Katažyna Bogdzevič is a Professor at Mykolas Romeris University (MRU) Law School, specializing in Private International Law , European Law , Human Rights , and Environmental Law . She leads the MRU Human Rights LAB and contributes to the Environmental Management Research LAB, focusing on legal frameworks for ecosystem services, climate change mitigation, and stakeholder engagement. Key Research Themes: Integration of Private International Law with Environmental Law , analysis of legal conflicts in nature-based solutions, and name rights under international human rights conventions. Policy Engagement: Serves as advisor to Lithuania's Minister of Justice Ewelina Dobrowolska , emphasizing knowledge transfer to legislative and judicial practices. Email: roffice@mruni.eu
Dr. Frederic Bosche is a Reader in Construction Informatics at the University of Edinburgh's School of Engineering, leading the CyberBuild Lab. His research focuses on advancing digital construction technologies, including BIM, sensing systems, and digital twinning to enhance infrastructure management and workforce safety. Education: PhD in Civil Engineering (University of Waterloo), M.Sc. from University of Texas at Austin, and M.Eng. from Ecole Centrale de Lille. Research interests include automated construction processes, data-driven infrastructure lifecycle management, and integrating emerging technologies like AI and IoT into construction workflows. His CyberBuild Lab has pioneered projects in defect detection, roof monitoring, and smart construction inspection. Notable contributions include over 100 publications, 12 research projects (e.g., 'Digital Facility' and 'Monitoring Roofs of Traditional Buildings'), and awards such as the Charles M. Eastman Top PhD Paper Award. He actively engages in public outreach through science festivals and collaborates internationally with institutions like ETH Zurich and Heriot-Watt University.
Jan Cudzik is an Assistant professor at the Gdańsk University of Technology's Department of Urban Architecture and Waterscapes, Faculty of Architecture. He leads the Digital Technology Laboratory and focuses on integrating computational methods with architectural design and conservation. His research spans parametric design, generative systems, artificial intelligence, and sustainable construction practices. Education details are not explicitly provided in the texts, but his academic roles indicate advanced training in architecture and engineering. Research interests include: AI-driven design processes Generative design using swarm intelligence 3D printing in construction Energy-efficient building lifecycle assessment Traditional-conservation/digital-fabrication hybrids Key publication trends emphasize: Public space sustainability (lighting, greenery) Machine learning applications in architecture Historical structure preservation He contributes to projects like ENACT 15mC, focusing on urban community development. His work bridges digital innovation with ecological and cultural heritage concerns. Labs/Teams: Director of the Digital Technology Laboratory, active in architectural education reform using AI tools.
Professor Jyh-Hone Wang holds a faculty position in the Department of Mechanical, Industrial and Systems Engineering at the University of Rhode Island (URI). His research focuses on transportation human factors, driving safety, and intelligent transportation systems, with particular emphasis on variable message sign (VMS) design, driver behavior analysis, and automation technology acceptance in elderly drivers. He has conducted studies on dynamic message sign efficacy, traffic flow management, and roadway safety improvement strategies. Education: Ph.D. and M.S. in Industrial Engineering from the University of Iowa (1989 and 1986), and B.S. in Industrial Engineering from Tunghai University, Taiwan (1980). Recent grants include a 2020 National Institute for Undersea Vehicle Technology grant (Co-PI) on stress monitoring via wearable devices, and a 2017 Rhode Island Department of Transportation grant (PI) assessing sidewalk quality compliance. His work bridges engineering principles with human factors to enhance traffic safety and transportation efficiency. Key research contributions include optimizing VMS message design for clarity, analyzing driver responses to automation levels, and addressing tailgating issues through behavioral interventions. He has advised multiple graduate students and collaborated on interdisciplinary projects involving traffic data analysis and manufacturing process optimization.
