Dr. Craig Hancock is a Research Professor in Geospatial Engineering with 15 years of research experience in Surveying and Geodesy. His expertise spans GNSS error mitigation, structural monitoring, and geospatial techniques for digital construction. He has supervised 10 PhD students and published over 80 academic papers. Education: BSc and PhD in Surveying/Geomatics Key Projects: Principal Investigator for projects on GNSS error mitigation, structural health monitoring, and marine economy technology. His research focuses on three core areas: GNSS error categorization and mitigation (particularly ionospheric effects), structural and environmental change monitoring, and geospatial data acquisition for BIM and digital construction. Recent work includes improving 3D modeling accuracy, UAV-based GNSS spoofing detection, and BIM-enabled facility management in healthcare infrastructure. His articles explore topics like sensor optimization, structural dynamics, and geospatial data fusion. Grants include £150k for bridge deformation studies and £9k for ionospheric error analysis. He actively contributes to teaching and enterprise initiatives, integrating geospatial technologies with industry needs.
Erik Prytz is a Senior Associate Professor in Cognitive Science at the Department of Computer and Information Science (IDA) at Linköping University. His research focuses on applying human factors principles to improve safety-critical systems, particularly in emergency response domains such as first aid, disaster medicine, and prehospital care. He holds a PhD in Human Factors Psychology and has served in roles including Director of the Forum Securitatis graduate school and Program Chair for the Cognitive Science BSc program. Education: PhD in Human Factors Psychology (Old Dominion University, 2014), MSc in Cognitive Science (LiU, 2010). Research Interests: Simulation-based training, stress and mental workload, emergency responder teamwork, and human-system interaction in crisis scenarios. His work emphasizes interdisciplinary collaboration, combining cognitive science, computer science, and medicine to enhance emergency response systems. Recent projects explore driver behavior toward emergency vehicles, ad-hoc responder group dynamics, and optimal placement of bleeding control kits in public spaces. He contributes to initiatives like the Center for Advanced Research in Emergency Response (CARER) and the Forum Securitatis graduate school. Erik’s teaching includes courses on human factors, distributed cognition, and emergency response systems. He actively participates in curriculum development and quality assurance committees within the Faculty of Arts and Sciences.
Professor Chris Lee is a faculty member in the Department of Transportation Science and Engineering at the University of Windsor's Faculty of Engineering. His research focuses on advancing transportation safety through the analysis of driver behavior, traffic flow dynamics, and the integration of emerging technologies like autonomous vehicles and machine learning. Key areas include collision risk prediction, driver vigilance assessment, and the development of advanced car-following models. He has contributed to initiatives such as the Transportation Science and Engineering scholarship program, supporting student research in innovative technologies like driving simulators for lane change behavior studies. His work bridges engineering and human factors, addressing challenges such as driver response to autonomous systems, heavy vehicle traffic management, and cross-cultural automotive design. Lee's interdisciplinary approach leverages data analytics, physiological signals, and machine learning to solve real-world transportation problems. His research has implications for policy-making, infrastructure design, and vehicle safety standards. Lee has collaborated extensively on projects analyzing crash precursors, variable speed limits, and the impact of ITS (Intelligent Transportation Systems) on safety. His publications span over two decades, demonstrating a commitment to both academic rigor and practical applications in transportation engineering. Notable contributions include refining car-following models, studying driver aggression, and evaluating the effectiveness of traffic management strategies.
