Professor Mounim A. El Yacoubi holds positions at Institut Polytechnique de Paris, Institut Mines-Télécom, and Telecom SudParis. His research focuses on AI, machine learning, and deep learning applied to e-Health (neurodegenerative disease detection, diabetes management), biometrics (gait, vein, and handwriting recognition), and smart systems (agriculture, surveillance, robotics). He leads the SAMOVAR CNRS Lab and has supervised 17 PhDs and 30+ master's students. Education: PhD (1996, Université de Rennes 1), HDR (2014, Paris-Saclay University). Experience: Senior Researcher at Parascript (2001–2008), Visiting Scientist at CENPARMI (1997–1998), Associate Professor at PUCPR (1998–2001). Research Interests: AI applications in healthcare, biometrics, pattern recognition, and smart technologies. Recent work includes Alzheimer’s detection via handwriting analysis, diabetes prediction using PPG signals, and palm/vein recognition systems. Grants & Leadership: Program Chair of ICPRAI 2022, ICCPRA 2024. Editor of IEEE Access and journals on cyber-physical intelligence. Authored books on Pattern Recognition and AI.
Zhongying Deng is a Research Fellow in the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge, affiliated with the Cambridge Image Analysis research group. His work focuses on advancing medical imaging technologies and computer vision through deep learning and domain adaptation techniques. Key contributions include developing benchmark datasets like TrafficCAM and TrafficMOT for traffic analysis, A-Eval for abdominal organ segmentation, and foundational models for medical AI such as GMAI-VL. His research bridges theoretical advancements in neural networks and practical applications in healthcare and transportation. His research interests span image segmentation, domain adaptation, neural network architectures, and multimodal data integration. Notable projects include FCN+ for enhanced convolutional networks and Brain Foundation Models for neurodegenerative disease analysis. Deng collaborates extensively on interdisciplinary projects, combining mathematical modeling with computational tools to address real-world challenges in medical diagnosis and autonomous systems. Publications emphasize scalable medical image analysis frameworks (e.g., STU-Net, Sa-med2d-20m) and robust domain adaptation methods for cross-dataset performance. His datasets and models are widely recognized for enabling reproducible research and advancing state-of-the-art performance in critical areas like MRI reconstruction and multi-organ segmentation.
Saurabh Bagchi is a Professor at Purdue University, West Lafayette, USA. He holds a PhD in Computer Science from the University of Illinois Urbana-Champaign (2001). His research focuses on distributed systems security, networking, and embedded systems. Key areas include IoT security, cyber-physical systems resilience, and machine learning applications in edge computing. Bagchi's work spans theoretical and applied domains, addressing challenges in distributed algorithms, fault tolerance, and secure communication protocols. His contributions to firmware analysis, serverless computing optimization, and anomaly detection in industrial IoT systems have been widely recognized. He has published over 300 papers in top-tier conferences and journals such as IEEE Transactions on Dependable and Secure Computing, ACM Transactions on Sensor Networks, and CVPR. He collaborates with researchers in academia and industry to advance resilient networked systems, including projects funded by NSF and industrial partnerships. His lab explores cutting-edge topics like federated learning security, edge computing architectures, and game-theoretic approaches to cyber defense.
Sverre Steen is a Professor and Head of the Department of Marine Technology at the Norwegian University of Science and Technology (NTNU). He leads the Kongsberg Maritime University Technology Centre focused on 'Ship Performance and Cyber-physical Systems' and is a member of the standing committee for the Symposium of Marine Propulsors. His research emphasizes ship propulsion, hydrodynamics, and big data analysis of in-service vessel performance. Key interests include seakeeping, high-speed marine vehicles, and model testing techniques. Steen teaches TMR 4217 Hydrodynamics of High-Speed Marine Vehicles , covering cavitation, experimental hydrodynamics, and propulsion systems. He collaborates internationally on projects like the Norwegian Ocean Technology Centre. His recent work explores wave-energy extraction via hydrofoil vessels, resistance modeling for fast ferries, and propulsion efficiency in real sea states. He has contributed to global shipping emission models (MariTEAM) and reliability analysis of structural components under vibration. Steen's publications span propulsion in waves, engine-propeller dynamics, and data-driven methods for ship performance monitoring. His applied research bridges experimental testing and computational modeling to address challenges in sustainable maritime transport and operational safety.
