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Wendy Ju is an Associate Professor of Information Science at Cornell Tech, with appointments in the Cornell Ann S. Bowers College of Computing and Information Science, the Jacobs Technion-Cornell Institute, and the Technion-Israel Institute of Technology. Previously, she served as executive director of interaction design research at Stanford University's Center for Design Research and as an associate professor of interaction design at the California College of the Arts. Her work bridges human-computer interaction, design, and robotics with a focus on how interactive devices can communicate with people without interrupting them. PhD in Mechanical Engineering from Stanford University Master's degree in Media Arts and Sciences from MIT Professor Ju's research centers on implicit interactions, human-robot collaboration, and automotive interfaces. She investigates how people interact with automated systems in natural contexts, develops methods for early-stage prototyping of autonomous technologies, and examines the social implications of robotics in urban environments. Her work spans from theoretical frameworks to practical applications, with particular emphasis on designing systems that integrate seamlessly into human activities without demanding constant attention. Her recent publications reveal a strong trajectory toward understanding human-robot interaction in public urban spaces, with increasing focus on robot navigation in city streets, the social implications of autonomous vehicles, and the integration of generative AI in design processes. Her work consistently bridges theoretical HCI frameworks with practical applications in transportation, urban design, and everyday robotics. Inducted into the ACM SIGCHI Academy (2025) Multiple Honorable Mention Awards at ACM CHI and DIS conferences Best Paper Award at Multimodal Technologies and Interaction (2023) Best Student Paper Award at IEEE Intelligent Vehicles Symposium (2017) Best Demonstration Award at HRI (2017) Professor Ju actively mentors numerous PhD and master's students, many of whom have become leading researchers in HCI and robotics. Her research has been supported by significant grants from NSF and industry partners, enabling extensive field studies of human-robot interaction in real-world settings. She has pioneered methodologies for studying autonomous vehicle interactions through both simulated and naturalistic driving environments. Her work with the Jacobs Technion-Cornell Institute supports interdisciplinary research at the intersection of computing, design, and urban technology. She has established research partnerships with transportation authorities, automotive companies, and urban planning organizations to study how emerging technologies can enhance urban mobility while respecting human needs and social contexts.

• Interaction with Automation
• Interaction Design Research
• Human Robot Interaction
• +2 more

Yanxi Liu is a Professor in the Department of Computer Science and Engineering and the Department of Electrical Engineering at Pennsylvania State University. She is affiliated with the Huck Institutes of the Life Sciences and holds multiple NSF grants focusing on computational symmetry, regularity perception, and human movement analysis. Her work bridges computer vision, cognitive science, and medical imaging. Education details not explicitly listed in provided text. Key research areas include computational symmetry, near-regular textures, human perception of patterns, and medical image analysis. Notable projects include 'RI: Medium: From Vision to Dynamics' (2023-2026) and 'INSPIRE: Symmetry Group-based Regularity Perception in Human and Computer Vision' (2012-2016). Her research emphasizes symmetry-driven approaches for urban scene analysis, medical diagnostics (e.g., brain asymmetry in Alzheimer's), and dynamic motion modeling. She has co-authored over 100 publications and pioneered methods like lattice-based tracking and symmetry-based mid-sagittal plane extraction in neuroimaging. Funding includes grants from NSF totaling over $5M, supporting interdisciplinary work in vision science and AI. Collaborations span neuroscience, biomedical engineering, and architectural pattern analysis.

• Computer Vision
• Medical Imaging
• Computational Symmetry
• +4 more

SangHyung Ahn is a Lecturer at the School of Civil Engineering , University of Queensland (UQ), since 2017. He joined UQ as a postdoctoral research fellow in 2015 after earning his PhD in Civil Engineering (Construction Engineering and Management) from Purdue University, USA. Prior to his academic career, he worked as an assistant manager at Hyundai Engineering and Construction Co., Ltd. (2003-2007) and holds an MBA in international business from Hanyang University and a B.Sc in Civil Engineering from Korea University. Research Focus: Construction process modelling with virtual reality, decision support systems for construction, automation of data-driven simulation modelling, sensor-based operations analysis, and integration of Building Information Modelling (BIM). Teaching: Coordinates undergraduate courses Introduction to Project Management (CIVL3510) and Construction Engineering Management (CIVL4522) . Research Trends: His recent publications highlight interdisciplinary work in transportation engineering, structural design, and AI-driven simulation tools. Key themes include application of machine learning to car-following models, drone-based vehicle identification, and optimization of public transport systems using agent-based simulations. Supervision: Available for supervision, with completed supervision of PhD and Master’s theses on topics such as BIM-LCA integration, pedestrian trajectory analysis, and AI-driven driving behavior models.

