Tina Comes is a Full Professor in Decision-Making & Digitalisation at the University of Maastricht, Netherlands. She holds a part-time position (0.2 FTE) and has previously held academic roles at TU Delft (Associate Professor in Decision-Making for Resilience, 2017), University of Agder (Full Professor in ICT, 2015-2017), and Visiting Professor at Lamsade, Université Dauphine, Paris (2014). Her research focuses on Crisis Informatics , Decision Theory , Disaster Management , Humanitarian Logistics , and Resilience . Her work spans building simulation , ventilation systems , and energy-efficient design , with grants totaling €9.6 million since 2012. Key projects include Resilient Systems (NL Ministry of Defense, 2020-2026), H2020 HERoS (2020-2023), and Climate Resilient Urban Infrastructure (Amsterdam, 2020-2022). She has supervised 6 PhD students at TU Delft (2017-2022), 3 Postdocs/PhDs at University of Agder (2013-2020), and 1 PhD at Université Toulouse (2014-2018). Her scientific awards include: 2020 José Maria Sarriegi Award by the Spanish Red Cross 2019 Emerald Literati Award 2016 Delft Technology Fellowship (acceptance rate 2012 Best Paper Award at ISCRAM Conference
Professor Klaus McDonald-Maier is a full Professor in the School of Computer Science and Electronic Engineering (CSEE) at the University of Essex , where he leads the Embedded and Intelligent Systems (EIS) Research Laboratory and heads the Intelligent Embedded Systems and Environments Research Group . He is also Director of Impact , Visiting Professor at the University of Kent, and Visiting Research Affiliate at NASA Jet Propulsion Laboratory, California Institute of Technology. Education PhD in High-Performance Parallel Neural Network Architectures, Friedrich-Schiller-University Jena (Germany, 1999) Electronic Engineering studies, University of Ulm (Germany) Electronic Engineering studies, Cardiff University (Wales) Electronic Engineering studies, École Supérieur de Chimie Physique Électronique de Lyon (CPE-Lyon) (France) Research Interests Professor McDonald-Maier’s research integrates embedded systems , System-on-Chip (SoC) architectures , and AI-driven robotics . He pioneers visual place recognition techniques that remain robust under severe appearance and viewpoint changes, develops cybersecurity frameworks based on ICMetrics for autonomous vehicles and IoT, and designs approximate real-time computing solutions for energy-constrained multicore and FPGA platforms. His work on radiation-tolerant systems supports space and nuclear applications, while his bio-inspired algorithms enable lightweight, neuromorphic perception on resource-limited robots. Publication Trends Between 2022 and 2025 his output converges on FPGA-accelerated AI , secure edge intelligence , visual navigation for autonomous systems , and healthcare analytics . He repeatedly couples rigorous algorithmic innovation with practical hardware deployment, yielding energy-efficient, real-time systems validated in domains ranging from autonomous driving to post-stroke rehabilitation. Scientific Awards & Recognition Best Paper Award – IEEE Transactions on Sustainable Computing (2024) Best Paper Award – IEEE/ACM DATE (2024) Best Paper Award – IEEE Systems Journal (2022) Best Paper Award – IEEE Sensors Journal (2021) Best Paper Award – IEEE Access (2020) Research Grants & Industrial Collaboration He has secured major funding from EPSRC , EU Horizon 2020 , Innovate UK , and industry partners. Current projects span trustworthy autonomy, radiation-hardened edge AI, and AI-enhanced rehabilitation technologies. He is Chief Scientist of UltraSoC Technologies Ltd and CEO of Metrarc Ltd , commercialising University research in semiconductor debug and cybersecurity respectively. Laboratory & Team Leadership As Director of the Embedded and Intelligent Systems Laboratory (EIS Lab) , he oversees a multidisciplinary team of researchers and PhD students, providing state-of-the-art FPGA, robotics, and embedded-systems facilities. The lab collaborates closely with NASA JPL, UK Atomic Energy Authority, and leading semiconductor firms to translate fundamental research into high-impact industrial solutions.
