Ivan Viola is an Associate Professor at the Institute of Computer Graphics and Algorithms, part of the Faculty of Informatics at TU Wien, Austria. He holds a leave of absence until December 2024 while also being affiliated with King Abdullah University of Science and Technology (KAUST) as an Associate Professor funded by the Vienna Research Groups program. His research focuses on visualization techniques in medicine, biological sciences, and earth sciences, with a specialty in illustrative visualization and DNA-nanotechnology applications. Viola has contributed over 100 scientific works and serves as a reviewer and panelist for major conferences in computer graphics and visualization. Education: M.Sc. (2002) and Ph.D. (2005) in Computer Graphics from TU Wien. Postdoctoral research at the University of Bergen (2006-2011), where he became Full Professor before returning to TU Wien. Research Interests: Whole-cell visualization Molecular modeling Interactive 3D environments Biomedical visualization Data-driven colormap techniques Awards: IEEE VIS 2017 Best Paper Honorable Mention, 'Best Overall Concept' for CellView, and multiple visualization awards. Active in EuroVis and IEEE VIS organizing roles. Grants & Supervision: Leads the Visualization Group at TU Wien, supervising student projects and master’s theses. Involved in grants like the Vienna Research Groups program. Labs/Teams: Visualization Group at TU Wien, collaborating on projects like CellView and Molecumentary.
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.
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.
Andrew M Milsten serves as Professor in the Department of Emergency Medicine at UMass Chan Medical School, specifically within the T.H. Chan School of Medicine and Division of EMS/Disaster. His work bridges clinical emergency medicine with large-scale disaster response systems. His educational foundation includes a BA in Biology from Bucknell University, an MS in Emergency Health Services from the University of Maryland Baltimore, and an MD from George Washington University. Milsten's research centers on disaster behavioral science and mass gathering medicine , with signature studies analyzing injury patterns at NHL/MLB games, marathons, and concerts. His recent work explores augmented reality applications for field procedures and ethical frameworks for hospital active shooter incidents. He has significantly contributed to disaster medicine standardization through the 2023 Model Core Content development. Publication trends reveal a strategic evolution from foundational mass gathering epidemiology (2000-2010) toward behavioral disaster science and technological integration (2020-2024), primarily in Prehospital and Disaster Medicine and similar journals. Fellow of the American College of Emergency Physicians (FACEP) Through his Division of EMS/Disaster affiliation, Milsten collaborates with national bodies like the National Association of EMS Physicians to shape position statements and resource documents. His research consistently informs operational guidelines for event medical planning and disaster response protocols. He maintains active leadership in disaster medicine education and operational research within UMass Chan's emergency medicine infrastructure.
Dr. Anil Ufuk Batmaz is an Assistant Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on Virtual Reality (VR), Augmented Reality (AR), and Human-Computer Interaction, with emphasis on interaction techniques, immersive analytics, and motor skill training systems. He holds a BSc in Electrical and Electronics Engineering (2007-2011), an MSc in the same field (2011-2013), and a PhD in Biomedical Engineering (2015-2018). His work bridges engineering and cognitive science, investigating how visual and haptic feedback impact user performance in immersive environments. Research interests include: 3D interaction techniques for mid-air tasks Effects of display technologies on motor coordination Hybrid UI design for mixed reality systems Training systems for precision tasks using VR Recent publications emphasize evaluation of AR/VR interfaces in healthcare, sports training, and collaborative environments. His work has appeared in venues like IEEE TVCG, ACM CHI, and ISMAR, addressing challenges in spatial navigation, error feedback, and system reliability.
Fernando Camelli is an Associate Professor in the Physics & Astronomy Department at George Mason University, holding dual roles as Instructional Faculty and Faculty. His research focuses on computational fluid dynamics (CFD), urban environmental modeling, and high-performance computing. He specializes in simulating complex fluid flows in urban environments, subway systems, and industrial applications, with particular emphasis on turbulence modeling, fluid-structure interaction, and GPU-accelerated algorithms. Key research areas include: CFD for urban airflow and contamination dispersion Meshless and immersed boundary methods Integration of geographic information systems (GIS) with CFD Large-scale simulations using parallel computing His work addresses practical challenges such as subway ventilation optimization, emergency contaminant dispersion prediction, and urban infrastructure design. Recent studies emphasize scalability improvements for fluid-structure interaction simulations and GPU-based code modernization.
Christian Jacob is a Professor in the Department of Computer Science within the Faculty of Science at the University of Calgary . He holds a B.S. in Computer Science and a Doctor of Engineering Science from Erlangen University . His research focuses on nature-inspired algorithms, biocomputing, and agent-based simulations applied to biological systems and education. Key initiatives include the LINDSAY Virtual Human Project , which uses immersive virtual reality to explore human anatomy and physiology. He contributes to the university's strategic priorities in Digital Worlds and Health and Life initiatives. His work integrates evolutionary algorithms, cellular automata, and swarm intelligence into creative and medical applications. Notable achievements include the ASTech Award (2015) from Alberta Science and Technology. His projects emphasize interactive education through tools like LeukemiaSIM , Eukaryo , and the Giant Walkthrough Gut . Jacob also explores visualization techniques, such as evoVision3D and LifeBrush , to enhance scientific understanding. His research bridges computational methods with real-world applications in healthcare, architecture, and game design. Collaborative efforts include developing agent-based models for immune systems, nervous responses, and crowd behavior. Jacob's work spans interdisciplinary fields, blending computer science with biology, engineering, and the arts.