Nico Buls is a Researcher in the Department of Radiology at Universitair Ziekenhuis Brussel (UZ Brussel). His work focuses on translational projects in medical imaging physics, radiation dosimetry, and engineering, with an emphasis on advanced imaging technologies for diagnostic and interventional radiology. Key research areas include imaging physics, spectral CT techniques, iterative reconstruction in CT, radiation dosimetry, neuro MRI applications, and applied statistics in medical imaging. He leads projects such as the PAD flow study (quantitative blood flow assessment via 4D CT) and the evaluation of lung ventilation using Xenon gas-enhanced CT. Buls collaborates internationally, with active research in Belgium and beyond. Affiliations: UZ Brussel, Research Centre for Digital Medicine. Grants/Projects: 12 active projects including OZR4357 (PhD stipend), PAD flow, and Xenon gas imaging studies. Scientific Awards: Editor's Recognition Award (2014, 2016) Radiological Society of North America (RSNA) Fellowship (2011) Young Physicist Grant (2001) Advising/Grants: Supervises 20+ research projects and students, with notable contributions to 4D CT applications and radiation safety protocols. His lab, the Research Centre for Digital Medicine, drives innovation in clinical imaging technologies.
Summary Associate Professor Mehrdad Arashpour is an internationally recognized researcher and educator in construction and civil infrastructure, focusing on automation and information technologies. He leads the ASCII Lab at Monash University's Department of Civil and Environmental Engineering. His academic roles include Head of Construction Engineering and membership in the CIB's Working Commission on Off-site Construction (W121) and Infrastructure Task Group (TG91). Education: Ph.D., RMIT University, Australia M.Sc., Grenoble University, France B.Sc., IU University, Iran Research Interests: Digital twins, computer vision, robotics, BIM integration, sustainable construction, and automation in construction processes. His work contributes to UN Sustainable Development Goals, particularly in sustainable cities and communities. Grants & Awards: Over $6M in grants from ARC, Austroads, and industry partnerships. Recognitions include Editor's Choice Paper (ASCE, 2019) and Outstanding Reviewer (Elsevier, 2016). Teaching: Courses like Risk Management in Engineering Projects and Infrastructure Research Project. Advises on PhD topics in computer vision, robotics, and BIM. Labs & Collaborations: ASCII Lab focuses on smart, sustainable solutions for construction. Collaborates with global researchers and organizations like SPARC Hub and Building 4.0 CRC.
Bruce A. Maxwell is a Teaching Professor and Assistant Director of Computing Programs at Northeastern University’s Seattle Campus, following roles as Chair of the Computer Science (CS) Department at Colby College (2013–2020) and leadership in establishing the Khoury College MS CS Align Program at the Roux Institute (2020–2022). His academic journey includes affiliations with Northeastern’s Seattle Campus and ongoing collaboration with Colby CS as a research scientist. He specializes in Computer Vision, Robotics, Computer Graphics, Game Design, and Data Analysis, with notable contributions to concussion management research through the Maine Concussion Management Initiative (MCMI), focusing on sports-related injury analysis and symptom monitoring. His research spans over two decades, with significant work in human-robot interaction, autonomous systems, and educational technology. Notable projects include developing tools for real-time shadow removal in autonomous driving contexts and analyzing cognitive outcomes in student-athletes post-concussion. Maxwell has authored over 50 peer-reviewed publications, emphasizing interdisciplinary approaches bridging computer science, sports medicine, and educational policy. Teaching innovations include integrating thematic elements (e.g., Lord of the Rings) into CS1 coursework and advocating for writing in computer science curricula. He maintains active roles in academic service, including SIGCSE conference contributions and panel discussions on gender equity in tech education. Education: Ph.D. in Robotics from Carnegie Mellon University (1996), M.Phil. in Engineering from Cambridge University (1993). Awards: Recognized for pedagogical contributions but no named awards listed in provided materials. Labs/Teams: Collaborates with the Maine Concussion Management Initiative and Khoury College’s Align Program team.