• Construction Process Modelling
• Building Information Modelling (BIM)
• Agent-Based Simulation
• +3 more

Robert Piche is a Professor at the Computing Sciences Mathematics Research Centre, specializing in advanced signal processing, positioning systems, and sensor fusion. He holds a Doctor of Science (Technology) and Master of Science from the University of Waterloo, Canada (1986 and 1982, respectively). His research focuses on Kalman filters, Global Positioning Systems (GPS), particle filters, and indoor positioning technologies. He has contributed extensively to fields like satellite orbit prediction, non-line-of-sight (NLoS) positioning, and machine learning applications in biomechanics and robotics. Dr. Piche has authored over 230 publications and received recognition through an invitation/ranking in a 2014 competition. He actively participates in academic activities, including conference presentations and peer-review roles. His work bridges theoretical advancements and practical applications, with contributions to autonomous systems, sensor data analysis, and wearable technology. Collaborations span international institutions, reflecting his global impact in engineering and computer science disciplines.

• Kalman Filters
• Global Positioning Systems (GPS)
• Signal Processing
• +5 more

Yingying Wang is an Assistant Professor in the Computing and Software department at McMaster University , where she joined in January 2022. Her research focuses on generating expressive animations for AR/VR applications and games through interdisciplinary approaches combining Computer Graphics , Artificial Intelligence , and Human Behavior Analysis . Education : Bachelor and Master degrees from Nanjing University , Ph.D. from University of California, Davis (2017) Her research explores: Generative models for human motion style transfer Physics-based motion simulation Audio-driven character synthesis Dance choreography for virtual characters Cartoon animation perception Conversational character gesture synthesis Markerless hand motion capture Recent publications focus on 3D hand pose estimation , motion style transfer , gesture-locomotion coordination , and personality perception in virtual agents . Key methodologies include deep learning , multimodal data analysis , and real-time animation systems . Scientific contributions recognized through: $240,000 Labarge Catalyst Grant in Mobility in Aging (interdisciplinary team award) US Patent 10,796,482 (3D hand pose estimation) US Patent 9,811,937 (gesture-locomotion coordination) Teaching includes graduate and undergraduate courses in Computer Animation (CAS 737), Computer Graphics (COMPSCI 3GC3/SFWRENG 3GC3), and Software Development (COMPSCI 2ME3). Research group actively recruits Ph.D. and Master's students in graphics + deep learning domains.

• Artificial Intelligence
• Computer Gaming and Animation
• Computer Graphics
• +4 more

Dr. E. John Ward is an Associate Professor in Infrastructure Planning at The Bartlett School of Planning, University College London , where he also serves as Director of the MSc Infrastructure Planning, Appraisal and Development . His work bridges quantitative and qualitative methodologies in infrastructure appraisal, focusing on Cost-Benefit Analysis , Multi-Criteria Analysis , and Strategic Risk Mitigation . Education: BEng/MSc in European Civil Engineering, University of Warwick (1999) MSc/DIC in Earthquake Engineering and Structural Dynamics, Imperial College London (2001) PhD in Computer Modelling of Pedestrian Movement, UCL (2007) Research Focus: Success metrics for Mega Transport Projects and Infrastructure Interdependencies Integration of Sustainable Development Goals into appraisal frameworks Policy-led Multi-Criteria Analysis for complex stakeholder environments Professional Contributions: Senior Research Fellow at the OMEGA Centre External Examiner for MSc SEM4ID, University of Swansea (2018-2023) Consultancy roles for the European Investment Bank , EIB , and governments including Malta and Croatia Key Publications include foundational work on Policy-Led Multi-Criteria Analysis and Risk Management in mega infrastructure projects. His scientific award as Senior Research Fellow at the OMEGA Centre highlights his expertise in strategic infrastructure appraisal.