Kailiang Wu is an Associate Professor at the Department of Mathematics, Southern University of Science and Technology (SUSTech), and holds concurrent roles at the Shenzhen International Center for Mathematics and National Center for Applied Mathematics Shenzhen. His research bridges Machine Learning and Computational Fluid Dynamics , focusing on High-Order Numerical Methods for Hyperbolic Conservation Laws and Relativistic Astrophysics . Education: Ph.D. in Mathematics (Peking University, 2016), B.Sc. in Mathematics and Statistics (Huazhong University of Science and Technology, 2011) His work develops Structure-Preserving Schemes for multidimensional PDEs, including Oscillation-Eliminating Discontinuous Galerkin (OEDG) and Geometric Quasilinearization (GQL) frameworks. These methods ensure positivity , divergence-free , and bound-preservation in simulations of relativistic flows and MHD systems. Recent publications emphasize Deep Learning applications in operator learning (e.g., DUE framework) and Data-Driven Modeling of unknown PDEs. His group has produced 20+ peer-reviewed articles in top journals (Math. Comp., SIAM J. Numer. Anal., JCP) since 2014. Honors: SUSTech President's Research Award (2025) World's Top 2% Scientist (2024) NSFC Major Program (2023, 0.7M CNY) Shenzhen Distinguished Young Scholar (2023, 4M CNY) National Excellent Young Scholar Program (2020, 2M CNY) Zhong Jiaqing Mathematics Award (2019) He advises 10+ graduate students and postdocs, with alumni securing academic positions at Sun Yat-sen University and HKUST. His lab collaborates on relativistic hydrodynamics , traffic models , and uncertainty quantification , supported by competitive funding.
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.
Mohsen Heidari is an Assistant Professor in the Department of Computer Science at Indiana University, Bloomington. He is affiliated with the IU Quantum Science and Engineering Center (QSEc) and the NSF Center for Science of Information (CSoI). He previously held positions as a Visiting Assistant Professor at Purdue University and as a Postdoctoral Research Associate at CSoI. Ph.D. in Electrical Engineering (2019) and M.Sc. in Applied Mathematics (2017) from the University of Michigan His research focuses span quantum computing, theoretical machine learning, and information theory. Key themes include: Quantum algorithm design and sample complexity Fourier-based learning frameworks Quantum-classical duality in learning problems Information-theoretic approaches to biological systems Article trends show a strong emphasis on quantum-classical learning intersections (6/15 papers), Fourier analysis applications (5/15), and information-theoretic foundations (12/15). Notable venues include NeurIPS, IEEE Transactions, and ISIT. He directs research involving: Quantum Neural Network development Quantum measurement simulation Quantum data compression techniques Quantum algorithm implementation constraints
Jayson Paulose is an Associate Professor of Physics at the University of Oregon, affiliated with the College of Arts and Sciences and the Institute for Fundamental Science. His research spans theoretical soft matter physics, biophysics, evolutionary dynamics, and metamaterials design, focusing on the intersection of topology, geometry, and statistical mechanics in artificial and biological systems. Academic Roles: Faculty member in the Department of Physics, Director of the MSTC Program. Research Themes: Designer matter (topological and active metamaterials), biological systems (elasticity of thin shells, evolutionary genetics), and mechanical principles in soft structures. Collaborations: Partners with experimentalists and theorists in physics, materials science, and biology at UO and institutions like Leiden University. Lab: Paulose Group, which includes graduate and undergraduate researchers, explores problems such as topological protection in metamaterials and genetic propagation in populations. Research Interests include: Topological soft matter: Using symmetry and geometry to design materials with robust mechanical properties. Evolutionary dynamics: Modeling the impact of long-range dispersal on genetic diversity and population structure. Elastic mechanics: Analyzing thin shells and membranes relevant to biological systems. Active matter: Studying non-equilibrium systems like rotating dimer particles and synthetic metamaterials. Publications reflect his interdisciplinary focus, with recent work (2023–2024) on mechanical metamaterials, elastic shells, and stochastic population genetics, and earlier contributions to active spinner materials and topological protection in biological systems. Education & Training of students in his lab emphasizes theoretical rigor and computational techniques, with alumni transitioning to postdoctoral positions and industry roles in mechanical engineering, data science, and software development. Contact: jpaulose@uoregon.edu | Office: 375 Willamette Hall, University of Oregon.
