جست‌وجوی استاد و پژوهشگر

Brian L. Smithمشاهده پروفایل

استاد

• Transportation Systems Engineering
• Cybersecurity
• Connected and Automated Vehicles
• +۵ مورد دیگر

Brian L. Smith, PE is a Professor and Senior Associate Dean for Research and Faculty Affairs at the University of Virginia's School of Engineering and Applied Science, specializing in Civil Engineering. He leads research in transportation systems with a focus on sustainability, cybersecurity, connected/automated vehicles, and smart infrastructure. Dr. Smith has authored over 150 publications and holds multiple patents. His work includes pioneering virtual reality tools for pedestrian safety, cybersecurity frameworks for autonomous systems, and innovations in traffic management. Education: B.S., Civil Engineering, Virginia Tech (1989) M.S., Civil Engineering, University of Virginia (1991) Ph.D., Civil Engineering, University of Virginia (1995) Research Interests: Dr. Smith's work spans advanced transportation technologies, including cooperative systems, probe-based traffic monitoring, and AI-driven infrastructure solutions. He emphasizes interdisciplinary approaches to address urban mobility challenges, such as integrating cybersecurity into vehicle networks and optimizing smart city systems. Awards: Fellow, American Society of Civil Engineers (ASCE) ASCE Huber Research Award (2006) NSF CAREER Award Eno Transportation Leadership Fellow His advisory roles include guiding state/national transportation policies and serving as an associate editor for the ASCE Journal of Transportation Engineering. He founded the University of Virginia's Center for Transportation Studies and leads the Link Lab's transportation research initiatives. Teaching: Courses include CE 6440 (Advanced Transportation Systems) and CE 5000 (Construction Project Management), emphasizing hands-on learning and industry collaboration.

Christian Gawronمشاهده پروفایل

استاد

• Internet Technologies
• Software Engineering
• Natural Language Processing
• +۳ مورد دیگر

Prof. Dr. Christian Gawron is a Professor of Internet Technologies at the University of Applied Sciences Südwestfalen since 2019. He leads the Master's program in Applied Computer Science and has held roles as Department Head and Practice Group Leader at IBM Global Business Services (2014–2018), focusing on Watson AI, chatbots, and text mining. Previously, he was a Senior IT Architect at IBM (1999–2014), specializing in business process digitalization for the insurance sector. He earned his Dr. rer. nat. in 1999 with a dissertation on Simulation-Based Traffic Assignment , and held research roles at the Center for Applied Computer Science (ZAIK) and the Universities of Cologne and Bonn. His research spans internet technologies, software engineering, natural language processing (NLP), and traffic simulation. His academic journey includes a physics degree from the Universities of Cologne and Bonn (1989–1995). His work bridges theoretical computer science and practical AI applications, including projects like BERT-DE-NER for NLP and traffic simulation models for large networks. He advises students on theses and projects, emphasizing real-world applications of technology. Prof. Gawron’s research trends reflect a shift from foundational traffic simulation (1990s) to modern AI-driven solutions (2020s), with notable contributions to transformer models and toxic comment detection. His IBM experience underscores practical IT architecture and AI implementation. Consultations are arranged via Calendly or email. He is a prolific researcher, with key contributions in traffic flow theory (e.g., dynamic user equilibrium algorithms) and NLP (e.g., BERT-based models). His work frequently addresses interdisciplinary challenges, such as environmental impact modeling in traffic simulations (FVU cooperative, 1998). Advising & Grants: Supervised numerous theses in internet technologies and AI. Prior IBM projects included grants for AI-driven insurance process optimization and real-time traffic simulation infrastructure. Labs/Teams: Leads the Internet Technologies research group at FH Südwestfalen, collaborating with industry partners on AI and NLP applications.