• Infrastructure planning
• Risk management
• Business cases for infrastructure
• +8 more

Rainald Loehner is a Distinguished Professor of Fluid Dynamics at George Mason University's Center for Computational Fluid Dynamics. Since 2003, he has led the Center for Computational Fluid Dynamics at George Mason University. He is currently a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS) for 2023, hosted by Professors Kai-Uwe Bletzinger and Roland Wüchner in the 'Adjoint-Based System Identification of Large-Scale Structures' Focus Group. Loehner received his Diplom Ingenieur (Maschinenbau) degree from the Technical University of Braunschweig, and his PhD and a DSc in civil engineering from the University College of Swansea, Wales. After teaching at Swansea for a year, he worked at the Naval Research Laboratory in Washington, DC, followed by a research professorship at George Washington University. He joined George Mason University as an associate professor and was promoted to full professor in 1995 and distinguished professor in 2004. With over 35 years of experience, Professor Loehner's research spans the complete pipeline of numerical solvers and simulation tools. His expertise includes pre-processing, grid generation, numerical methods, field solvers, parallel computing, adaptive mesh refinement, fluid-structure interaction, shape optimization, system identification, and computational crowd dynamics. His current work focuses on developing advanced field solvers for compressible and incompressible flows, acoustics, electromagnetic wave propagation, heat and mass transfer, structural mechanics, and fluid-structure interaction. Key application areas include blast mitigation, ship hydrodynamics, blood flow, contaminant transport, and pedestrian safety. Loehner's recent research output (2020-2024) shows a strong trend toward digital twin technology and adjoint-based methods for structural analysis and optimization. His publications focus on high-fidelity digital twins for detecting structural weaknesses, risk assessment in engineering systems, and optimization of sensor placement. His work bridges computational mechanics with machine learning approaches, particularly in system identification and inverse problems, demonstrating how computational methods can solve complex real-world engineering challenges. 2020: Ranked #15119 in the Stanford List of Most Influential Scientists of the World; #8 in Aerospace and Aeronautics 2010: Distinguished International Career Award, Argentine Association of Computational Mechanics 2008: Fellow, International Association for Computational Mechanics 2006: Associate Fellow, AIAA 2005: Honorary Professor, University of Wales Swansea 2005: Advisory Professor, Shanghai Jiao Tong University 2004: Distinguished Professor of Fluid Dynamics, George Mason University 1999: Computational Mechanics Achievements Award, Japan Society of Mechanical Engineering 1993: Doctor of Science in Civil Engineering, University College of Swansea 1979-1983: Studienstiftung des Deutschen Volkes (Top 1% of German Students) Professor Loehner has mentored numerous students through his work at George Mason University and has supervised research in computational fluid dynamics, structural mechanics, and related fields. His research has been supported by various grants from government agencies and industry partners, enabling the development of advanced simulation tools applied in aerodynamics, hydrodynamics, shock-structure interaction, and medical applications. His codes and methods have been widely adopted in industry and academia for applications ranging from aircraft and ship design to medical simulations and urban pathogen transmission modeling. Loehner leads the Center for Computational Fluid Dynamics at George Mason University, which focuses on developing cutting-edge computational methods for fluid dynamics and related multiphysics problems. The center works on strategic application areas including blast mitigation, ship hydrodynamics, blood flow simulation, and pedestrian movement modeling. As a TUM-IAS Fellow, he collaborates with the Chair of Computational Modeling and Simulation at TUM on adjoint-based system identification of large-scale structures, bringing together expertise in computational mechanics and digital twin technology to address complex engineering challenges.

• Computational Fluid Dynamics
• Numerical Methods
• Grid Generation
• +7 more

Dr. Ahmed F. Abdelghany is the Associate Dean for Research and Professor of Operations Management at the David O'Maley College of Business, Embry-Riddle Aeronautical University, since January 2006. He specializes in commercial airlines, airports, big data cloud computing, business analytics, and operations research models. Prior to his academic career, Dr. Abdelghany worked in enterprise optimization at United Airlines, Chicago. Education: Ph.D. in Civil Engineering (Transportation Systems) from the University of Texas at Austin (2001) Dr. Abdelghany’s research focuses on airline network planning, flight scheduling, simulation of complex transportation systems, and NextGen air traffic management. He has authored two influential books: Modeling Applications in the Airline Industry (Routledge 2010) and Airline Network Planning and Scheduling (Wiley 2018). His publications analyze airline operations, competitive dynamics, and crowd management in transportation facilities. He teaches courses like Airline Management (BA 315) and Airline Operations & Mgmnt (BA 609), and participates in industry short courses. Dr. Abdelghany contributes to research projects such as NextGen air traffic implementation, integrated airport initiatives, and benefit-cost analysis of arrival management systems. His work bridges academic theory with real-world airline and transportation challenges.