Jim Crutchfield is a Distinguished Professor of Physics at the University of California, Davis, where he also serves as Director of the Complexity Sciences Center. He holds additional affiliations as President and Scientific Director of the Art & Science Laboratory in Santa Fe, External Faculty at the Santa Fe Institute, General Member of the Telluride Science Research Center, and Visiting Scholar at the Redwood Center for Theoretical Neuroscience. His work bridges physics, computation, and complex systems. Education: B.A. summa cum laude in Physics and Mathematics, University of California, Santa Cruz (1979) Ph.D. in Physics, University of California, Santa Cruz (1983) Crutchfield's research centers on computational mechanics , a framework he pioneered to quantify how natural systems store, process, and transmit information. His interests span nonlinear dynamics, evolutionary dynamics, information engines, quantum computation, and pattern discovery. He explores how structure emerges in complex systems, from cellular automata to biological evolution and neural networks. His recent work focuses on thermodynamic computing, causal inference, and the physics of intelligence. His publications reveal a consistent focus on the interplay between information, energy, and computation in physical systems. Themes include the thermodynamics of information engines, causal architecture in time series, emergent organization, and intrinsic computation in quantum and classical domains. These works span disciplines such as physics, computer science, biology, and cognitive science. Scientific Recognition: Postdoctoral Fellow, Miller Institute for Basic Research in Science IBM Postdoctoral Fellow, Condensed Matter Physics Distinguished Visiting Research Professor, Beckman Institute Bernard Osher Fellow, San Francisco Exploratorium NSF Graduate Fellow UCB Chancellor’s Fellow Crutchfield has advised over two dozen PhD students in physics, computer science, and mathematics, contributing significantly to the next generation of complexity scientists. He has led major interdisciplinary initiatives, including NSF-funded museum exhibits and workshops on network dynamics, collective cognition, and evolutionary dynamics. He has also been active in public discourse through talks, films, and publications on the philosophy of complexity. He leads research groups exploring the dynamics of learning, pattern discovery, and distributed intelligence, often in collaboration with institutions like the Santa Fe Institute and Caltech. His work continues to shape the theoretical foundations of complex systems science.
Dr. Yen-Ting (Allen) Yeh is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan, where he leads research in Human-Computer Interaction focusing on mobile interaction techniques, collaborative tools, and creative technologies. PhD, Cheriton School of Computer Science, University of Waterloo MS, Graduate Institute of Networking and Multimedia, National Taiwan University His research explores physical and cognitive human capabilities through: Innovative phone interaction methods (folding, dexterous gestures, side-touch expansion) Collaborative writing environments with privacy controls Creativity augmentation systems for 3D modeling Augmented reality and interactive fabrication tools Recent publications demonstrate strong focus on: Acoustic input techniques using finger snapping Motion-based creative reflection tools Dynamic gesture recognition systems Collaborative editing comfort optimization Scientific recognition includes: ACM Creativity and Cognition 2021 Honorable Mention The research group at the University of Saskatchewan's HCI Lab actively seeks students interested in phone interactions, human factors, AR/VR, collaborative tools, and creative arts applications.