Christoph Heinzl is a Professor of Cognitive Sensor Systems at the University of Passau since September 2022. He leads the Knowledge-based Image Processing research group at the Fraunhofer Development Center X-ray Technology (EZRT) . His academic background includes a PhD in Informatics and a Habilitation in 2022 , both from TU Wien . Research Focus: Scientific visualization, visual analytics, immersive analytics, virtual/augmented reality, machine learning, and X-ray computed tomography (XCT). Key Trends: Development of novel visualization techniques for complex volumetric data (e.g., dynamic volume lines, visual coherence frameworks), parameter space analysis, and cross-virtuality collaboration tools. Applications: Aerospace component inspection, defect analysis in composites (CFRP, GFRP), porosity quantification, and 4DCT time-series exploration.
Isabelle Augenstein is a Professor at the University of Copenhagen, Department of Computer Science (DIKU), where she heads the Copenhagen Natural Language Understanding (CopeNLU) research group and the Natural Language Processing section. She is also a co-lead of the Danish Pioneer Centre for Artificial Intelligence, Denmark's largest research center initiated by the Danish Ministry of Higher Education and Science. In October 2022, she became Denmark's youngest ever female full professor. Dr. Augenstein earned her undergraduate degree in Computational Linguistics and Psychology from Heidelberg University, followed by a Master's in Computational Linguistics. She completed her PhD in Computer Science at the University of Sheffield under the supervision of Dr. Diana Maynard and Prof. Fabio Ciravegna. In 2021, she earned a Habilitation at the University of Copenhagen in Explainable Fact-checking. Professor Augenstein's primary research focuses on fair and accountable Natural Language Processing, with particular emphasis on explainability, factuality, and bias detection. Her work spans multiple subfields including automated fact-checking, stance detection, gender bias analysis, and cultural bias in language models. She has pioneered research in explainable fact-checking, developing methods that not only predict claim veracity but also provide meaningful explanations of the decision-making process. Her research group has produced numerous influential papers on measuring model fragility, quantifying gender biases, and developing robust fact-checking systems that account for distribution shifts. Her significant contributions have been recognized with several prestigious awards: ERC Starting Grant on 'Explainable and Robust Automatic Fact Checking' DFF Sapere Aude Research Leader fellowship on 'Learning to Explain Attitudes on Social Media' Karen Spärck Jones Award from the British Computing Society and Bloomberg Hartmann Diploma Prize from the Hartmann Foundation Member of the Royal Danish Academy of Sciences and Letters since 2024 Professor Augenstein has secured significant research funding including her ERC Starting Grant supporting five years of blue-sky research. She actively mentors PhD students and postdoctoral researchers through her 'ExplainYourself' project. She served as President of SIGDAT (which organizes the EMNLP conference series), having previously held leadership roles as Vice President and Vice President-Elect. She is a co-founder of Widening NLP (WiNLP), an initiative to increase diversity in the NLP community, and maintains the BIG Directory of underrepresented groups in NLP. She leads the Copenhagen Natural Language Understanding (CopeNLU) research group, which relocated to the historic Østervold Observatory in Copenhagen's Botanical Gardens in 2023. The group focuses on developing methods for explainable and robust natural language understanding, with applications in fact-checking, bias detection, and social media analysis. Professor Augenstein also co-leads the Speech and Language collaboratory at the Pioneer Centre for Artificial Intelligence, where her team investigates how language models can better serve diverse populations while maintaining accountability and transparency.
Dr. Jie Li is a dual-career academic and creative professional with a PhD in Industrial Design Engineering from Delft University of Technology. As an HCI/UX researcher in industry and Adjunct Professor at multiple institutions, she bridges academia and practice through work on Extended Reality (XR) , Human-AI interactions , and user experience evaluation . Her ACM Interactions column 'Bits to Bites' explores interdisciplinary research methodologies. Education: MSc in Industrial Design Engineering, Delft University of Technology PhD in Industrial Design Engineering, Delft University of Technology (2019) Her research spans social VR platforms , AI-augmented cognition , and privacy-preserving emotion detection , with recent publications analyzing LLM-assisted game design , harassment detection in VR , and XR's impact on remote collaboration . She has received Best Demo Awards (2020, 2022) and the ACM Best Paper Award (2018). Notable trends in her work include emerging immersive technologies (XR, 6DoF displays), human-AI collaboration frameworks , and cross-domain applications from medical VR clinics to cultural heritage experiences . Her advocacy for synthetic UX research and asynchronous co-creation tools reflects industry-academia hybrid innovation. Scientific Awards: Best Demo Award (2020, ACM TVX/IMX 2020) Best Demo Award (2022, ACM Multimedia) ACM Best Paper Award (2018, ACM TVX) While maintaining active roles in CHI conference committees and guest lecturing , Jie also operates a Delft-based creative cake design business , demonstrating her commitment to interdisciplinary exploration and 'slash career' balance between technical research and artistic practice.