• Commercial Airlines
• Airports
• Big Data Cloud Computing
• +7 more

Prof. Dr. Hannes Taubenböck holds the Chair of Global Urbanization and Remote Sensing at the Julius-Maximilians University of Würzburg (Faculty of Philosophy, Institute of Geography and Geology) since 2022 and collaborates with the German Aerospace Center (DLR). His research bridges remote sensing with urban geography, focusing on: Global urbanization patterns and structural analysis Informal settlements (slums/refugee camps) Climate change and natural hazard vulnerability Migration dynamics via remote sensing and social media He obtained his PhD (2008) and habilitation (2019) at JMU Würzburg, preceded by geography studies at LMU Munich (1999-2004). His recent publications analyze: Climate impacts on African agriculture Urban permeability and walkability Border region disparities Heat exposure modeling Methodologically, he specializes in: Deep learning for earth observation Multi-modal data fusion Urban pattern classification Building stock analysis His work informs policy applications in: EU cohesion programs Disaster risk reduction Environmental justice Urban sustainability

• Remote Sensing
• Global Urbanization
• Urban Structure Analysis
• +6 more

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.

• Urban Mobility Data Analytics
• Spatiotemporal Data Modeling
• Deep Learning & Artificial Intelligence
• +3 more

Young Ook Kim is a Professor at the Department of Architecture, Sejong University. His research focuses on spatial morphology, space syntax, and urban design, with applications in pedestrian behavior analysis and urban regeneration. 1999 Ph.D., University College London 1994 M.S., University of Colorado, Denver 1986 B.S., Yonsei University His work explores the relationship between spatial layouts and human behavior, particularly in crowded environments. Recent studies include predictive modeling for crowd accidents and agent-based simulations for subway station design. Key methodologies involve space syntax and computational modeling. Latest research trends emphasize pedestrian safety, urban walkability, and regional spatial characteristics, leveraging space syntax tools and agent-based simulations to analyze crowd dynamics and urban configurations. He has collaborated extensively on projects related to spatial configuration and urban planning, with contributions to conferences like the International Space Syntax Symposium. His h-index is 7, with 13 Scopus citations on recent works. 2024: Crowd accident risk prediction, improved agent simulations, and regional walking behavior studies 2023: Pedestrian behavior analysis in Seoul's Gangnam Station 2022: Mega-shelter layout planning and user-behavior studies

• Spatial Morphology
• Space Syntax
• Urban Design
• +7 more

Andrew Robb is an Assistant Professor in the School of Computing at Clemson University. His research focuses on the societal impact of consumer virtual reality (VR), including user behavior adaptation, avatar embodiment effects, presence in VR, and perception studies. Prior to Clemson, he earned his PhD in the Virtual Experience Research Group at the University of Florida. He is funded by the NSF CHS Small grant #1717937 and collaborates with researchers like Sabarish Babu and Chris Pagano. His work explores topics such as cybersickness mitigation, pedestrian-AV interactions, and VR's therapeutic applications for social anxiety disorders. Education: PhD in Virtual Experience Research, University of Florida Research Interests: Longitudinal effects of VR exposure on user behavior Avatar embodiment and its real-world behavioral implications Measuring and enhancing presence in VR environments Perception of space and motion in virtual vs. real-world contexts Human-VR interaction design for accessibility and safety Social and ethical considerations of emerging VR technologies Key Research Trends: His recent work emphasizes VR's impact on spatial cognition, cybersickness reduction through interaction design, and leveraging VR for mental health interventions. Over 2023-2024, he has published extensively on avatarization effects, near-field interactions, and pedestrian-AV dynamics in immersive environments. Grants & Lab: Hosts the McAdams Hall 120 lab and has NSF-funded research on longitudinal VR exposure effects. Collaborates with automotive engineering teams on VR-based autonomous vehicle interaction studies.