Dr. Patrick Bianchi serves as a Researcher at the Swiss Seismological Service (SED) within ETH Zurich, Switzerland, where he conducts fundamental investigations into earthquake processes and rock failure mechanisms. His work integrates laboratory experimentation with numerical modeling to advance seismic hazard assessment methodologies. His research spans seismology, rock mechanics, and experimental geophysics with emphasis on fault mechanics and earthquake physics. Dr. Bianchi employs distributed fiber-optic strain sensing, acoustic emission monitoring, and triaxial testing to study strain localization, precursory signals, and the transition from aseismic to seismic deformation in crystalline and siliclastic rocks. His experimental approaches bridge laboratory observations with natural fault behavior, focusing on how surface roughness, wear processes, and fluid pressure influence fault stability and rupture nucleation. Analysis of his 15 most recent publications (2024-2025) reveals consistent investigation of strain heterogeneities, preslip phenomena, and energy dissipation during earthquake preparation phases. Key methodological trends include scaling deep learning applications from labquakes to megathrusts, comparative laboratory-numerical modeling of pre-failure processes, and environmental loading effects on brittle failure thresholds. His work demonstrates particular expertise in distributed strain sensing techniques applied to fault zone deformation. As an integral member of the Swiss Seismological Service, Dr. Bianchi contributes to Switzerland's national seismic monitoring network and fundamental research on earthquake physics. The SED operates as ETH Zurich's center for seismic hazard analysis, maintaining real-time earthquake detection systems while conducting experimental and theoretical research to improve understanding of seismic sources and ground motion prediction.
Sheelagh Carpendale is a Professor and Canada Research Chair in Information Visualization at Simon Fraser University's School of Computing Science. Her research focuses on Information Visualization, Interaction Design, and Human-Computer Interaction, with a strong emphasis on large display interaction, visual analytics, and personal visualization. She leads the Innovations in Visualization Interactive Experiences (ixLab) and has contributed to over 200 publications. Education: PhD (Computing Science, Simon Fraser University, 1999); BSc (Computing Science, Simon Fraser University, 1992). Research Interests: Dr. Carpendale's work bridges theory and practice, emphasizing user-centered design and interdisciplinary collaboration. Key areas include data physicalization (e.g., Kirigami-inspired visualizations), interactive technologies for healthcare, and educational tools like TangiBooks for programming concepts. Her lab explores novel interaction paradigms for large displays and mobile devices. Recognition: Recipient of the 2018 IEEE Visualization Career Award, numerous best paper awards, and leadership roles in conferences like IEEE VIS. Her contributions span academic, industrial, and public engagement contexts, including projects on clinical decision support and public data literacy. Grants & Labs: Active in securing research grants for projects like the Arctic Movement visualization and Energy Data initiatives. The ixLab collaborates with artists, scientists, and healthcare professionals to create impactful visualizations.
Karl Ulrich Schreiber is an Adjunct Professor at the Department of Physics and Astronomy, University of Canterbury, New Zealand, and an apl. Professor at the Institute for Astronomical and Physical Geodesy at the Technical University of Munich (TUM). He is a scientist at the Geodetic Observatory Wettzell, jointly operated by TUM and the Bundesamt für Kartographie und Geodäsie (BKG). His work bridges fundamental physics and geodetic applications, with leadership roles in major international projects including ESA’s MAGIC/Science, QSG4EMT, and Baltic+ Theme 5, as well as DFG Research Units NEROGRAV and UPLIFT. His research focuses on Space Geodesy , Satellite and Lunar Laser Ranging , and Ring Laser Technology . He has pioneered the use of large ring laser gyroscopes for measuring Earth's rotation, polar motion, and seismic rotations. His work enables high-precision monitoring of geophysical phenomena such as Earth tides, Chandler wobble, and rotational ground motions from earthquakes. He is a key contributor to multi-technique co-location studies (VLBI, SLR, GNSS) and time transfer experiments, advancing the Global Geodetic Observing System (GGOS). His recent publications show a strong trend in developing and applying large-scale ring laser arrays (e.g., ROMY) for geophysical sensing, photon-counting laser ranging for space debris and satellite tracking, and optical timing systems for synchronization across geodetic networks. These efforts span disciplines including geodesy, seismology, quantum optics, and fundamental physics. Scientific contributions include: Development of the Wettzell Large Ring Laser (G-ring) for continuous Earth rotation monitoring. First direct measurements of Earth's diurnal polar motion and Chandler wobble using ring lasers. Pioneering work in rotational seismology, validating ring laser data against seismic arrays. Contributions to lunar laser ranging and its role in reference frame realization. Leadership in ESA and DFG projects advancing space geodesy and inertial sensing. He advises doctoral and master’s students within the DFG Research Training Group UPLIFT and collaborates with international institutions on instrumentation and data analysis. His lab at Wettzell hosts advanced laser ranging and ring laser systems, serving as a fundamental geodetic observatory. Future work includes enhancing clock ties for global geodesy, expanding multi-component rotation sensing, and advancing space-based geodetic technologies.