• Control Systems
• Energy Management
• Distributed Optimization
• +۴ مورد دیگر

Yutaka Iino serves as an Associate Professor at Waseda University's Advanced Collaborative Research Organization for Smart Society (ACROSS) and Research Institute for Advanced Network Technology (RIANT). With over 35 years of professional experience, he transitioned from a long career at Toshiba Corporation (1984-2018) where he worked on energy management and energy-saving technologies, to his current academic position focusing on smart society element technologies including power, transportation, and information systems. Doctor of Engineering from Tokyo Institute of Technology (2015) Master's in Electrical Engineering from Waseda University (1984) Bachelor's in Electrical Engineering from Waseda University (1982) Professor Iino's research focuses on control and system engineering with particular emphasis on energy management systems and distributed optimization. His work bridges theoretical control systems with practical applications in smart grids, electric transportation, and distributed energy resources. He has pioneered approaches in decentralized optimization, modeling techniques for energy systems, and demand science applications in power networks. His research interests include Di-centralized and distributed optimization, Distributed Energy Resource management, System Control Theory, and Demand Science. Analysis of his recent publications reveals a strong focus on practical applications of distributed energy resources, particularly in the context of electric buses, photovoltaic integration, and grid congestion management. His work demonstrates a consistent trajectory toward developing market-oriented solutions for energy systems, with increasing emphasis on machine learning techniques for parameter optimization and federated learning for smart inverter control. The research spans multiple domains including electrical engineering, transportation systems, and control theory, with a clear practical orientation toward solving real-world energy challenges. SICE Paper Award, No.1995 for 'Cyber-physical Optimal Traffic Signal Control Based on a Macroscopic Traffic Model and Its Verification Using Microscopic Traffic Simulator' Best Paper Award of IEEJ Transactions on Electrical and Electronic Engineering 2021 for 'Evaluation of Mutual Effect between Power and Traffic Aiming Electrified Urban Transportation System Using Integrated Light Rail Transit and Distribution System Model' Professor Iino has secured research funding through Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research, including current projects on cooperative next-generation distribution system operation methods for mass introduction of photovoltaic power generation (2023-2027) and hybrid model analysis methods with data and physical models for automatic energy analysis (2020-2023). His committee memberships include roles in IEEE, Japan Society of Energy and Resources, The Institute of Electrical Engineers of Japan, and The Society of Instrument and Control Engineers (where he holds Fellow status). At Waseda University, Professor Iino contributes to the research ecosystem through the Advanced Collaborative Research Organization for Smart Society, where he leads efforts in developing practical energy management solutions that bridge theoretical control systems with real-world applications in smart grids and transportation electrification. His work exemplifies the integration of academic research with industry applications, leveraging his extensive industrial experience at Toshiba to inform his current academic pursuits.

Pan Heمشاهده پروفایل

استادیار

• Deep Learning
• Computer Vision
• Artificial Intelligence
• +۱۲ مورد دیگر

Pan He is an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University, part of the Samuel Ginn College of Engineering. His research focuses on developing deep learning techniques for real-time AI applications in infrastructure systems, including computer vision, 3D point cloud processing, and intelligent transportation. Education: Ph.D. in Computer Science, University of Florida B.E. in Software Engineering, Sichuan University (2015) His research interests include deep learning, computer vision, LiDAR, 3D perception, and adversarial machine learning. He develops AI techniques to empower downstream applications such as traffic signal control, anomaly detection, and infrastructure monitoring. Much of his work involves unsupervised and self-supervised learning on spatiotemporal data. His recent publications span top venues like TPAMI, ICLR, NeurIPS, CVPR, and IEEE T-ITS, focusing on topics such as explainable video anomaly detection, backdoor attacks in 3D detection, and efficient LiDAR annotation. These works demonstrate a strong trend toward robust, real-time, and interpretable AI systems for real-world infrastructure. Scientific Awards: 2025 ORAU Ralph E. Powe Junior Faculty Enhancement Award CVPR'22 and ICCV'21 Doctoral Consortium Awards Multiple Gartner Group Graduate Fellowships (2020–2022) Dean’s Award for Innovation and Creativity (SIAT, 2016) Best Bachelor Thesis Award (Sichuan University, 2015) Pan He advises students who have earned recognitions such as the CRA Outstanding Undergraduate Researcher Honorable Mention and the Wolotsz Graduate Fellowship. He has secured research grants and is actively recruiting PhD, Master’s, and undergraduate students. He has served as an Associate Editor for IEEE TNNLS and has taught courses on deep learning and computer vision. He leads a research group focused on foundational AI for pervasive computing and infrastructure intelligence.

Niklas Kolbeمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۴ مورد دیگر

Niklas Kolbe is an interim professor at the Department of Mathematics, RWTH Aachen University . His research focuses on numerical analysis, modeling of partial differential equations, and applications in cancer biology and traffic flow systems. Current affiliation: Department of Mathematics, RWTH Aachen University Academic rank: Interim Professor Research Interests Dr. Kolbe specializes in: Numerical methods for hyperbolic/parabolic PDEs Adaptive mesh refinement Lagrange-Galerkin techniques Cancer invasion modeling (stem cells, extracellular matrix) Network models for blood vessels/road systems Notable Contributions Recent publications address: Lax-Friedrichs methods in hemodynamics Relaxation approaches for fluid-solid coupling Flux-limited PDEs for glioma invasion Stochastic TGF-β signaling models

Santiago Narvaezمشاهده پروفایل

پژوهشگر

• High Performance Computing
• Parallel Programming
• C++ Programming
• +۶ مورد دیگر

Santiago Narvaez is a doctoral candidate at Technische Universität München (TUM) and a Research Associate at the Chair of Scientific Computing in Computer Science (SCCS) since 2019. He holds an M.Sc. in Computational Science and Engineering from TUM (2019) and a B.Sc. in Electrical and Telecommunications Engineering from Universidad del Cauca, Colombia. Research Interests: High Performance Computing (HPC) Parallel Programming with C++ and MPI Development of libraries for invasive/elastic/malleable MPI applications Molecular dynamics simulations Dynamic load balancing Teaching Activities: Santiago has supervised multiple seminars and lab courses at TUM, including the Advanced Programming lecture (C++), Bachelor/Master seminars in HPC, and courses like Parallel Numerics and Turbulent Flow Simulation on HPC-Systems since 2019. Students Supervised: He has mentored thesis projects by Huaiwei Zhang, Radu Raicea, Lukas Kirchmair, Chang-Gen Lai, Leonard Evers, Tim Alexander Meyerhoff, and Thomas Beranek. These projects focused on molecular dynamics simulations, library development, and algorithm evaluations for invasive computing.

