: Active vision, decision-making under uncertainty, sensorimotor control, and computational modeling. Key themes include how humans use sensory input to form beliefs, make decisions, and act in dynamic environments. Grants/Awards: ERC Consolidator Grant (2022), SCENE Funding (2025) Labs/Teams: Centre for Cognitive Science, hessian.ai, ELLIS Unit Darmstadt
Dr. Paul Henderson is a Lecturer in Machine Learning at the School of Computing Science, University of Glasgow. He holds a BA in Mathematics (University of Cambridge, 2009), an MSc in Informatics (University of Edinburgh, 2010), and a PhD in Computer Vision (University of Edinburgh, 2018). His research focuses on generative AI, probabilistic machine learning, and minimally-supervised approaches to 3D computer vision, with applications in healthcare, computer graphics, and physical sciences. Education: PhD in Computer Vision (University of Edinburgh, 2018) MSc in Informatics (University of Edinburgh, 2010) BA in Mathematics (University of Cambridge, 2009) His work spans generative models, medical imaging, and robotics. Notable contributions include datasets like Flat’n’Fold and techniques in diffusion models for text-to-image retrieval. He has received grants including the Royal Society Research Grant (2022-2023) and the Vesuvius Challenge Autosegmentation Prize (2025). He supervises PhD students in topics such as medical image segmentation and generative AI. Teaching: CS5002 Advanced Programming, CS4061/CS5014 Machine Learning.
Elmira Djafarova serves as the Head of the Marketing Subject Group in the Department of Marketing, Operations, and Systems at Northumbria University's Faculty of Business and Law. She holds a PhD in Tourism and is a Senior Fellow of the Higher Education Academy. Her academic leadership includes roles as Programme Director for Top-Up and Postgraduate Business programmes, focusing on enhancing international student experiences through initiatives like the International Mentoring Scheme. Her research spans digital influencers, social media engagement, consumer behavior, and tourism marketing. Notable contributions include studies on influencer credibility, crisis resilience via digital technology, and Generation Z's ethical consumption patterns. She has authored over 30 journal articles in outlets like *Computers in Human Behavior* and *Tourism Analysis*, and actively reviews for *Tourism Management* and *Journal of Advertising Research*. Research Interests: Electronic Word of Mouth, Social Media Analytics, Crisis Communication, Digital Marketing Professional Roles: Associate Editor for *Journal of Marketing Management*, Programme Chair at the Academy of Marketing Conference (2016) Recent work explores the impact of data usage patterns in Africa and the effectiveness of mindfulness interventions against fake news. She supervises PhD candidates researching cancel culture, showrooming behavior, and university search experiences. Djafarova has presented keynotes at the Operational Research Society and participates in international conferences on marketing innovation and digital transformation.
Roman Kuc is a Professor of Electrical Engineering at Yale University, affiliated with the School of Engineering & Applied Science. He directs the Intelligent Sensors Laboratory, focusing on biomimetic sensors for robotics and bioengineering. His research explores brain-based devices (BBDs), sonar sensing, and neuromorphic processing inspired by biological systems. He holds a BSEE from Illinois Institute of Technology and a PhD from Columbia University. Dr. Kuc’s work bridges signal processing, robotics, and bioengineering, with applications in autonomous systems and clinical diagnostics. He has published over 200 papers and authored textbooks like Electrical Engineering in Context and The Digital Information Age . Notable honors include an honorary doctorate from the Glushkov Institute of Cybernetics and the Yale Sheffield Distinguished Teaching Award. His research themes include cognitive mapping via sonar echoes, neural network-based classification of environmental features, and biomimetic approaches to echolocation. Recent work emphasizes sensorimotor integration and robust performance in uncertain environments. Scientific awards highlight his contributions to robotics, signal processing, and education. His lab develops systems that emulate biological sensory mechanisms, aiming to advance robotics, medical applications, and assistive technologies.
Alberto Viglione is an Associate Professor at the Politecnico di Torino , Department of Environment, Land and Infrastructure Engineering (DIATI), and a member of the Interdepartmental Center SmartData@PoliTO. He has been a faculty member since 2019, following a decade as a Research Fellow at the Vienna University of Technology. University: Politecnico di Torino Department: DIATI – Department of Environment, Land and Infrastructure Engineering Rank: Associate Professor Email: alberto.viglione@polito.it His research focuses on flood hydrology, water resources, and hydro-meteorological extremes , integrating statistical analysis, climate change impacts, land use dynamics, and socio-hydrological modeling. He investigates the spatio-temporal dynamics of climatic, hydrological, and human processes in river basins and their implications for extreme event risks. His work emphasizes data integration, conceptual modeling, and risk assessment across scales. The recent publications highlight a strong trend in analyzing European flood dynamics , the impacts of climate change , and the development of socio-hydrological frameworks that incorporate human behavior and societal memory into flood risk modeling. His research spans from statistical hydrology in ungauged basins to large-scale assessments of climate-flood interactions. Scientific Awards and Honors: AMGA Award for best PhD thesis on water resources (2009) Editorial and Professional Service: Associate Editor, Water Resources Research (2014–present) Associate Editor, Hydrological Sciences Journal (2012–2018) Associate Editor, WIRES Water (2012–2020) Associate Editor, Journal of Hydrology and Hydromechanics (2019–present) Scientific Committee Member, European Geosciences Union (2019–2023) Secretary, International Commission on Water Resources Systems, IAHS (2015–present) Teaching and Advising: He teaches courses such as Bayesian Inference , Applied Hydrology , Fundamentals of Environmental Geosciences , and Hydro-meteorological Risk Assessment . He is a PhD supervisor and member of multiple PhD colleges in Civil and Environmental Engineering at Politecnico di Torino. He currently advises PhD students including Tsion Ayalew Kebede , Emanuele Mombrini , Luigi Cafiero , Luca Lombardo , and Matteo Pesce . His research is supported by grants from national (PRIN), EU, and commercial sources, including projects like Clim2FlEx , RETURN , and ATO4WATER . Research Labs and Teams: He is affiliated with the SmartData@PoliTO laboratory, focusing on big data and data science applications in hydrology and environmental systems.
Stephen Humphrey is the Alvin H. Clemens Professor of Management and Organization at the Smeal College of Business, Pennsylvania State University. His research focuses on social relations at work, with a primary emphasis on teamwork dynamics, negotiation theory, and organizational behavior. He holds a PhD in Organizational Behavior and Human Resource Management from Michigan State University and a BS in Psychology from James Madison University. Professor Humphrey's research explores two core areas: (1) the 'bottom-up' formative design of teams (including composition, role allocation, and reward structures), and (2) the 'top-down' management of existing teams (focusing on temporal dynamics, structural adaptation, and conflict resolution). His work on team microdynamics examines multilevel, multi-period, and multi-theoretical aspects of teamwork. His recent publications demonstrate strong research trends in team dynamics, organizational reputation, negotiation pedagogy, and ethical decision-making. Articles frequently employ meta-analytic approaches and focus on contextual factors influencing team performance across diverse settings. The research consistently bridges theoretical frameworks with practical organizational applications. Professor Humphrey teaches negotiation skills across undergraduate, MBA, EMBA, and executive education programs. He has developed several negotiation simulations derived from real-world scenarios and teaches doctoral seminars on organizational research design. As faculty advisor, he mentors PhD and DBA students in research methodology and academic development.