Brad Hayes is an Associate Professor of Computer Science at the University of Colorado Boulder within the College of Engineering and Applied Science, where he directs the Collaborative AI and Robotics (CAIRO) Laboratory. He also serves as Chief Technology Officer at Circadence, leading efforts in developing AI-enabled products for cybersecurity training and assessment. Undergraduate degree from Boston College PhD in Computer Science from Yale University Postdoctoral Associate at MIT Professor Hayes' research focuses on developing techniques that enable autonomous agents and robots to learn from and collaborate with humans safely, reliably, and productively. His work occurs at the intersection of pervasive and personalized artificial intelligence, human-robot teaming, and decision support. He has made significant contributions to collaborative robotics, dependable explainable AI, and imitation learning, with applications spanning manufacturing, healthcare, disaster response, autonomous vehicles, and space exploration. His recent publications reveal a strong emphasis on human-robot interaction, with particular focus on improving predictability in collaborative tasks, developing explainable AI systems that build trust, leveraging augmented and virtual reality for enhanced collaboration, and creating more efficient learning algorithms from human demonstrations. His work increasingly integrates large language models and advanced neural network architectures while maintaining a strong human-centered design approach. Sustainability Recognition (2025) for computational efficiency in motion planning Best Student Paper Runner-up at AAMAS 2022 Nominated for Best Technical Paper at HRI 2024 Best Technical Paper Runner-up at HRI 2019 Hayes has successfully mentored numerous graduate students through the CAIRO Lab, including multiple PhD graduates in 2024 alone. His lab receives funding from various organizations supporting research in human-robot interaction and collaborative AI. He frequently collaborates with industry partners and has established connections with major technology companies through his research and speaking engagements. The CAIRO Lab, under Hayes' direction, is a vibrant research environment focused on turning theoretical concepts into practical applications through hands-on work with real robots and human participants. The lab's research spans multiple domains including manufacturing, disaster response, autonomous vehicles, and space exploration, with a consistent emphasis on safe and effective human-machine teaming.
Dr. Changyou Chen is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York. His research focuses on Multi-Modal Learning Foundation Models Deep Generative Models Large-scale Bayesian Sampling with applications in document understanding, music-AI integration, and molecular representation learning. Research Trends revealed through his recent publications include Optimizing Multimodal Large Language Models Developing Novel Retrieval-Augmented Generation Frameworks Creating Benchmark Datasets for Visual Text Understanding Advancing Diffusion Models with Domain-Specific Constraints across domains from music sheets to biomedical documents. Scientific Contributions : UB Young Investigator Award (2020) Architect of LoCAL Framework for Long Document Understanding Co-developer of MusiXQA Benchmark Pioneering Work in Probability Contrastive Learning Academic Leadership includes mentoring 10+ graduate students and serving as Area Chair for major AI conferences (ICML, NeurIPS, AAAI, IJCAI). His Labs develop scalable solutions for multimodal reasoning, with recent work demonstrating practical GPU memory optimization through LoRA adapter sharing.
Qian Lou serves as an Assistant Professor in the Department of Computer Science at the University of Central Florida and is an active member of the university's Cybersecurity and Privacy Cluster. His research program targets critical challenges in deep learning systems, specifically enhancing efficiency, privacy, and security for applications in computer vision and natural language processing. His academic foundation includes: Ph.D. in Computer Engineering from Indiana University, Bloomington M.S. in Computer Engineering from Indiana University Bloomington B.S. in Computer Science from Shandong University Lou's research spans deep learning methodologies with specialized focus on computer vision and natural language processing systems. His work integrates cybersecurity principles into machine learning architectures, particularly through privacy-preserving techniques and secure computational frameworks. This interdisciplinary approach bridges computer systems architecture with practical AI deployment challenges, emphasizing efficiency optimizations for resource-constrained environments. His scholarly recognition includes: 2018 AAMAS Best Paper Finalist 2016 AAMAS Best Demonstration Paper Finalist University of Southern California Merit Fellowship Professionally, Lou contributes extensively to the academic ecosystem through program committee service and peer review activities for leading conferences and journals in artificial intelligence and computer science. His industry experience at Samsung Research AI Center informs his applied research perspective and technology transfer approach. Within UCF's Cybersecurity and Privacy Cluster, Lou collaborates on cross-disciplinary initiatives addressing real-world security vulnerabilities in AI systems, working alongside researchers from engineering, data science, and policy domains to develop robust computational frameworks.