Wenchao Li is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University, directing the Dependable Computing Laboratory. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences, along with a B.A. in Economics from UC Berkeley. His research focuses on dependable computing, applying formal verification, machine learning, and control theory to cyber-physical systems, electronic design automation, and AI safety. Key research interests include neural network verification, safe reinforcement learning, autonomous systems security, and resilient control strategies for connected vehicles. His work emphasizes provable safety guarantees and defense against adversarial attacks in critical infrastructure systems. Notable awards include the ACM Outstanding Ph.D. Dissertation Award and the Leon O. Chua Award. His lab investigates topics such as neural network repair, secure multi-robot coordination, and formal methods for autonomous systems. He advises students like Jiameng Fan and collaborates on projects funded by grants in AI safety and cyber-physical systems. Labs/Teams: Dependable Computing Laboratory Grants: Focus on formal verification, AI safety, and autonomous systems resilience
Dr. Sohrab Zendehboudi is an Equinor Chair Professor and research lead in the Department of Chemical and Process Engineering at Memorial University's Faculty of Engineering and Applied Science. His work focuses on energy and environmental challenges through experimental and modeling approaches. He has over 15 years of experience across academia and industry in Iran, Kuwait, the U.S., and Canada. He holds a PhD in Chemical Engineering (specializing in transport phenomena) from the University of Waterloo. Research interests include carbon capture, utilization, and sequestration (CCUS), renewable energy systems, process systems engineering, and advanced wastewater treatment. He leads a large research team addressing theoretical and practical challenges in energy sustainability and environmental protection. Key achievements include the 2023 Lectureship Award. His publications span topics like hydrogen production, CO2 storage, solar energy systems, and novel adsorbent materials. He actively seeks graduate students and researchers skilled in experimental work, numerical modeling, and machine learning for energy applications. Education: PhD in Chemical Engineering (University of Waterloo) Key Areas: CO2 Management, Bioenergy, Adsorption Technologies Labs/Teams: Large interdisciplinary research group Grants: Focus on renewable energy and sustainability projects
Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building
Professor Zoheir Sabeur is Professor of Data Science and Artificial Intelligence at Bournemouth University (2019–present) and Head of the Processes and Behaviour Understanding (PRO_BU) Research Group. He concurrently serves as Visiting Professor of Data Science at Colorado School of Mines (2017–present) and held the position of Science Director at the IT Innovation Centre, University of Southampton (2009–2019). Over three decades he has led more than 30 large-scale projects as Principal Investigator, securing over £12 million of funding from the European Commission, UKRI, DSTL, NERC, EPSRC and industry. Education PhD in Theoretical Physics, University of Glasgow (1990) MSc in Theoretical Physics, University of Glasgow (1986) BSc First-Class Honours in Physics and Applied Mathematics, Université d'Oran (1984) Advanced Leadership Programme, Ashridge Business School (2011) Research Interests Professor Sabeur’s research focuses on the fundamental theory and application of data science and artificial intelligence to understand complex human, natural and industrial processes and behaviours. His work spans multi-modal sensing, big-data analytics and machine-learning algorithms that extract actionable knowledge from large heterogeneous datasets. Application domains include: Healthcare: AI-driven diagnostics and prognostics for chronic diseases such as COPD, asthma and cancers through omics and phenotypic data integration. Environmental & Climate: Earth-observation analytics for wildlife migration and climate-change impact assessment using satellite data and global grid systems. Maritime & Cyber-Physical Security: Real-time risk assessment for shipping in extreme environments, smart-city safety and critical-infrastructure protection using computer vision and sensor fusion. Recent research has produced novel AI classifiers that analyse lung-auscultation audio signals to grade COPD severity, as well as digital-twin frameworks for detecting malicious behaviour in urban spaces. Scientific Awards & Recognition Fellow of the British Computer Society (FBCS) Fellow of the Institute of Marine Engineering, Science & Technology (FIMarEST) Chartered Engineer (CEng) and Chartered Physicist (CPhys) Multiple ORS Awards (1987, 1988, 1989) Grants & Doctoral Supervision Professor Sabeur has secured and led more than 40 funded projects since 1996, including recent grants such as INSIGHT (NIHR, 2024) and S4AllCities (H2020, 2020). He currently supervises three ongoing PhD students at Bournemouth University and has successfully graduated three others, covering topics from computational hydrodynamics to AI-based respiratory-disease analytics. He welcomes enquiries from prospective postgraduate researchers interested in data science, AI and interdisciplinary applications under schemes such as UKRI and Horizon Europe.
