Per Vagn Freytag is a Professor at the Department of Business and Sustainability, University of Southern Denmark (DBS Kolding). He leads the Business-to-Business Marketing and Supply Chain Management research group, focusing on collaborative approaches to address societal challenges. Education: Ph.D. in Marketing, Copenhagen Business School (1986–1990) MBA (Marketing), Copenhagen Business School (1982–1985) Bachelor in International Commerce, Sønderborg Business School (1979–1982) His research centers on sustainable business models , market segmentation , and collaborative innovation within water sustainability, digitalization of industries, and cross-sector partnerships. Recent work explores IoT engagement mechanisms, B2B trade show evolution, and climate adaptation technologies. His publications demonstrate trends in business development for environmental challenges, qualitative methodologies , and cross-disciplinary applications in industrial and public sectors. Notable projects include EU-funded PREP4BLUE (2022–2025) and NEPTUN (2020–2023), focusing on water and climate solutions. He actively bridges academic and practical knowledge through part-time master's programs and industry collaborations.
Dr. Julien Meyer serves as Associate Professor at the School of Health Services Management within Toronto Metropolitan University's Ted Rogers School of Management, a position held since 2015. His research critically examines information systems' transformative impact on healthcare delivery, with dual specializations in pathology information systems and digital access improvement initiatives. Education: Ph.D., HEC Montreal MSc in Management, HEC Paris Dr. Meyer's research program investigates how information systems reconfigure healthcare processes through three interconnected streams: AI integration in pathology decision-making (analyzing accountability shifts and professional autonomy), telemedicine expansion for specialized care access (particularly in isolated regions), and mHealth applications for direct patient engagement (studying adoption patterns and user sentiment). His industry experience implementing global IS solutions provides critical context for translating theoretical insights into practical healthcare management strategies. Methodologically, he combines qualitative depth from semi-structured interviews with quantitative rigor in big data analysis and survey research. Teaching emphasizes applied learning through practicum projects where students develop IS solutions for real healthcare management challenges. Dr. Meyer's industry background enables him to effectively contextualize academic concepts within operational healthcare constraints, preparing students to implement meaningful organizational change through information systems.
Alain Hertz is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. He is affiliated with two major research centers: Institut de valorisation des données (IVADO) and Groupe d'études et de recherche en analyse des décisions (GERAD). His expertise spans operations research, management science, and algorithm development with applications across multiple industries. Professor Hertz specializes in combinatorial optimization, graph theory, algorithms, heuristics and metaheuristics. His research bridges theoretical mathematics with practical applications in scheduling, vehicle routing, and decision support systems. Recent work explores graph-based approaches for recommender systems and chemical graph theory, demonstrating the versatility of his mathematical frameworks. His publication record shows consistent output across top journals in operations research and graph theory. Recent articles (2021-2025) focus on extremal graph theory, chemical graphs, graph coloring variants, and applications of graph theory to recommender systems. This demonstrates both theoretical depth and practical relevance in his research trajectory. Prix de la ministre de l'Éducation, du Loisir et du Sport - Gouvernement du Québec (2011) Professor Hertz has supervised 13 doctoral students and 18 master's students, with thesis topics ranging from optimization methods for semi-supervised clustering to wind farm network design. His supervision approach emphasizes both theoretical foundations and practical applications, preparing students for careers in both academia and industry. His research has been supported by various grants enabling collaborative work with international partners. Through his affiliations with IVADO and GERAD, Professor Hertz contributes to interdisciplinary research initiatives that connect mathematical theory with real-world problems in data science, artificial intelligence, and industrial engineering.