Haitham Al-Deek is a Professor in the Department of Civil, Environmental, and Construction Engineering at the University of Central Florida's College of Engineering and Computer Science. He leads the Intelligent Transportation Systems and Data Analytics Lab and has over 32 years of experience in transportation engineering, planning, and operations. His work is nationally recognized, particularly in freeway operations and intelligent transportation systems (ITS). Ph.D., Civil Engineering-Transportation Engineering, University of California, Berkeley (1991) M.S., Civil Engineering-Transportation Engineering, University of California, Berkeley (1987) B.S., Civil Engineering (with Honors), University of California, Berkeley (1985) Dr. Al-Deek's research focuses on wrong-way driving countermeasures, connected and automated vehicles, traffic safety, and data analytics. He pioneered innovative ITS solutions for detecting and preventing wrong-way driving, including the development of a high-success-rate detection system in partnership with the Central Florida Expressway Authority (CFX). His work extends to freight transportation, electronic toll collection, and sustainable transportation systems. He has also contributed to safety performance functions and driver behavior modeling. His recent publications highlight advanced methodologies in network screening for crash modeling, the use of crowdsourced data (e.g., Waze) for incident detection, optimization of wrong-way driving countermeasures, and benefit-cost analyses of safety technologies. These works reflect a strong trend toward data-driven, real-time, and cost-effective solutions in transportation safety and operations. Scientific awards and recognitions include: TRB Chairman Award (2018, 2012) Multiple TRB Best Paper Awards (Freeway Operations and Regional TSM&O, 2023–2003) TRB Best Student Paper Awards (2022, 2019, 2018, 2017) UCF Excellence in Research Award (2018) UCF Researcher of the Year (1999) Distinguished Researcher, UCF College of Engineering (2003) Dr. Al-Deek has supervised 15 Ph.D. students and 29 M.S. theses and has secured over $10.3 million in research funding from agencies including FDOT, TRB, USDOT, and CFX. He serves as a technical editor for TRR and associate editor for the Journal of Intelligent Transportation Systems. He also chaired key TRB paper review subcommittees and is an active professional engineer in Florida. He leads the Intelligent Transportation Systems and Data Analytics Lab, which focuses on real-world applications of ITS, data warehousing, and advanced analytics for transportation safety and efficiency.
Daniela C. A. Pigosso is a Professor of Design for Absolute Sustainability at DTU Construct, Department of Civil and Mechanical Engineering, Technical University of Denmark. She leads the ERC Consolidator project REBOUNDLESS and is a key figure in sustainable design and circular economy research. Her work bridges academia and industry, with strong international collaboration and policy impact. Research Interests: Her expertise spans Sustainable Design, Circular Economy, Rebound Effects, Eco-innovation, and Engineering Design. She focuses on how product development can drive absolute sustainability, prevent unintended consequences of efficiency gains, and promote systemic change in manufacturing and service systems. Her work contributes to multiple UN Sustainable Development Goals. Recent Research Trends: Her latest publications highlight decision-making tools for sustainability trade-offs, behavioral mechanisms behind rebound effects, circularity metrics aligned with EU frameworks, and strategies for industrial transition. There is a clear trend toward integrating behavioral science, policy, and industrial application in circular economy research. Scientific Awards: Grundfos Prize - The Stars of Tomorrow (2024) ACPN Medal Award - Young Researcher (2021) Best Paper Award (2015) Best Paper Award (2013) Design Society's Reviewers' Favorite (2020) Advising and Grants: She is main supervisor for multiple PhD projects on rebound effects, carbon reduction, and simulation modeling. She leads high-impact research funded by the European Research Council and other national/international bodies, demonstrating strong grant acquisition and project leadership. Labs and Teams: She is part of DTU Construct, a research environment focused on sustainable construction and engineering design, and collaborates extensively within the Design Society network and the Biomimicry Institute.
Lynn Kistler is a Professor in the Department of Physics & Astronomy at the University of New Hampshire (UNH), part of the College of Engineering and Physical Sciences. Her research focuses on plasma physics, space weather, and magnetospheric dynamics, particularly investigating the interactions between the solar wind and Earth's magnetosphere-ionosphere system. She holds a Ph.D. in Physics from the University of Maryland, along with a B.S. from Harvey Mudd College. Dr. Kistler's work emphasizes understanding plasma processes such as ion outflow from the ionosphere, magnetic reconnection, and storm-time magnetospheric evolution. She has led studies using data from missions like the Van Allen Probes, Solar Orbiter, and Cluster, contributing to advancements in instrumentation (e.g., the SWA suite) and computational modeling. Her research bridges observational analysis, theoretical frameworks, and machine learning to address challenges in space weather prediction and plasma dynamics. Key areas of her research include the role of ionospheric ions (O⁺, H⁺) in plasma sheet dynamics, the effects of geomagnetic storms on ring current formation, and the behavior of heavy ions in near-Earth space. She has authored or co-authored over 260 publications, spanning journals like Nature Communications , Geophysical Research Letters , and Journal of Geophysical Research . Dr. Kistler has secured grants and collaborations through initiatives like the NASA Interstellar Mapping and Acceleration Probe (IMAP) and has served as a co-investigator on multiple missions. Her work emphasizes interdisciplinary approaches, combining spacecraft observations with ground-based data and numerical simulations to unravel the complexities of Earth's space environment.