• Virtual Reality
• Human-Computer Interaction
• User Behavior Analysis
• +3 more

Ehud Sharlin is a Professor in the Department of Computer Science at the University of Calgary, Faculty of Science. His research focuses on Human-Computer Interaction (HCI) with specializations in human-robot interaction, tangible interfaces, virtual/augmented reality, and autonomous vehicle interactions. He holds a Ph.D. in Computing Science from the University of Alberta (2003), and M.Sc. and B.Sc. degrees in Electrical and Computer Engineering from Ben-Gurion University of the Negev (1997 and 1990). Teaches CPSC 481: Human-Computer Interaction I Recipient of the NSERC Discovery Accelerator Award (2019), ACM Creativity & Cognition Honourable Mention (2018), and multiple academic excellence awards Active in industry collaborations, particularly in medical simulation (e.g., VRSpineSim) and geosciences (e.g., PLANWELL) Research explores: Embodied interaction through robotics and wearables Autonomous vehicle-pedestrian communication systems Immersive tools for creative and professional domains Accessibility in human-technology interfaces Publications span over 100 peer-reviewed works, emphasizing design methodologies, user experience in XR systems, and ethical considerations in sociotechnical systems. His work bridges technical innovation with human-centered design principles.

• Human-robot interaction
• Tangible user interfaces
• Virtual reality
• +4 more

Affiliations & Roles Lionel P. Robert Jr. is a Professor of Information and Robotics at the University of Michigan, holding joint appointments in the School of Information and the College of Engineering's Robotics Department. He directs the Michigan Autonomous Vehicle Research Intergroup Collaboration (MAVRIC) and is an affiliate faculty member at the National Center for Institutional Diversity and Indiana University's Center for Computer-Mediated Communication. His roles include editorial board positions at journals like the Journal of Computer Information Systems and leadership in professional organizations such as ACM and IEEE. Education Ph.D. in Information Systems, Indiana University (BAT Fellow, KPMG Scholar) M.B. from Indiana University, Bloomington M.S. degrees from Clemson University and University of Louisiana, Lafayette B.S. from University of Louisiana, Lafayette Research Focus Robert's research bridges collaboration through technology, with a focus on human-robot interaction, autonomous vehicles, and virtual teams. His work addresses trust in automated systems, human-AV communication, and the sociotechnical implications of robotics in workplaces and public spaces. Recent projects explore explanations for automated vehicles, security robots' societal acceptance, and AI ethics in healthcare and labor. Key Contributions He has published over 100 peer-reviewed articles in journals like MIS Quarterly and conferences such as CHI and HRI. His research has been funded by NSF, Toyota Research Institute, and the Army Research Laboratory. Notable outcomes include frameworks for AV trust repair, models of human-robot team performance, and critiques of AI-driven labor practices. Awards & Recognition ACM Distinguished Member IEEE Senior Member Carnegie Junior Faculty Development Fellowship 3× Teaching Commendation (2006–2008) Grants & Labs Current grants include studies on explainable AI, human-AV trust dynamics, and security robot design. The MAVRIC lab focuses on AV-pedestrian interactions while the CCMC explores digital communication's societal impact.

• Autonomous Vehicles
• Human-Robot Interaction
• Collaborative Robotics
• +5 more

Dana Rowangould serves as Assistant Professor in the Department of Civil and Environmental Engineering at the University of Vermont's College of Engineering and Mathematical Sciences. Her interdisciplinary work bridges engineering, economics, and social sciences to address transportation system challenges, with particular focus on improving mobility for constrained-travel populations. Her educational background includes: Ph.D. in Ecology (Environmental Policy emphasis) from University of California, Davis M.S. in Agricultural and Resource Economics from University of California, Davis B.S. in Civil and Environmental Engineering from Rice University Dr. Rowangould's research centers on transportation equity and justice , rural travel behavior , and accessibility measurement , with significant contributions to understanding rural mobility constraints, transit recovery post-pandemic, and policy impacts on vulnerable populations. Her methodology integrates spatial analysis, behavioral studies, and policy evaluation to develop equitable transportation solutions. Recent publications reveal a pronounced focus on rural transportation challenges, including travel burdens among migrant communities, wildfire evacuation safety, and electric vehicle adoption barriers. Her work increasingly addresses contemporary policy shifts through the lens of transportation justice, examining how anti-DEI movements impact mobility access while developing practical tools for accessibility measurement. As founder of Sustainable Systems Research, she has partnered with community organizations on transportation health impact assessments. Her teaching at the University of Washington included Health and Sustainable Transportation and Transportation Economics courses. Current affiliations include the Transportation Research Center where she contributes to Vermont Transportation Energy Profile initiatives and pedestrian safety evaluations in rural contexts.

• Transportation equity and justice
• rural travel behavior
• accessibility measurement
• +4 more