Yang Fan is an Associate Professor at the Shenzhen University of Technology, currently serving as Deputy Director of the Shenzhen Key Laboratory of Marine Energy and Environmental Safety and Deputy Director of the Center for Frontier Science and Engineering Applications of Surfaces and Interfaces. He is a recipient of the Shenzhen 'Peacock Plan' Overseas High-Level Talent Program and Pingshan District Second Prize in the 2020 Shenzhen Innovation and Entrepreneurship Competition. Educational Background: Bachelor in Materials Science (2006), Huazhong University of Science and Technology Master in Materials Science (2009), University of Alberta PhD in Chemical Engineering (2015), University of Alberta Research Interests: Focuses on magnetic functional materials, silicon-carbon anode materials for lithium-ion batteries, and superhydrophobic coatings. His work on oil-water emulsion stability mechanisms and nanosilver composite applications has been recognized by major energy companies. Prominent Research Trends: Publications highlight advancements in energy storage materials (e.g., potassium-ion battery anodes), functional coatings for water treatment, and innovative carbon encapsulation strategies for silicon nanoparticles in batteries. Scientific Awards: Shenzhen 'Peacock Plan' Overseas High-Level Talent Program Nanshan District Pilot Talent Guangdong Province Yuyue Card 2019 Guangdong Provincial University Achievement Transformation Competition - First Place in Environmental Protection and New Materials 2020 Shenzhen Innovation and Entrepreneurship Competition - Third Place in Finals Grants & Projects: Currently leads the Shenzhen Key Laboratory of Marine Energy and Environmental Safety (5000k RMB, 2021-2023) and co-leads the Shenzhen University of Technology's Center for Surface and Interface Science (10,000k RMB, 2021-2023). Previously contributed to NSERC-funded projects in Canada and Guangdong's leading talent program. Labs & Teams: Associated with the Shenzhen Key Laboratory of Marine Energy and Environmental Safety and the Center for Surface and Interface Science and Applied Engineering at Shenzhen University of Technology.
Lyndia Wu is an Assistant Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science, where she holds the prestigious Canada Research Chair in Wearable Brain Injury Sensing. She leads the SimPL (Sensing in Biomechanical Processes Lab) and maintains an active research program focused on biomechanics and medical device development. Her educational background includes: B.A.Sc. from the University of Toronto M.S. from Stanford University Ph.D. from Stanford University Postdoctoral Fellowship from Stanford University Dr. Wu's research program centers on developing novel sensing and data analytics technologies to study human biomechanics in health and disease states. Her primary research areas encompass brain injury or concussion biomechanics using advanced sensing, modeling, and machine learning approaches, as well as the development of innovative sensors and algorithms for studying sleep disorders like obstructive sleep apnea. She specializes in wearable sensors for brain health monitoring, traumatic brain injury mechanisms, and AI applications in healthcare settings. Analysis of her recent publications reveals a strong focus on sports-related head impacts (particularly in soccer), EEG monitoring following impacts, and sleep monitoring after concussions. Her work demonstrates interdisciplinary collaboration across biomechanical engineering, neuroscience, and clinical medicine, with publications spanning biomechanics, neurotrauma, biomedical instrumentation, and signal processing domains. Dr. Wu has received significant recognition for her work, including: Scholar Award from the Michael Smith Foundation for Health Research (2019) Junior Faculty Teaching Award from UBC Mechanical Engineering (2022) She actively supervises graduate students in Mechanical Engineering programs (MASc and PhD) and collaborates extensively across disciplines. Dr. Wu is affiliated with multiple research centers including the Institute for Computing, Information and Cognitive Systems (ICICS), Origins of Balance Deficits and Falls, and SmarT Innovations for Technology Connected Health (STITCH), reflecting her interdisciplinary approach to solving complex biomedical challenges. As director of the SimPL lab, she leads a research team developing cutting-edge sensing solutions for biomechanical processes with particular emphasis on brain injury prevention, monitoring, and recovery assessment through innovative engineering approaches.