Daniel Beat Müller serves as Professor at the Industrial Ecology Programme within the Department of Energy and Process Engineering at the Norwegian University of Science and Technology (NTNU), Trondheim. His office is located at Realfagbygget Gløshaugen (E4-120) with contact details daniel.mueller@ntnu.no and +4791897755. His research centers on analyzing human needs in relation to material/energy flows and environmental impacts, with two primary focus areas: (i) urban evolution and associated material flows for managing building/infrastructure stocks, and (ii) national/global metal cycles to identify supply constraint reduction strategies. His methodology integrates design, modeling, and decision-making through transdisciplinary stakeholder engagement. Müller teaches Material Flow Analysis and Systems Analysis of the Built Environment for Industrial Ecology and Civil Engineering Master's students. His research outputs demonstrate strong trends in circular cities, critical mineral management, and urban metabolism, with recent publications emphasizing building information modeling, electric vehicle battery systems, and phosphorus cycling. His work consistently addresses resource criticality within energy transition contexts. As (ad interim) chair of the International Society of Industrial Ecology’s MFA-ConAccount section, he contributes to methodological standardization. He previously served on the U.S. National Research Council’s Committee on Defense Stockpiles and remains active in Switzerland's National Research Programme 65 "New Urban Quality". Müller supervises numerous Master's and doctoral students, with thesis topics spanning lithium-ion battery recycling, building stock dynamics, and urban resource flows. His projects frequently involve industry collaboration for practical implementation of material stewardship strategies.
Dr. Ivan Duric is a Research Fellow at the Department of Agricultural Markets, Agricultural Marketing and World Agricultural Trade, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale), Germany. Since October 2008 he has led and contributed to numerous international research projects focusing on digital transformation, trade policy, and value-chain analysis in agriculture and food systems. Education: Doctorate (Dr.) “summa cum laude” in Agricultural Economics, Faculty of Agriculture, Martin Luther University Halle-Wittenberg. Research Interests: Dr. Duric’s core expertise lies at the intersection of digital technologies and agri-food economics . His work explores how machine learning, blockchain, and immersive analytics reshape agricultural value chains, enhance transparency, and improve competitiveness. He continually investigates price transmission mechanisms , the impact of trade policy shocks (e.g., export bans, import restrictions), and pathways to strengthen food security in transition and emerging economies. Across more than forty peer-reviewed articles and policy briefs, a clear trend emerges: rigorous empirical assessment of how policy interventions and digital innovations jointly determine market outcomes—from wheat-to-bread chains in Serbia to salmon value networks spanning Norway, France and Poland. Awards & Recognition: Doctoral degree awarded “summa cum laude” (highest distinction), Martin Luther University Halle-Wittenberg. Grants & Collaborative Projects: Dr. Duric has co-ordinated or served as senior researcher in major EU and German-funded initiatives including AGRICISTRADE, AgriDigital, AGRIIMMERSE, VALUMICS, SecureFood, GERUKA, eTrust-Food, DITAC, GTRS, STARLAP, TAAST, UaFoodTrade , and the IAMO XR Lab . These projects investigate global grain trade, digital platform adoption, consumer trust, resilience of food systems, and immersive data analytics. Labs & Teams: He is a founding member and scientific lead of the IAMO XR Lab , where virtual-reality and immersive analytics are leveraged to visualize and interpret complex agricultural market data, creating new avenues for stakeholder engagement and policy dialogue.
Luis Merino Cabañas is a Professor at the Universidad Pablo de Olavide , affiliated with the Deporte e Informática department and leading the SRL Service Robotics Laboratory . His research focuses on robotics, systems engineering, and automation, with a specialization in human-robot interaction and path planning. Education : PhD in Systems Engineering from the Universidad de Sevilla (2007), where his thesis explored cooperative perception techniques for multiple unmanned aerial vehicles in forest fire detection. Research Trends : Recent work (2023–2025) emphasizes 3D path planning, sensor fusion (LiDAR, radar, inertial systems), neural distance fields for safe navigation, and socially aware robotics. His studies integrate AI, genetic programming, and multi-modal perception for applications in construction, healthcare, and GNSS-denied environments. Labs & Teams : He leads the SRL Service Robotics Laboratory , contributing to projects like the Skyeye team and BIM2ROS integration for construction robotics.