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
Roberto Rojas-Cessa is a Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT), affiliated with the School of Applied Engineering and Technology. His research focuses on networking, blockchain applications in smart cities, energy systems, wireless communications, and high-performance switching. He has led multiple National Science Foundation (NSF)-funded projects, including initiatives on controlled delivery power grids and next-generation network quality of service. Notably, his work explores blockchain for energy metering, sustainable environmental measures, and smart grid optimization. He is also a Senior Member of the National Academy of Inventors (2024). His research interests span network protocols, distributed systems, and IoT applications. Recent projects include AMI-Chain (a blockchain-based power metering system) and studies on indirect free-space optical communications for vehicular networks. He has contributed to advancements in medium access control for crowded networks and energy packet switches for digital microgrids. Rojas-Cessa’s work integrates machine learning for network management and flood impact analysis. He has developed tools for time-lapse analysis of urban data and agent-based models to evaluate electric vehicle adoption. His publications emphasize scalability, security, and efficiency in both traditional and emerging technologies. Grants: Collaborative Research on Power Grids (NSF, 2016–2018), NeTS-NR: Quality of Service Networks (NSF, 2004–2008) Awards: Senior Member of the National Academy of Inventors (2024) His lab activities include experimental evaluations of digital microgrids and blockchain implementations for carbon footprint tracking. He actively collaborates on projects addressing emergency communications and resilient energy distribution systems.
Martin D. F. Wong is the Edward C. Jordan Professor of Electrical and Computer Engineering and Executive Associate Dean of the College of Engineering at the University of Illinois. A pioneer in Electronic Design Automation (EDA) and VLSI circuit design, his work has significantly advanced chip design methodologies through algorithmic innovations. He holds over 450 publications and has been recognized with prestigious awards, including the ASP-DAC Most Frequent Author Award and the inaugural EDA Research Award from Synopsys. Wong’s research focuses on EDA, computational lithography, and 3D integrated circuits. He has mentored 48 PhD students, many of whom have excelled in academia and industry. His contributions include foundational frameworks like OpenILT (Inverse Lithography Technique) and Xplace (global placement). He is an IEEE Fellow and has served as a Distinguished Lecturer for the IEEE Circuits and Systems Society. Key Achievements: Recipient of six best-paper awards in chip design and routing optimization Developed GPU-accelerated tools for static timing analysis and global routing Advances in machine learning applications for EDA, including congestion prediction and hotspot detection Wong’s legacy combines technical innovation with mentorship, shaping the future of semiconductor design and manufacturing.
Dr. Ioannis Kaparias is an Associate Professor in Transport Engineering at the University of Southampton, affiliated with the Transportation Research Group (TRG). He holds a Master of Engineering from Imperial College London and a PhD from the same institution. His academic career includes roles at City, University of London, and postdoctoral research at Imperial College. He is a Fellow of Advance HE, a member of the Chartered Institute of Highways and Transportation (CIHT), and serves as Deputy Editor-in-Chief of the IET Intelligent Transport Systems journal. Education: MEng in Civil Engineering, Imperial College London (2004) PhD in Transport Engineering, Imperial College London (2008) Postdoctoral Researcher, Imperial College London (2008–2012) Research Interests: Efficient, safe, and sustainable land transport systems Highway and traffic management, including real-time routing and network reliability Active travel modes (cycling/pedestrian infrastructure) Public transport operations and optimization New transport technologies (CAVs, MaaS, EVs) Land use-transport interaction models Teaching: Highway & Traffic Engineering modules at Southampton Doctoral Programme Director (Training) in the School of Engineering Past roles include teaching at Imperial College London, City University London, and the University of East London External Roles: Member of US Transportation Research Board committees (Pedestrians/ACH10 and Human Factors/ACH40) Independent expert for the European Commission Speaker at international conferences (e.g., 'To share or not to share space? A very British tale', 2023)
Ziqi Song is an Associate Professor in the Department of Civil, Structural and Environmental Engineering at the School of Engineering and Applied Sciences, University at Buffalo. Their research focuses on Transportation Engineering, with expertise in transportation network modeling, electrification, intelligent transportation systems, and traffic operations. Recent work includes zero-emission mobility strategies , electric bus charging infrastructure , autonomous vehicle lane deployment , and pedestrian group dynamics . Key themes involve optimizing transportation systems for electrification, integrating renewable energy into transit networks, and addressing equity in mobility through accessibility studies. Publications show strong emphasis on electric vehicle integration , urban transit optimization , and pedestrian behavior modeling . The work spans multi-disciplinary approaches combining transportation network analysis , renewable energy , and machine learning techniques.