Ben Amor is a Full Professor in the Department of Civil Engineering at the Faculty of Engineering, Université de Sherbrooke, where he serves as Director and Founder of the CIRMIB (Integrated Research Center on Sustainable Materials, Infrastructure and Buildings) and Director of Sustainable Development for the Faculty of Engineering. Previously, he held associate professor positions at Université Laval and Université de Sherbrooke. His research focuses on Life Cycle Assessment (LCA) methodologies applied to sustainable construction, circular economy implementation in building sectors, and building decarbonization strategies. He has pioneered regionalized LCA approaches for Arctic regions and developed frameworks for carbon budgeting in building sectors. His work bridges environmental science with practical engineering solutions for sustainable infrastructure. His recent publications reveal strong trends in building decarbonization pathways, material circularity in construction, and the integration of biogenic carbon accounting. He emphasizes both technological solutions and behavioral change strategies for achieving net-zero emissions in the built environment. ACLCA 2018 Life Cycle Assessment Leadership Award Life Cycle Academy Awards 2019 (two awards) Quebec Public Administration Excellence Prize 2023 for Scientific Collaboration Multiple university teaching awards including the Jacques-Bazinet Merit Award Professor Amor leads significant research grants totaling over $20 million, including NSERC Alliance grants for sustainable building materials and a $2 million Research Chair on Net Zero Strategies and Life Cycle Assessment. He directs the CIRMIB research center and the LIRIDE (Interdisciplinary Research Laboratory in Sustainable Engineering and Eco-design), supervising multiple doctoral candidates. His work includes developing LCA tools for Quebec's construction industry and advising government bodies on sustainable procurement policies.
Panagiotis Zervopoulos is an Associate Professor at the Department of Business Organization and Administration within the School of Economics, Business and International Studies at the University of Piraeus. Previously, he served as Associate Professor and Director of the PhD Program in Business Administration at the School of Business Administration of the University of Sharjah in the UAE. His research interests focus on operations research, efficiency and performance measurements, optimization methods, and econometrics. Specifically, he specializes in developing new data envelopment analysis (DEA) techniques, Bayesian methods, parametric and non-parametric econometric models, with innovative applications across multiple disciplines. His methodological contributions have been applied in diverse fields including supply chain management, financial systems, environmental efficiency, and corporate governance. Zervopoulos has published extensively in top-tier journals such as European Journal of Operational Research, Journal of the Operational Research Society, Annals of Operations Research, Journal of Financial Stability, and Journal of Cleaner Production. His recent work (2023-2024) demonstrates continued innovation in efficiency measurement techniques, particularly in network DEA models with bias correction, environmental efficiency analysis, and systemic risk measurement. His publications show strong international collaboration patterns, frequently working with researchers from different countries and institutions. He has served as Guest Editor for journals including Socio-Economic Planning Sciences and IMA Journal of Management Mathematics, demonstrating recognition of his expertise by the academic community. Zervopoulos has held research fellowships at prestigious institutions worldwide, including Peking University (China), the London School of Economics (United Kingdom), the Academy of Athens (Greece), and the Foundation for Economic and Industrial Research (Greece). He also participates in the World Economic Survey and the Economic Expert Group of the Ifo Institute (Germany). Professionally, he has served as Senior Consultant Modeling Statistician at IRi Worldwide and as Project Manager and Expert in Quantitative Analysis and Public Sector Reform through technical support projects with the European Public Law Agency.