Francisco Manuel Espingardeiro Banha serves as a Researcher at the Research Centre for Tourism, Sustainability and Well-being (CinTurs) at the University of Algarve since 2023, while also holding invited lecturer positions at ISEG (Lisbon School of Economics and Management), the University of Algarve, and ISG Business and Economics School. He maintains dual research affiliations with CEFAGE at the University of Évora, focusing on interdisciplinary work bridging economics, education, and tourism policy. His educational foundation includes a PhD in Economics and Management Sciences from the University of Algarve (2020), a Master's in Business Management (1997), and an MBA (1995) from ISEG, complemented by a Bachelor's in Business Organization and Management (1987). This academic trajectory underpins his expertise in entrepreneurship ecosystems and policy implementation. Banha's research centers on entrepreneurship education, public policy decision-making, and tourism-driven economic development, with particular emphasis on the Algarve region. His work investigates barriers in Portuguese entrepreneurship ecosystems, gender disparities among entrepreneurs, and the integration of sustainability goals into business education. Methodologically, he innovates through frameworks like ISM modeling and qualitative-to-quantitative data transformation for policy analysis. Recent publications reveal a strong interdisciplinary trend, with outputs spanning education sciences (focusing on entrepreneurship pedagogy), mathematics (methodological contributions), and tourism journals. His 2022-2024 work shows increasing engagement with European policy frameworks like NUTS III regions while maintaining regional Portuguese case studies. His professional recognition includes: Conselheiro Member of the Order of Economists, Portugal (2023) Banha actively supervises master's students on topics including SME innovation in the Algarve, women entrepreneurship, and business planning for local accommodation. He secures research funding through nationally competitive projects like the current CinTurs initiative (UIDB/04020/2020) and previously contributed to the multi-institutional CEFAGE project (UID/ECO/04007/2019), both funded by Portugal's Foundation for Science and Technology. As a core member of CinTurs, Banha contributes to a collaborative research environment focused on sustainable tourism development. The center provides resources for regional impact studies, policy evaluation frameworks, and entrepreneurship education program implementation—particularly relevant to the Algarve's tourism-dependent economy.
Adam Perer is an Assistant Professor at Carnegie Mellon University within the Human-Computer Interaction Institute . His research focuses on data visualization , machine learning , and human-AI collaboration systems, particularly in healthcare contexts. Co-directs the Data Interaction Group Area Papers Chair at IEEE VIS PhD in Computer Science from University of Maryland Former Research Scientist at IBM Research His work integrates visual analytics with machine learning to create interactive systems for clinical data analysis , AI interpretability , and exploratory data science . Recent publications demonstrate applications in epidemiology , ICU medicine , and child welfare decision-making . Key research themes: Designing collaborative AI interfaces Visualizing embedding spaces for ML Interactive clinical decision support tools Explainable AI systems evaluation Temporal data exploration techniques Awards include Best Paper Honorable Mentions at CHI and EuroVis, plus Most Reproducible Paper recognition. He advises multiple PhD candidates and teaches courses in Data Visualization and Interactive Data Science .
Mehdi Neshat is a Visiting Scholar at the Data Science Institute within the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). He holds a PhD in Engineering from the University of Adelaide (2016-2020) and has extensive experience as a research data scientist specializing in computational optimization methods applied to complex engineering and healthcare problems. His educational background includes: PhD in Engineering, University of Adelaide (2016-2020) Neshat's research focuses on developing and applying advanced computational methods to solve real-world challenges. He specializes in evolutionary algorithms, swarm intelligence, and machine learning techniques for optimizing renewable energy systems, particularly wave and wind energy converters. His work extends to healthcare applications including genomic analysis and medical diagnostics, as well as structural engineering optimization and smart building energy management. His interdisciplinary approach bridges theoretical algorithm development with practical implementation across multiple domains, demonstrating exceptional versatility in computational problem-solving. Analysis of his recent publications reveals a strong trend toward sophisticated ensemble methods and hybrid optimization approaches that combine multiple algorithms to overcome limitations of single-method approaches. His research shows increasing sophistication in handling multi-objective optimization problems, particularly in renewable energy systems where trade-offs between power output, system stability, and cost must be balanced. The geographical focus of his energy research centers on Australian coastal regions, with practical applications for wave and wind farm deployment. Neshat has received significant recognition for his research contributions: Back-to-back Best Paper Prizes at the GECCO conference (2019 and 2020), a CORE A-ranked international optimization and machine learning conference His collaborative research spans multiple institutions and disciplines. Previously, he served as a Postdoctoral Research Associate with the Genomic analysis team at the Australian Centre for Precision Health, Cancer Research Institute, University of South Australia, and as a Senior Research Fellow at the Center for Artificial Intelligence Research and Optimization, Torrens University Australia. His work demonstrates consistent engagement with multidisciplinary teams across engineering, computer science, and healthcare domains, with a strong emphasis on practical implementation of theoretical methods. At UTS, Neshat contributes to the Data Science Institute's research agenda, focusing on applying advanced computational methods to complex real-world problems where traditional analytical approaches fall short. His current work continues to expand the boundaries of optimization techniques for renewable energy systems while exploring new applications in healthcare analytics and structural engineering.
