Professor Motohiro Fujita is affiliated with Nagoya Institute of Technology, where he contributes to the Department of Civil Engineering and Department of Environmental and Urban Engineering. Holding a Doctor of Engineering from Nagoya Institute of Technology, his work bridges transportation engineering, urban planning, and disaster prevention. Doctor of Engineering (Nagoya Institute of Technology, 1990) Master of Engineering (Nagoya Institute of Technology, 1985) His research focuses on transportation demand forecasting, traffic congestion analysis, and engineering education integration. Notable projects include: Developing time-of-day Origin-Destination (OD) estimation models using traffic counts Studying congestion definition based on driver consciousness Advancing marketing-oriented approaches in engineering education Recent publications analyze urban freeway dynamics, traffic signal behavior, and residential environment planning. He has presented at major conferences like the European Transport Conference and Japan Society of Civil Engineers meetings. Award of the Japan Society of Civil Engineers (1999) Active in professional bodies, he serves on committees for Nagoya Expressway Public Corporation, Nagoya City Environmental Impact Assessment Board, and academic societies like the Japan Society of Civil Engineers.
Arne Bathke is a University Professor at Paris Lodron University Salzburg, specializing in Artificial Intelligence and Human Interfaces within the Faculty of Digital Sciences. He leads the Intelligent Data Analytics (IDA) Lab Salzburg and serves on prestigious international bodies including the United Nations High Level Expert Group and as Chair of the European Statistical Advisory Committee (ESAC) through 2029. His academic profile demonstrates significant leadership in statistical methodology and data science applications. Professor Bathke's research centers on nonparametric statistics, multivariate data analysis, biostatistics, and biometrics, with particular emphasis on methodological challenges in rare disease research. His work bridges rigorous statistical theory with practical applications across healthcare, arts interventions, and environmental education. He has developed innovative approaches to statistical analysis that address complex data structures and small sample limitations, making significant contributions to evidence-based research in specialized fields. His extensive publication record reveals a strong interdisciplinary trajectory, with recent work focusing on statistical methodology for rare disease trials, arts and health research evaluation, and educational initiatives like the CO2BS project that integrates sensor technology with environmental science education. This pattern demonstrates his commitment to applying advanced statistical methods to solve real-world problems across diverse domains. Dr. Bathke has earned substantial recognition for his scholarly contributions: Elected Academy Member, European Academy of the Sciences and the Arts (March 2024) Fellow, American Statistical Association (May 2024) GREAT TEACHER AWARD (January 18, 2012) HENRY CLAY AMBASSADOR (August 8, 2012) Kulturfonds der Stadt Salzburg: Kinder- und Jugendprojektpreis 2020 (November 23, 2020) As an active research leader, Professor Bathke manages multiple significant projects including MINT:labs (City and State of Salzburg 2025), Dance with us! (a health study on psychophysiological effects of dance programs), ERDERA (European Rare Diseases Research Alliance), and DIH West (Digital Innovation Hub West). His work extends beyond traditional academic boundaries through third mission activities including the ditact: IT Summer School for Women and Mozart does STEM initiatives that connect music, mathematics, and education. He directs the Intelligent Data Analytics (IDA) Lab Salzburg and collaborates extensively through EXDIGIT and international networks. His current projects demonstrate a commitment to applying data science to rare disease research, developing educational tools for scientific literacy, and exploring the intersection of arts and health through innovative methodological approaches that enhance research rigor in these fields.