Iain Spears holds dual academic appointments as Senior Lecturer in Sport & Exercise Science at Newcastle University's Faculty of Medical Sciences (Department of Biomedical Sciences) since May 2020, and as Lecturer in Biomedical/Sports Engineering at Nottingham Trent University's Department of Engineering since August 2019. His interdisciplinary position bridges sports science, biomechanics, and engineering applications in athletic performance. Dr. Spears' research focuses on several interconnected areas: Sports biomechanics and movement analysis Training load monitoring and performance assessment methodologies Injury prevention and rehabilitation strategies Technological applications in sports performance Physiological responses to exercise His publication record demonstrates methodological innovation, with recent work employing point-cloud processing for motion analysis, low-cost depth-sensing camera systems, and exergaming solutions for high-intensity training. Key research themes include differential ratings of perceived exertion, environmental effects on athletic performance, and cooling methodologies for endurance exercise. Dr. Spears' collaborative research network includes frequent co-authors Matthew Weston, Thomas Macpherson, and Sean McLaren, with publications appearing in high-impact journals such as Journal of Biomechanics, Sports Medicine, and Medicine and Science in Sports and Exercise. His work has practical applications across team sports, military training contexts, and rehabilitation programming.
Tasos Dagiuklas is a Professor in the Department of Computer Science and Technology within the School of Engineering and Technology at the University of Bedfordshire. With over 168 publications spanning from 1995 to 2025, he has established himself as a leading researcher in telecommunications and network systems. His extensive publication record demonstrates continuous scholarly contribution across multiple decades in the field. Professor Dagiuklas' research focuses on wireless communications, edge computing, 5G/6G networks, quality of experience (QoE), and federated learning . His work bridges theoretical networking concepts with practical applications, particularly in multimedia delivery and security. He has developed significant expertise in video streaming optimization, network security mechanisms, and resource management in emerging network architectures. His research consistently addresses the evolving challenges of modern communication systems, with recent work increasingly focusing on AI integration in networking. Analysis of his recent publications (2023-2025) reveals a strong trend toward edge computing, federated learning, and security applications in next-generation networks. His work demonstrates a strategic shift from traditional networking concerns to more complex systems involving AI integration, energy efficiency, and heterogeneous environments. The publications show consistent collaboration with researchers across multiple institutions, with particularly strong partnerships with Muddesar Iqbal, Ilias Politis, and Stavros Kotsopoulos. Professor Dagiuklas has made substantial contributions to the academic community through his extensive publication record in high-impact venues including IEEE journals and conferences. His work has evolved from foundational networking research to cutting-edge investigations of AI-enhanced communication systems, reflecting the broader trajectory of the field itself. His research demonstrates both technical depth in specific networking challenges and breadth across multiple application domains.
Mikael Wiberg is full Professor of Informatics at Umeå University, Sweden, where he leads research groups in Design Informatics and Digital Interaction & Design. He is co Editor-in-Chief of ACM Interactions and has held chaired and guest professorships at Uppsala, Södertörn and Chalmers universities. His work sits at the intersection of human-computer interaction, materiality, architecture and emerging technologies. Education: PhD in Informatics, Umeå University, 2001 Docent (Associate Professor) in Informatics, Umeå University, 2004 Research interests revolve around interactivity, mobility, materiality and architecture . Wiberg coined the notion of “materiality of interaction” to study how digital resources merge with physical materials, spaces and artefacts. Recent strands include more-than-human design, human-building interaction, autonomous systems UX, and social justice in HCI, all interrogating how interactive technologies shape—and are shaped by—human and non-human actors. Across more than two decades he has published in top venues such as ACM TOCHI, Design Issues, Int. Journal of Design, Human-Computer Interaction journal and the magazine ACM Interactions . His 2018 MIT Press monograph The Materiality of Interaction consolidates his theoretical stance and has become a touchstone for architectural and material HCI discourse. Editorial & scientific awards: Co Editor-in-Chief, ACM Interactions (2019-) Member, Royal Skyttean Society (Kungliga Skytteanska Samfundet) Board member, Professors’ Association, Umeå University He currently leads interdisciplinary projects on digital heritage archives, autonomous vehicle experiences for children with intellectual disabilities, and sustainable interaction infrastructures. Although the provided text does not enumerate specific grants or doctoral students, his continuous project leadership and editorial roles evidence sustained funding and supervisory activity. Wiberg directs the Design Informatics research environment and is a core member of Umeå’s Internet of Things group, fostering collaboration between informatics, architecture, design and social sciences. His overarching agenda asks how interactive technologies can support just, sustainable and aesthetically rich futures at architectural and urban scale.