Seongjin Choi is an Assistant Professor in the Department of Civil, Environmental, and Geo-Engineering at the University of Minnesota, Twin Cities , where he began his role in January 2024. His research bridges Urban Mobility Data Analytics , Spatiotemporal Modeling , and Deep Learning to advance transportation systems. Affiliated with the Center for Transportation Studies , Minnesota Robotics Institute , and Data Science Initiative , he leads the Choi Research Group . Education: Ph.D., Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), 2021 M.S., Civil and Environmental Engineering, KAIST, 2017 B.S., Civil and Environmental Engineering, KAIST, 2015 His research focuses on Urban Mobility Data Analytics and Deep Learning to optimize transportation systems. Key areas include: Spatiotemporal Data Modeling for forecasting and imputation Generative AI applications in transportation data Reinforcement Learning for Connected Automated Vehicles (CAV) Cooperative Intelligent Transport Systems (C-ITS) Recent publications in Transportation Science and Transportation Research Part C highlight his work on probabilistic traffic forecasting , deep generative models , and vision-language-action frameworks for autonomous systems. His methodologies often combine AI-driven analytics with real-time mobility optimization . Dr. Choi serves as: Associate Editor of The Journal of the Korean Society of Transportation (JKST) , 2023–Present Guest Editor for Journal of Advanced Transportation special issue on "Advanced Data Intelligence Theory and Practice in Transport 2023", 2023–2024 He actively seeks PhD students/postdocs for 2025 cohorts focused on machine learning for transportation challenges. Current projects include AI-enhanced traffic forecasting, CAV control, and urban air mobility (UAM) integration studies.
Barbara Bigliardi is an Associate Professor at the Department of Engineering and Architecture, University of Parma, with national scientific qualification for full professor in Economic-Management Engineering (SSD ING-IND/35). She serves as President of the Management Engineering Program at University of Parma and Director of Bachelor's/Master's programs at University of San Marino, co-leading double-degree initiatives between the two institutions. Over 100 publications (57 SCOPUS-indexed) with H-index=20 Editorial roles: Cambridge Scholars Publishing (2019), MDPI Sustainability, Sci, European Journal of Innovation Management Key research areas: Open Innovation, Technology Transfer, Food Industry Innovation, Industry 4.0, Supply Chain Sustainability Recent Publications (2024-2025) demonstrate leadership in: Industry 4.0 integration with circular economy AI applications in public administration and healthcare Digitalization of food supply chains Green startup resource orchestration Simulation-based optimization in remanufacturing Sustainable additive manufacturing Scientific Recognition : 2005 Emerald Highly Commended Award 2013 Most Cited Paper in Trends in Food Science & Technology 2019 Highly Cited Paper in Review of Policy Research Research Leadership includes: National Observatory on Start-ups (President since 2021) National Observatory on Reputation (Vice President since 2019) INAIL-funded mobile risk assessment systems (2018-2020) INAF space technology transfer projects (2018-present) Academic Contributions : Supervised over 300 theses Deputy Coordinator of Industrial Engineering Doctoral Program Director of Management Engineering Programs (Parma & San Marino) Founder of academic spin-offs: Sistemi per il marketing di contenuto S.r.l. (2016-present), Univenture SrL (2006-2010)
Niklas Grabbe is a postdoctoral researcher at the Chair of Ergonomics, Technical University of Munich (TUM), where he leads the research group on "Automated Driving and Mobility Systems" and is establishing a new working group focused on "Modelling complex socio-technical systems" with emphasis on Resilience Engineering and the Functional Resonance Analysis Method (FRAM). His research centers on human factors in automated and teleoperated driving, mobility systems, and behavior modeling. He applies systems engineering principles to analyze safety and usability, particularly using FRAM to study performance variability and resilience in socio-technical systems. His work addresses critical challenges in urban automated driving, teleoperation, and multi-driver interactions through rigorous quantitative modeling and field studies. Analysis of Grabbe's publications reveals a dominant trend in applying FRAM to driving scenarios, with recurring themes of safety enhancement, human-automation interaction, and usability evaluation. His interdisciplinary work bridges transportation psychology, safety engineering, and human-computer interaction, consistently emphasizing systems thinking to solve complex problems in automated vehicle technology. Grabbe contributes to academic instruction through courses like "Modelling Complex Sociotechnical Systems" (Winter 2025/26). He operates within TUM's Chair of Ergonomics infrastructure, utilizing specialized labs including driving simulators and ergonomic mockups to support experimental research in human factors and automated systems.