Franziska Hübl is a researcher at the Institute of Geodesy, Graz University of Technology, specializing in geospatial technologies and machine learning applications for environmental and energy challenges. Her work bridges geodesy, remote sensing, and urban systems analysis with tangible real-world implementations. Education BSc in relevant field MSc in relevant field Research Focus Her expertise spans Geodesy , Remote Sensing , and Geographic Information Systems , with concentrated efforts in urban environment modeling , photovoltaic potential assessment , and water resource monitoring . Key innovations include neural network applications for shadow analysis and satellite-based water detection systems, demonstrating strong interdisciplinary integration of geospatial engineering with sustainable energy solutions. Publication Trends Recent work (2023-2025) reveals a strategic focus on sensor fusion for environmental monitoring and renewable energy optimization. Publications consistently integrate GNSS/INS/LIDAR technologies with machine learning to address photovoltaic site selection, wave dynamics, and urban shadow modeling, reflecting a cohesive research trajectory targeting climate-resilient infrastructure. Collaborative Impact WAMOS project: Wave monitoring system using GNSS/INS on buoys PV4EAG initiative: Geospatial identification of photovoltaic installation sites Media engagement: ORF features on Kärnten heute and Steiermark heute Conference leadership: Presentations at ION GNSS+ and GIScience
Mona Abdelgayed is a Lecturer in Computer Science and Applied Computing at the School of Computing and Digital Media, London Metropolitan University. She holds a PhD in Computer Science from the National University of Singapore (NUS), an MSc in Communication and Information Technology, and a BSc in Computer Science from Egypt. Her career combines teaching and research, with prior roles as a Teaching Assistant at NUS and in Egypt. Education PhD in Computer Science, National University of Singapore MSc in Communication and Information Technology, Egypt BSc in Computer Science, Egypt Research Interests Mona focuses on Computer Vision , Machine Learning , and Deep Learning , particularly in Image/Video Processing for segmentation, tracking, and classification using biometrics. Her work spans interdisciplinary applications in Medical Imaging , Cybersecurity , and Cognitive Science , exploring intersections with psychology and human perception. Scientific Awards Leading, Educating and Nurturing Talent (TALENT) Award - A*STAR, Singapore (2018) SINGAPORE INTERNATIONAL GRADUATE AWARD (SINGA) (2015) Third Prize in Microsoft Imagine Cup Software Design, Egypt (2008) Distinguished Participation in Microsoft Imagine Cup, Egypt (2009) Top-Ranked Undergraduate Student Award, Minister of State for Military Production, Egypt (2009) Advising and Grants Mona supervises undergraduate, MSc, and PhD dissertations. She has been part of the AI and Data Science Research Group and Cyber Security Research Centre at London Met. Her funded projects include the SINGA scholarship (2015) and the A*STAR TALENT award (2018), supporting interdisciplinary research in computer vision and machine learning.
Laura Gastaldi is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) of the Polytechnic University of Turin . She is a member of the PolitoBIOMed Lab and the Master's and Continuing Education School . Her academic roles include teaching in doctoral programs since 2013 and serving as course lecturer/collaborator for topics like Mechanics Applied to Biomedical Systems and Automation of Mechanical Systems . Research Interests : Biomechanics Human Body Modeling Human-Machine Interaction Wearable Robotics Parasports Motion Analysis Her 15 most recent publications focus on wearable inertial sensors, exoskeletons, human-robot collaboration, and mobility assistance devices, spanning Biomechanics , Robotics , and Biomedical Engineering . She leads research projects like EMPATHY (2024-2026) and Promobilia (2023-2024), emphasizing accessibility and industrial sustainability. Laura supervises PhD students Claudia Barattini , Michele Polito , and Mattia Antonelli , and holds patents for Directional propulsion assist devices and Active joints for exoskeletons .
Denys J.C. Matthies is an Associate Professor at Technical University of Applied Sciences Lübeck and affiliated with Fraunhofer IMTE Lübeck . He specializes in Human-Computer Interaction , particularly focusing on Wearable Computing , Tactile Feedback Systems , and Activity Recognition through smart footwear and body-worn sensors. Key Collaborations: Augmented Human Lab (NUS), Fraunhofer IGD, City University of Hong Kong Research Themes: Smart wearables, haptic interfaces, physiological sensing, assistive technologies His recent work explores: PhantomFolds (2025) - Spatial tactile feedback via fingernail-mounted LRAs PAVES (2025) - Pneumatic terrain simulation in VR Cyber-Placebo (2024) - Ethical implications of fake-AI in CPHS He has contributed to smart footwear systems like ShoeTect2.0 (2024) and SurfSole (2024), integrating capacitive sensing with neural networks for real-time activity and surface recognition. His work spans medical applications (e.g., 2025 study on hepatic encephalopathy screening) and novel interaction paradigms (e.g., Kavy conversational AI 2024).