Prof. Dr. Harald Tauchmann is a Professor of Health Economics at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where he has held a faculty position since 2013. He is affiliated with the School of Business, Economics and Social Sciences, specifically within the Department of Economics. Prof. Tauchmann also participates in multiple research focus areas at FAU, including 'Insurance and Risk' and 'Work in Transition,' demonstrating his interdisciplinary approach to health economics. Prof. Tauchmann received his education at Heidelberg University and the University of Manchester, UK, where he studied economics, political science, and sociology. He graduated in 1998 and completed his doctorate at the Interdisciplinary Institute for Environmental Economics (University of Heidelberg) in 2003. Prior to joining FAU, he worked as a research associate at the Rhineland-Westphalian Institute for Economic Research (RWI) in Essen from 2003 to 2012 and headed a junior research group at the health economics research center CINCH at the University of Duisburg-Essen. His research expertise lies in empirical health economics, with a particular emphasis on health insurance choice and competition, as well as individual health behavior. He has made significant contributions to understanding obesity, health shocks, mental health care payment systems, and thyroid diagnostics through his extensive publication record. His methodological work includes developing specialized Stata modules for econometric analysis, which have been widely adopted by researchers in the field. Prof. Tauchmann's scholarly work demonstrates a consistent focus on applying rigorous econometric methods to pressing health policy questions. His research portfolio shows particular strength in causal analysis of health behavior, especially regarding obesity interventions, health insurance market dynamics, and the economic consequences of health shocks. His recent publications (including several forthcoming in 2025) indicate continued scholarly productivity and relevance to current health policy debates. From March 2021 to April 2022, Prof. Tauchmann served as chairman of the German Society for Health Economics, highlighting his leadership and recognition within the national health economics community. His email contact is harald.tauchmann@fau.de for professional inquiries.
Perry Hinton is a Professor (Teaching Focused) in the Centre for Applied Linguistics at the University of Warwick, part of the Faculty of Social Sciences. He contributes to the interdisciplinary degree in Language, Culture and Communication, drawing on his expertise in psychology and cultural studies. University: University of Warwick School: Faculty of Social Sciences Department: Centre for Applied Linguistics Academic Rank: Professor Email: P.R.Hinton@warwick.ac.uk His research centers on the psychology of interpersonal perception, especially the interplay between cognition and culture. Key areas include stereotyping as a cognitive and cultural phenomenon and Western (particularly British) interpretations of Japanese culture, including media portrayals and anime. He also has a strong commitment to statistical education, having authored multiple textbooks on SPSS and data analysis. The recent publications reflect a consistent focus on cultural psychology, intercultural communication, and social representation. Themes include the construction of identity, media influence, cultural stereotypes, and cognitive biases in person perception. His work often takes a multidisciplinary approach, integrating insights from psychology, linguistics, and media studies. Perry Hinton has authored and co-authored several influential books in his field, particularly on stereotypes and statistical methods. While no formal scientific awards are listed, his sustained publication record in peer-reviewed journals and with major academic publishers (Routledge, Bloomsbury, Palgrave) indicates significant scholarly recognition. He has supervised or co-edited collaborative works, such as the 2023 volume on intercultural relations, suggesting advisory and mentoring roles. His career path includes positions at five British universities, progressing from lecturer to Head of Department, with extensive experience teaching psychology across disciplines including linguistics, education, and media studies. He joined Warwick's Centre for Applied Linguistics at the inception of its Language, Culture and Communication program in 2014. Hinton works within a multidisciplinary academic environment, contributing to a research culture that bridges psychology and applied linguistics. His collaborations, particularly with Troy McConachy, suggest active participation in intercultural research teams and scholarly networks focused on global communication and cultural understanding.
Nelly V. Litvak is a Full Professor in Algorithms for Complex Networks at Eindhoven University of Technology (Mathematics and Computer Science). She works on mathematical methods and algorithms for complex networks (social networks, WWW) using random graph models. She joined TU/e as a part-time professor in 2017 after being an Associate Professor at the University of Twente since 2012. Affiliations: 4TU Applied Mathematics Institute, Data Science Center Eindhoven, CTIT Industry Partners: ABN-AMRO Bank, Philips Lighting, Thales Editorial Role: Managing Editor of Internet Mathematics Her research focuses on extracting value from network data across three areas: (1) Information extraction and prediction, (2) Mathematical analysis of network characteristics, and (3) Efficient algorithms for incomplete network data. Key topics include PageRank, HITS algorithm, random graphs, homophilic networks, and network epidemiology. Recent work (2022-2025) spans network growth mechanisms, fairness in ranking algorithms, educational pedagogy, and pandemic forecasting dashboards. She contributes to SDGs through data-driven approaches to societal challenges. Teaching activities include course development at TU/e and earlier institutions, with innovative methods for computer engineering students' statistical understanding.