Dr. Andrzej Ożadowicz is a University Professor at the Department of Power Electronics and Automation of Energy Conversion Systems within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His office is located in room 510, building C-1, with contact details including phone +48 12 617 50 11 and email ozadow@agh.edu.pl. He holds PhD, DSc, and Engineering degrees, reflecting his dual expertise in academic research and practical engineering applications. His research spans Power Electronics, Building Automation, Smart Grids, and IoT-driven energy systems. Key interests include energy efficiency optimization through digital twins and BIM, distributed energy resource integration , and AI-enhanced demand management . Notably, he pioneers applications of deep reinforcement learning in home energy systems and develops frameworks for Smart Readiness Indicator implementation. His work bridges theoretical innovation with practical case studies in building thermal modeling and dynamic façade systems. Recent publications (2021-2025) reveal three dominant trends: (1) Convergence of digital twin technology with building automation for real-time energy management; (2) Critical analysis of IoT security and interoperability in smart infrastructure; (3) Pedagogical innovations in engineering education through blended learning methodologies post-COVID-19. His scholarly output demonstrates consistent focus on energy transition challenges and smart grid evolution. Professor Ożadowicz actively contributes to the Discipline Council for Automation, Electronics, Electrical Engineering and Space Technologies at AGH. He is instrumental in the AutBudNet initiative —a network of certified laboratories for energy efficiency assessment that implements "learning by doing" principles in building automation education. His work with this consortium emphasizes practical validation of smart grid technologies and demand response systems.
Dr. Hameed Chughtai is an Associate Professor at Lancaster University Management School, where he conducts critical research on decolonial approaches to information systems and the engagement of marginalized populations with technology. His work spans multiple research centers including the Academy for Gender and Social Justice, the Pentland Centre for Sustainability in Business, and the Centre for Technological Futures. Dr. Chughtai's research focuses on critical and decolonial approaches to technology, with particular interest in how marginalized populations such as Indigenous Peoples interact with information technologies. His methodological approach emphasizes fieldwork and ethnographic methods to examine ethical aspects of technology, body, marginalization, decolonization, and Indigenous scholarship. His work challenges conventional information systems research paradigms by centering local contexts and marginalized perspectives. His recent publications reveal a strong trend toward decolonizing information systems research, with increasing focus on ethical considerations in technology, particularly regarding generative AI applications and the experiences of marginalized communities. His work bridges theoretical frameworks from postcolonial studies, critical theory, and information systems to create more inclusive and contextually relevant research approaches. Associate Editor at the Information Systems Journal Senior Editor at The Electronic Journal of Information Systems in Developing Countries Chair of IFIP Working Group 9.5 Guest Senior Editor for special issues on Decoloniality in IS Research (2022-2024) Guest Senior Editor for special issues on Addressing Refugees and Migration Issues (2024-2026) As a dedicated supervisor, Dr. Chughtai mentors postgraduate research students in critical and interpretive research related to digital technologies, focusing on ethical technology, marginalization, and decolonial approaches to information systems.