Aurélie Davranche serves as an Associate Professor in Ecology and Spatial Analysis at the University of Angers' Department of Biology since 2011, while maintaining an active international research presence as a Visiting Researcher at the Lammi Biological Station, University of Helsinki since September 2024. Her academic career spans multiple European institutions with significant research contributions in wetland ecology and remote sensing applications. Dr. Davranche's research focuses on nature-society interactions with particular emphasis on developing remote sensing tools for wetland monitoring across diverse landscapes from boreal forests to semi-arid zones. Her multidisciplinary approach combines ecology, geosciences, biogeography and mathematics to create robust models for automated mapping of biophysical parameters and species requirements. She specializes in extracting multispectral and multitemporal data from high-resolution satellite and drone images combined with field surveys to monitor landscapes while minimizing sampling costs. Recent work has expanded into social ecology with art-based protocols to understand social cognition of wetlands and developing pedagogical kits that integrate game, art and science to improve public perception of wetland biodiversity. Analysis of her publication record reveals a consistent trajectory in wetland monitoring using remote sensing technologies, with increasing interdisciplinary integration over time. Her early work focused on technical aspects of remote sensing applications for wetland mapping, while recent publications demonstrate expansion into broader ecological concerns including freshwater browning, artificial light pollution impacts, and social-ecological approaches to wetland management. The work shows strong practical application orientation with direct connections to wetland management needs. Dr. Davranche has secured substantial research funding including the Kone Foundation grant for the POOL project (2022-2025), ANR funding for WETLANDSPACE (2017), and multiple CNRS projects. She leads significant collaborative efforts across European institutions with particular strength in French-Finnish research partnerships. As a research supervisor, Davranche has directed numerous students across multiple projects including 19 Master's students, 1 PhD student, and 1 post-doc for the POOL project alone. Her research group structure typically involves interdisciplinary teams of students, technicians, and researchers from multiple institutions working on complex wetland management questions. Current research activities center around the Lammi Biological Station at the University of Helsinki and the Department of Biology at the University of Angers, with extensive international collaboration networks spanning Europe, Africa, and beyond.
Dr. Sadik Alashan serves as Associate Professor in the Faculty of Engineering and Architecture at Bingol University, Turkey, specializing in Civil Engineering disciplines through teaching courses including Hydraulics, Hydrology, Fluid Mechanics, and Water Resources Structures. His academic journey spans over a decade at Bingöl University with progressive appointments from Research Assistant to current Associate Professor status. Education: Ph.D. in Hydraulic and Water Resources Engineering, Istanbul Technical University (2011-2016) M.S. in Hydraulic Engineering, Firat University (2008-2011) B.S. in Civil Engineering, Dicle University (1999-2003) Research Focus: Dr. Alashan pioneers statistical methodologies for hydrological trend analysis, particularly advancing Sen's Innovative Trend Analysis (ITA) into frameworks like S-IPTA and ITA-NF. His work bridges climate science and water engineering through drought assessment in Mediterranean regions, earthquake recurrence modeling in Eastern Turkey, and machine learning applications for hydraulic structures. Recent publications demonstrate evolution from foundational ITA refinements (2016-2020) toward integrated climate-hydrology frameworks (2023-2025), with increasing international collaboration. Scientific Awards: No major scientific awards listed in the provided information Academic Contributions: Dr. Alashan has co-supervised Master's research on climate impacts to river systems and serves as reviewer for leading journals including Water Resources Management and Natural Hazards. His publication trajectory shows consistent output with 15+ articles in the last five years, primarily in Q1 hydrology/climate journals. While no formal lab is specified, his computational research group focuses on methodological innovation for water resource challenges in semi-arid regions. Research Environment: Based in Bingöl (Eastern Turkey), his work addresses regional water security through earthquake-prone basin studies and Mediterranean drought analysis. His recent shift toward machine learning integration (2025 publications) indicates evolving technical capacity within his research group, leveraging computational approaches to solve practical hydraulic engineering problems.