Wei Huang (Wayne) is a Chair Professor and founding dean of the College of Business at Southern University of Science & Technology (SUSTech) in Shenzhen, China. He holds the prestigious National Yangtze Chair in Management Information Systems and has over 35 years of full-time teaching and research experience across multiple continents. His academic career spans renowned institutions including University of New South Wales (Sydney, Australia), National University of Singapore (NUS), Harvard University, Chinese University of Hong Kong (CUHK), and Xi'an Jiaotong University. His research interests focus on Management Information Systems , specifically on using IS/IT to support decision-making and collaboration, and business analytics. Dr. Huang has published over 200 research papers in top-tier journals including MIS Quarterly (MISQ), Journal of Management Information Systems (JMIS), Journal of the Association for Information Systems (JAIS), and IEEE Transactions, with his work being cited by leading journals such as Management Science and ISR. His recent publications demonstrate a clear trend toward integrating emerging technologies like artificial intelligence, blockchain, and IoT with traditional business analytics to create more robust decision support systems. The research spans multiple subfields including machine learning, data visualization, collaborative technologies, and cross-cultural aspects of information systems adoption, reflecting both the breadth and depth of his scholarly contributions. AIS Fellow (2020) - second professor from a Chinese university to receive this honor Sandra Slaughter Outstanding Services Award (2018) - first mainland Chinese scholar to receive this award National Yangtze Chair in Management Information Systems Outstanding SIG Award for AIS SIG-ISAP (2017) Highest Quality Rating from the British Library Outstanding Professional Service Award of ICIS Dr. Huang has secured significant research funding from diverse sources including the Australian Research Council (ARC), National Science Foundation of China, National University of Singapore, Chinese University of Hong Kong, and Harvard University. His leadership extends beyond research to academic service where he has served as PACIS Council Chair (2019-2022), founding President of AIS SIG-ISAP for over 15 years, and key founding member of China AIS Chapter. He currently serves as Vice Chairman of the Teaching Steering Committee for Management Science and Engineering Programs at Guangdong Universities, Honorary Dean of the China Guoxin Credit Big Data Research Institute, and several other high-level advisory roles with Chinese governmental bodies.
Dr. Md Hasanuzzaman Sagor is a Lecturer at the School of Electronic Engineering and Computer Science , Queen Mary University of London. His research focuses on advanced antenna systems for emerging communication technologies, including transparent/flexible 5G antennas, wearable device antennas, and metamaterial-loaded RF components. Teaching: Digital Circuit Design, Microprocessor Systems Design, Networks and Protocols (all for BUPT joint programme) Research Highlights: Pioneering work in mmWave antenna design, energy harvesting rectennas, and graphene-based THz antennas Key Project: Co-PI and Head of Ground Station Design Team for BRAC Onnesha, Bangladesh's first satellite under the BIRDS project Contact: m.h.sagor@qmul.ac.uk His recent work explores material innovations in antenna design, showing a clear trajectory from wearable communication systems to education technology applications. Notably, Sagor's research team successfully deployed space-bound technology through their satellite project collaboration. Research Trends: Analysis of publications reveals sustained focus on mmWave antenna geometries (2014-2021), with recent expansion into educational technology systems (2024-2025). Key technical contributions include novel metamaterial integration methods and wearable device optimization.
Susanne Kratzer is an Associate Professor in Marine Ecology at Stockholm University's Department of Ecology, Environment and Botany, specializing in marine remote sensing and bio-optics with focus on Baltic Sea ecosystems. She leads the 'Group Scratches' research group and coordinates the Nordic Network for Baltic Remote Sensing. Her work integrates satellite data, field measurements, and modeling for coastal zone management. Her educational background includes a German Diploma, Master's thesis in the School of Ocean Sciences (University of Wales, Bangor), and PhD in Biological Oceanography from the School of Ocean Sciences. She has been conducting marine remote sensing research at Stockholm University since 1997. Her research focuses on developing novel methods for ocean color remote sensing in optically complex waters, with particular emphasis on Baltic Sea applications. She has pioneered algorithms for retrieving suspended matter, Secchi depth, and chlorophyll-a from satellite data, addressing challenges posed by high CDOM concentrations. Her work bridges optical oceanography with practical coastal management needs, especially eutrophication assessment. Analysis of her recent publications reveals strong trends in satellite validation (particularly Sentinel-3 OLCI), integration of multi-source data (satellite, mooring, ship-based), and development of region-specific algorithms for Baltic Sea conditions. Her research increasingly addresses climate change impacts on coastal optical properties and monitoring requirements. National advisor for bio-optics in Swedish monitoring programs (SMHI, GU, UU, SU) Professional trainer for bio-optical measurements funded by Swedish Marine and Water Management Agency Contributor to 'The Colour of the Baltic Sea' film segment She actively mentors students through teaching marine remote sensing and bio-optics at all academic levels, and has coordinated numerous PhD courses through the Nordic Network. Her current projects include developing advanced methods for imaging biomolecules, improving national guidelines for marine bio-optical measurements, and long-term operation of the AERONET-OC station in Lake Vänern. Her research group maintains strong international collaborations with NASA, ESA, and European monitoring networks, contributing significantly to the integration of remote sensing into operational coastal zone management frameworks.