Ann Bostrom is the Weyerhaeuser Endowed Professor in Environmental Policy at the Evans School of Public Policy & Governance, University of Washington, where she joined the faculty in 2007 after serving as Associate Dean for Research and Professor at Georgia Tech's Ivan Allen College. She co-directed the NSF Decision Risk and Management Science Program and serves on the AAAS and Washington State Academy of Sciences boards. Her educational background includes: Ph.D. in Public Policy Analysis, Carnegie Mellon University M.B.A., Western Washington University B.A. in English, University of Washington Postdoctoral studies in Engineering and Public Policy, Carnegie Mellon University Postdoctoral studies in cognitive survey methodology, Bureau of Labor Statistics Bostrom's research centers on risk perception, communication, and management in environmental policy and uncertain decision contexts. She investigates causal misconceptions about climate change, earthquake risk awareness, and pandemic risk communication, bridging social/behavioral sciences with weather and climate risk management through efficacy-focused frameworks. Her 2017-2021 publications reveal concentrated work on climate change communication, natural hazards, and pandemic risks. Key themes include causal thinking's impact on policy support, risk message design efficacy, and cross-cultural risk perception comparisons, frequently contributing to National Academies reports on science communication and hazard management. Major scientific recognitions include: 2020 Distinguished Educator Award (Society for Risk Analysis) 1997 Chauncey Starr Award Elected fellow of AAAS, WSAS, and Society for Risk Analysis ASA/NSF/BLS Research Associateship (1991-92) Fulbright Fellowship (1989-90) Patricia Roberts Harris Fellowship (1988-89) She has secured major funding from NSF, EPA, and NIH, currently co-leading the Cascadia Coastlines and Peoples Hazards Research Hub and NSF AI Institute for Trustworthy AI in Weather/Climate. Advisory roles include National Renewable Energy Laboratory Decision Science Committee and Earthquake Hazards Reduction Advisory Committee. At UW, Bostrom co-chairs Environments and Populations research in the Center for Studies in Demography and Ecology, serves on EarthLab's steering committee, and participates in the Program on Climate Change Governing Board, while maintaining affiliations with Carnegie Mellon's Center for Climate and Energy Decision Making.
Goran Oreški is an Associate Professor and Head of the Laboratory at the Faculty of Informatics in Pula (University Jurja Dobrile, Croatia), where he has been employed since 2019. He teaches courses on databases, object-oriented programming, data warehousing, and artificial intelligence at both undergraduate and graduate levels. Education: Ph.D. in Informatics (2016), Faculty of Organization and Informatics Industry Experience: 9 years as software architect and programmer in banking sector Research Focus: Artificial Intelligence systems, classical machine learning algorithms, and deep learning architectures. His work bridges theoretical advancements with practical applications in autonomous vehicles, traffic monitoring, and financial risk assessment. Recent Publication Trends: 2023-2025 works emphasize generative AI for synthetic credit data, traffic object segmentation with monocular cameras, and context-aware detection models (YOLO*C). Earlier works focus on genetic algorithms and ensemble learning for imbalanced datasets. Awards: Google RFP Award for autonomous vehicle research Highly Cited Paper (Web of Science, top 1%) Best Paper at CECIIS conference Leadership: Director of FIPU Laboratory since 2022, leading projects like ai.Shuttle (autonomous mini-bus) and CenAI (industry collaboration with Cenosco).