Alfio Grillo is a Full Professor at the Department of Mathematical Sciences (DISMA) of Politecnico di Torino, with research interests in biomechanics, continuum mechanics, and mathematical physics. His expertise spans classical mechanics and multiscale modeling of biological tissues. Research Focus: Grillo's work integrates analytical mechanics with nonholonomic constraints, fractional calculus applications, and multiscale modeling of growth/remodeling phenomena in biological systems. Recent articles emphasize poroelasticity, viscoelastic composites, and bi-phasic material behavior. Scientific Contributions: Editorial roles in leading journals since 2014 Member of INdAM-GNFM since 2009 Recipient of National Scientific Qualification in 2017 €128,609 PRIN grant for multiscale biological modeling Academic Leadership: Supervises PhD students in Civil Engineering, Mathematics, and Mathematical Engineering. Teaches advanced courses in Differential Varieties, Variational Methods, and Porous Media Mechanics.
Fedor Dokshin is an Assistant Professor in the Department of Sociology at the University of Toronto, Downtown Toronto (St. George) campus. His research bridges computational social science with environmental and political sociology, focusing on energy transitions, partisan dynamics, and social network structures. Key research areas include racial and income disparities in solar photovoltaic adoption, policy feedback mechanisms in renewable energy programs, and partisan influences on environmental decision-making. Fields of Study: Computational and Quantitative Methods, Environmental Sociology, Political Sociology, Social Networks Areas of Interest: Computational social science, Energy and the environment, Political polarization Research Trends: Dokshin's publications reveal a focus on energy justice, behavioral diffusion models, and political polarization. His work combines computational methods with environmental policy analysis, examining how socioeconomic factors and partisan identities shape renewable energy adoption. Articles demonstrate geographic heterogeneity in opposition to extraction projects, digital discourse analysis techniques, and institutional dynamics affecting scholarly knowledge production. Methodological Emphasis: Utilizes large-scale data analysis, spatial modeling, and automated textual analysis to explore energy-environment-society intersections. Research highlights the tension between technical solutions and social equity in energy transitions, with recurring themes of policy design, public engagement, and networked political behavior.
Ranjana Mehta serves as Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison and Affiliate Faculty in the BerbeeWalsh Department of Emergency Medicine, directing the NeuroErgonomics Laboratory while co-directing the Texas A&M Ergonomics Center and holding faculty fellowships at the Center for Population Health and Aging and Center for Remote Health Technologies and Systems. Her academic background includes: PhD in Industrial & Systems Engineering from Virginia Tech MS in Industrial Engineering from University at Buffalo BE in Production Engineering from University of Mumbai, India Mehta pioneers neuroergonomic approaches to study human performance under fatigue and stress in safety-critical environments, developing closed-loop human augmentation technologies for emergency response, space exploration, and oil/gas operations. Her work integrates adaptive AR/VR interfaces, wearable systems, human-robotic interactions, and brain-computer interfaces to enhance human-technology partnerships through user-centered design. Analysis of her recent publications reveals strong emphasis on fatigue detection in offshore workers, trust dynamics in human-robot collaboration, and sex-specific neural adaptations to exoskeletons. Her research spans human factors engineering, neuroscience, and industrial engineering, employing multimodal physiological metrics to address real-world safety challenges across high-risk industries. Her scientific recognition includes: 2024 Virginia Tech, ISE Distinguished Alumni 2023 Human Factors and Ergonomics Society, Fellow 2022 IISE Award for Technical Innovation in Industrial Engineering 2022 NASA ideas* Fellow 2022 NASEM Gulf Research Early Career Research Fellow 2022 The Human Factors Prize 2021 Virginia Tech, ISE Emerging Leaders Award 2021 Texas A&M Presidential Impact Fellow 2020 TEES Engineering Genesis Award 2020 Virginia Tech Engineering Outstanding Recent Alumni Award 2019 HFE Woman of the Year 2017 William C. Howell Young Investigator Award Her research receives funding from multiple federal agencies and industry partners supporting neuroergonomic solutions for worker safety. She mentors graduate students through ISyE 699/790/890/990 research courses and PSYCH 859 special topics, focusing on human factors engineering applications in emergency response and healthcare systems. Mehta leads interdisciplinary teams across the NeuroErgonomics Laboratory and Texas A&M Ergonomics Center, integrating engineering, neuroscience, and emergency medicine expertise to develop real-time fatigue monitoring systems and adaptive interfaces for high-stakes occupational environments.