Hersh Sagreiya is an Assistant Professor of Radiology at the University of Pennsylvania, board-certified in both Diagnostic Radiology and Clinical Informatics. His academic position focuses on advancing AI integration within radiological practice to enhance diagnostic accuracy and clinical workflow efficiency through cutting-edge machine learning applications. Dr. Sagreiya's research centers on the development and implementation of artificial intelligence systems for medical imaging analysis. His primary interests include deep learning for abdominal MRI and CT characterization, vision-language models for 3D medical representations, and natural language processing for radiology report generation. He also investigates critical legal and ethical dimensions of AI adoption in radiology, particularly regarding malpractice risk mitigation and regulatory compliance frameworks. His work consistently addresses real-world clinical challenges in imaging order optimization, diagnostic support, and treatment monitoring through novel algorithmic approaches. Analysis of his 15 most recent publications (2024-2025) reveals three dominant research trajectories: (1) AI-driven clinical decision support systems aligned with radiological guidelines, (2) automated integration of AI results into reporting workflows using standardized data elements, and (3) development of foundational models for medical image analysis. His publications demonstrate exceptional methodological diversity spanning supervised, unsupervised, and generative AI techniques applied across abdominal imaging, pulmonary analysis, and oncology contexts. The work consistently emphasizes practical clinical implementation, safety considerations, and regulatory adherence in AI deployment. No scientific awards, grant funding information, or student mentorship activities were documented in the source material. Similarly, there is no available information regarding laboratory affiliations, research teams, or collaborative networks led by Dr. Sagreiya. His publication record indicates sole or primary authorship on multiple high-impact technical implementations suggesting strong independent research leadership within the radiology informatics domain.
Karl McCreadie serves as a Lecturer in Data Analytics at Ulster University's School of Computing, Engineering and Intelligent Systems, Magee Campus. His research integrates computational methods with neurotechnology to address clinical challenges, particularly in brain-computer interfaces and rehabilitation engineering. His primary research domains include Brain-Computer Interfaces (specializing in motor imagery decoding and auditory feedback systems), Virtual Reality applications for upper-body physiotherapy, and smart materials development for medical devices like stoma management systems. He employs advanced machine learning techniques to enhance classification accuracy in EEG/MEG signal processing and develops embodied VR environments for neurorehabilitation. His work bridges computer science with clinical needs, focusing on user experience optimization and assistive technology for disabilities. Analysis of his 26 publications (2011-2025) reveals a clear evolution from foundational BCI signal processing toward applied clinical solutions. Early work concentrated on motor imagery classification algorithms and auditory feedback mechanisms, while recent publications (2023-2025) emphasize extended reality rehabilitation, biodegradable electrode substrates, and semiconductor production optimization. A strong interdisciplinary thread connects his machine learning expertise with biomedical applications, particularly in stoma care innovation and neurotechnology for tetraplegia. Dr. McCreadie actively contributes to major research initiatives including the Princess Anne-opened Spatial Computing & Neurotechnology Innovation Hub (2023) and three Medical Research Council/Invest NI-funded stoma care projects: Addressing GAPS in Stoma Output Monitoring (2025-2026), STOMACAP: Reimagining Stoma Management (2025-2026), and MICA: Stomasense (2023-2026). These projects address critical healthcare challenges through composite materials and wireless monitoring systems. He has supervised three research students and maintains active collaborations within Ulster's Computer Science and Informatics group. As a core member of the Spatial Computing & Neurotechnology Innovation Hub, he participates in developing next-generation neurotechnology solutions that combine virtual reality, spatial computing, and physiological signal processing. His team's work on the Cybathlon championship training program demonstrates real-world impact in assistive technology for people with severe disabilities.
Dr Mark Ng is a Reader (equivalent to Associate Professor) in Mechatronics Engineering and Control at the School of Engineering, Ulster University. He is also attached to the Engineering Research Institute and leads the Multi-Agent and Advanced Robotics Centre (MAvRiC). Additionally, he serves as an Adjunct Senior Research Fellow at Monash University Malaysia. Education: Ph.D. in Fault Diagnosis and Control Systems, Monash University (2009) BEng (Hons) in Electrical and Computer Systems Engineering, Monash University (2006) Research Interests: Dr Ng’s research spans fault diagnosis, control systems, mathematical modelling, digital twin technologies, and data analytics for anomaly detection and classification. His work has been applied across automotive systems, renewable energy, water treatment, and public health modelling. His recent publications reflect a strong focus on developing robust digital twins for automotive engines, creating hybrid model-based and data-driven fault isolation techniques, and modelling infectious disease dynamics such as COVID-19 to inform public health policy. He has also contributed to smart home technologies and advanced control architectures. Awards and Honours: Learning and Teaching Award, Ulster University (2020) Monash University PVC’s Awards for Excellence in Research and Teaching (2010–2012) Funding and Leadership: He has secured over £6.5 million in research funding from bodies such as EPSRC, UKRI, and GCRF. He currently leads the EPSRC-funded "Empowering Green Futures" project developing energy mapping digital twin technology for wind turbines. He has supervised 2 postdocs, 8 PhD candidates, and 3 Master’s by Research students. Labs and Teams: Dr Ng directs the Multi-Agent and Advanced Robotics Centre (MAvRiC) and collaborates with the Offshore Renewable Energy Catapult, Digital Catapult, and various national and international research networks.