Prof. Dr. Nina Zschocke is Professor of Art History with a focus on 'Digital Aesthetics' at the Karlsruhe University of Arts and Design (HfG Karlsruhe) since April 2024. Previously, she served as senior research associate and lecturer at the Department of Architecture at ETH Zurich until 2023, and as a research associate at the Institute of Art History at the University of Zurich from 2005. She maintains strong connections with the ZKM | Center for Art and Media in Karlsruhe through collaborative projects and lecture series. Her educational background includes studies in art history, ethnology, and classical archaeology at the University of Cologne, where she earned her doctorate in 2004 with a dissertation on 'irritation' in art reception. She furthered her academic work as a DFG visiting scholar at University College London and Columbia University in New York. Zschocke's research centers on the intersection of art history, digital aesthetics, and materiality, with particular emphasis on how computational processes reshape artistic production and reception. Her work explores the material dimensions of digital media, algorithmic authority, and unconventional computing paradigms. She investigates how traditional art historical frameworks can be adapted to address contemporary digital practices and the physical manifestations of computational processes in artistic contexts. Her publications and symposia reveal consistent engagement with digital materiality, examining how digital processes manifest in physical form and how traditional art historical methods apply to contemporary computational practices. Recent work focuses on 'unconventional computing' - exploring alternative physical substrates for computation beyond standard silicon-based systems, and questioning the dominant paradigms of digital technology. Zschocke has organized numerous significant academic events including the 'Conversations on Art and Media' lecture series (2025), 'Dirty Computers' seminar week (2024), 'Digital Matters Symposium' (2024), and the long-running 'Don18 - Conversations on Art and Architecture' (2006-2022). These events demonstrate her commitment to creating interdisciplinary dialogue platforms that bridge art, architecture, media theory, and computational practices. Her academic leadership extends to doctoral program development, having co-designed the SNSF doctoral program 'ProDoc Art&Science' (2008-2014) and the 'Doctoral Program in the History and Theory of Architecture' at ETH Zurich (2012-2015). She has taught at multiple institutions including the University of Fribourg, Bremen University of the Arts, and Bern University of the Arts, establishing herself as a significant figure in European art and media theory education.
Hao Yang is an Assistant Professor in the Department of Civil and Systems Engineering at Johns Hopkins University, with dual affiliations at the Johns Hopkins Data Science and AI Institute and the Johns Hopkins Institute for Assured Autonomy. His research develops Trustworthy Machine Learning methods to enhance urban mobility systems, focusing on traffic safety, equity, and sustainability through ethical AI and human-machine cooperative systems. Yang earned dual bachelor's degrees in Electrical and Computer Engineering from Beijing University of Posts and Telecommunications and the University of London, followed by a Ph.D. in Civil Engineering (Transportation) from the University of Washington. His educational background bridges telecommunications, electrical engineering, and transportation systems. His research integrates spatio-temporal modeling, assured autonomous systems, and multimodal representation learning to address transportation equity and safety. Key projects include edge-AI-powered traffic surveillance, real-time crash identification, and cooperative signal assistance for vulnerable road users. His work emphasizes ethical AI deployment in cyber-physical infrastructure to create sustainable urban mobility solutions. Recent publications reveal a strategic shift toward large language models and multimodal AI for transportation challenges, with strong emphasis on explainability, reliability, and equity in traffic crash prediction, flow forecasting, and autonomous driving systems. This evolution demonstrates his commitment to adapting cutting-edge AI for real-world transportation problems. Yang's scientific contributions have earned significant recognition: Michael Kyte Outstanding Student of the Year Award (2022) High-Value Research Award from AASHTO (2022) Best Paper Award from TRB Information Systems Committee (2023) Best and Outstanding Dissertation Awards (2024) IEEE DTPI Outstanding Paper Award (2022) TRANSFOR22 Data Competition 2nd place (2022) ASCE Bridges Photo Contest First Place (2021) He actively mentors graduate researchers and seeks 2-3 PhD students for Fall 2025 to advance trustworthy AI in transportation. His research is supported by NSF, USDOT, and AASHTO grants including the Real-Time Truck Parking Information System project that received the High-Value Research Award. Current work focuses on edge-AI for traffic safety and multimodal data integration. Yang leads research within Johns Hopkins' Data Science and AI Institute and Institute for Assured Autonomy, collaborating with Transportation Research Board committees. His lab develops real-time perception systems using edge computing and representation learning, with active projects on non-motorized user safety and equitable traffic management for people with disabilities.