Prof. Achim Schweikard is a Full Professor at the University of Lübeck's Institute for Robotics and Cognitive Systems, where he has led pioneering research since 2002. His academic journey spans Stanford University's neurosurgery and computer science departments and Technical University of Munich, establishing him as a leading figure in medical technology translation. His research focuses on Medical Robotics and Artificial Intelligence with transformative clinical applications. Key achievements include inventing correlation-based tracking for cancer radiosurgery (now global standard of care) and developing stereotactic arrhythmia radioablation (STAR) protocols. Current projects address critical challenges in cardiac radioablation through the RAVENTA multicenter trial, MATRIX-VT imaging fusion study, and SonoBox robotic ultrasound system for pediatric diagnostics. His publication record shows sustained high impact with 15+ articles in 2023-2025 in top journals including Radiotherapy and Oncology and Heart Rhythm. These works demonstrate progression from foundational robotics to clinical implementation, with recent focus on cardiac motion estimation, target transfer automation, and S-ICD patient treatment solutions. As Academic Director of UNI Luebeck's Grad School (2025), he oversees doctoral training while leading the Robotics Laboratory (RobLab). The lab maintains active grants supporting: RAVENTA trial: German multicenter feasibility study for ventricular tachycardia radioablation DYNAMIC phantom development for end-to-end treatment validation ECG-gated 4D CT motion modeling for precision targeting Landmark-based ultrasound-CT fusion techniques Students gain comprehensive experience across the medical technology pipeline - from hardware prototyping to clinical trial participation - within an internationally collaborative environment spanning the STOPSTORM.eu consortium and multiple EU research networks.
Mehdi Delrobaei serves as an Assistant Professor in the Mechatronics Engineering Department within the Faculty of Electrical Engineering at K. N. Toosi University of Technology. He leads the Biomechatronic Systems Research Group, directing a comprehensive research program focused on the intersection of biomechanics, artificial intelligence, and healthcare technology. His laboratory maintains active collaborations across multiple disciplines and has established itself as a significant research hub in Iran for cognitive health technologies. Dr. Delrobaei's research focuses on developing innovative biomechatronic solutions for cognitive health assessment and management. His primary areas include Parkinson's disease monitoring systems, spatial navigation evaluation using movement patterns, executive attention assessment through motion analysis, and decision-making analysis using eye tracking. His work uniquely integrates AI algorithms with biomechanical analysis to create accessible assessment tools that can replace costly equipment like EEG and dedicated eye-trackers with standard camera-based analysis. This approach addresses environmental challenges like lighting variations and camera angles while maintaining clinical validity. The research output demonstrates a clear trend toward practical clinical applications of engineering solutions, with publications spanning healthcare AI, neuroimaging, biomechanics, and cybersecurity for medical devices. His team has developed numerous algorithms for cognitive assessment, medication management systems for movement disorders, and secure healthcare data solutions using blockchain technology. Dr. Delrobaei actively supervises a substantial research group with approximately 10 current students across various academic levels, including Ph.D., M.Sc., and B.Sc. candidates. His advising approach appears to focus on interdisciplinary projects that combine engineering expertise with clinical applications, providing students with opportunities to work on meaningful healthcare challenges. The consistent stream of publications and growing student cohort indicate active research funding supporting the laboratory's operations. The Biomechatronic Systems Research Group operates from the Mechatronics Laboratory at K. N. Toosi University of Technology, with facilities including the Library Building on the first floor. The lab maintains a strong focus on translating engineering solutions into practical healthcare applications, particularly in the areas of movement disorders and cognitive assessment. The research environment emphasizes collaboration between engineering students and clinical researchers to ensure both technical innovation and clinical relevance of developed solutions.