Saeed Latif is an Associate Professor at the University of South Alabama's College of Engineering , specializing in electrical engineering with a focus on antenna design and wireless communication systems . His research spans biomedical applications, 4G/5G networks, satellite communication, and metamaterials. His work includes: Developing large-scale antenna arrays for 5G/4G LTE Designing metasurface-based antennas for millimeter wave systems Miniaturized antennas for satellite and biomedical devices Publications highlight expertise in antenna miniaturization , beamforming , and engineered materials for performance optimization. He teaches courses ranging from Introduction to Engineering to Antenna Theory and Design , covering both foundational and advanced topics in electrical engineering.
Prof. Dr. Bernd Pinzer serves as Professor and Institute Director at the Institute for Computer Vision within the Faculty of Mechanical Engineering at Kempten University of Applied Sciences. He leads the Optical 3D Metrology and Computer Vision Laboratory (3D visionlab), focusing on interdisciplinary research where physics, mathematics, computer science, and mechanical engineering converge. His educational background includes a physics degree completed in 2005, followed by a doctorate at ETH Zurich (2009) on snow metamorphism using X-ray computed tomography. His postdoctoral work at the Paul Scherrer Institute advanced novel phase-contrast X-ray techniques for medical diagnostics. Research interests span computer vision , 3D metrology , and non-destructive imaging , with emphasis on industrial applications. His work integrates Stereo Vision and Photogrammetry Optical coordinate measurement systems X-ray tomography for material analysis Deep learning for industrial monitoring Recent publications demonstrate strong industry collaboration in foundry automation, additive manufacturing quality control, and medical sensor development. Patents include methods for rotating body surface capture (DE102018216458A1) and processing installation operation (EP3655175A1), reflecting applied research impact. His laboratory develops cutting-edge optical metrology solutions for industrial and medical applications, bridging academic research with practical engineering challenges.
Tobias Bauer is an Associate Professor in Ore Geology at the Department of Civil, Environmental and Natural Resources Engineering at Luleå University of Technology. His research focuses on structural geology, 3D and 4D geological modeling, and mineral exploration techniques, with particular emphasis on the Kiruna mining district and the Fennoscandian Shield. He leads several significant research projects including the industry-funded 'Common Earth Modelling of the Kiruna mining district' and contributes to the Horizon Europe project 'Exploration Information Systems (EIS)'. Dr. Bauer's research interests center on combining structural geology with ore geology to understand mineralized systems. He employs field geology to identify large-scale shear zones and their control over ore deposits, complemented by structural and microstructural analysis, high-resolution geochronology, lithogeochemistry, and geophysical surveys. His work integrates modern 3D and 4D modeling techniques to constrain structures and mineralized systems at depth, using digital field mapping devices for multi-scale 3D models. A key innovation in his research is the application of Virtual Reality environments through the EIT Raw Materials network 'VISUAL3D,' which focuses on VR and AR technologies in exploration and geosciences. His recent publications demonstrate a strong focus on critical raw materials, particularly lithium-caesium-tantalum (LCT) pegmatites, iron oxide-apatite deposits, and copper-gold systems in the Fennoscandian Shield. The articles show a consistent trend toward integrating geological, geochemical, and geophysical data to develop comprehensive mineral system models that enhance exploration targeting. His work spans from fundamental research on petrophysical signatures to applied projects developing innovative exploration technologies. Dr. Bauer runs a Virtual Reality laboratory to improve 3D-4D modeling through VR environments and has developed a UAV system with high-resolution sensors for efficient 3D data collection. These technologies aim to improve mineral exploration workflows by combining 3D models with geological surveys to create 4D models that visualize geological evolution. His research, conducted in close collaboration with the mining industry, helps predict the prospectivity of mineralized areas, target new mineralizations, and predict the shape of ore bodies.