• Traffic Engineering
• Automated Vehicles
• Reinforcement Learning
• +۵ مورد دیگر

Papamichail Ioannis is a Professor at the School of Production Engineering and Management, Technical University of Crete. His research focuses on advanced traffic control systems, automated vehicle navigation, and intelligent transportation systems. He specializes in macroscopic/microscopic traffic modeling, reinforcement learning applications, and optimization-based control strategies for lane-free and conventional traffic environments. Key research areas include automated vehicle trajectory planning, variable speed limit algorithms, cooperative adaptive cruise control, and intersection control for connected vehicles. His work integrates numerical methods, partial differential equations, and multiagent decision-making frameworks to address traffic congestion, safety, and efficiency challenges. Recent investigations emphasize lane-free traffic systems, exploring optimal path planning, vehicle nudging strategies, and boundary control mechanisms through microscopic simulations. He has also developed novel controllers for highway work zones and urban networks, leveraging data fusion and real-time state estimation techniques. Ioannis collaborates on EU-funded projects and actively contributes to SUMO-based simulation tools for automated vehicle testing. His research bridges theoretical control systems with practical traffic management solutions, aiming for zero congestion/accidents in future transportation networks.

• Traffic Control
• Transportation Systems
• Automation
• +۳ مورد دیگر

Amar BENASSER is an Associate Professor affiliated with the Université d'Artois, specifically within the Department of Computer Science and Automation (LGI2A). His research focuses on traffic flow modeling, control systems for transportation networks, and hybrid simulation techniques. Key areas include ramp metering optimization, variable speed limit coordination, and multi-agent systems applied to traffic management. Education: Not explicitly detailed in the text. His work emphasizes the integration of control theory and computational models to address challenges in urban traffic systems. Research themes include dynamic traffic adaptation, infrastructure coordination strategies, and the development of advanced traffic simulation frameworks. Publications span conferences such as CIFA, IFAC, and IEEE ITSC, with a focus on practical applications in transportation engineering. No scientific awards are listed, though his contributions are highlighted through collaborative projects with institutions like the LGI2A. Advising and grants are not explicitly detailed, though his involvement in multiple publications suggests active research collaboration. His primary affiliation remains the LGI2A laboratory, where he contributes to both theoretical and applied research in automated traffic systems.

• Transportation Engineering
• Traffic Flow Theory
• Crowd Dynamics
• +۳ مورد دیگر

Dr. Venkatesan Kanagaraj is an Assistant Professor in the Department of Civil Engineering at the Indian Institute of Technology Kanpur, specializing in Transportation Engineering. His research focuses on complex traffic phenomena and transportation systems modeling. Education: Ph.D., IIT Madras, 2011 M.E., College of Engineering, Guindy, Anna University, 2004 B.E., Government College of Technology, Coimbatore, 2002 Dr. Kanagaraj's research interests span Traffic Flow Theory, Crowd Dynamics, and Connected and Autonomous Vehicles, with particular emphasis on mixed traffic conditions common in developing countries. His work combines theoretical modeling with empirical data analysis to develop more accurate traffic simulation frameworks. He has made significant contributions to understanding merging behaviors, car-following dynamics, and the characteristics of disordered traffic flows. His publication record demonstrates consistent contributions to high-impact transportation journals, with a focus on Physica A and Transportation Research journals. The research shows an evolution from fundamental traffic flow theory toward more complex modeling of mixed traffic systems and autonomous vehicle integration. Scientific Awards: Marie Curie Individual Fellowship from European Commission Humboldt Research Fellowship from Alexander Von Humboldt Foundation PBC Fellowship Program for Outstanding Post-Doctoral Researchers Best Project Award for Post Graduate thesis from College of Engineering, Guindy Dr. Kanagaraj has held prestigious research positions including Marie Curie Fellow and Humboldt Research Fellow at TU Dresden, Germany, and Post-Doctoral Research Fellow at Technion - Israel Institute of Technology. His industry experience as a Scientific Software Developer at Transport Simulation Systems (TSS) in Barcelona provides practical perspective to his academic research. His work bridges theoretical transportation engineering with real-world applications, particularly in contexts with heterogeneous traffic conditions.

• Transportation Engineering
• Traffic Management
• Work Zone Safety
• +۵ مورد دیگر

Lazar Spasovic is a Professor in the Department of Civil and Environmental Engineering at the New Jersey Institute of Technology (NJIT), serving as Director of the Intelligent Transportation System Resource Center. His research focuses on transportation engineering, traffic management, and intelligent systems, with expertise in work zones, urban transit optimization, and traffic simulation modeling. He has led federally funded projects, including a 2018 study on automated truck platooning's impact on traffic flow. Key research interests include crash severity analysis using machine learning, cost-reliability tradeoffs in public transit, and deployment of in-vehicle advisory systems. He has published extensively in peer-reviewed journals and contributed to interdisciplinary projects combining traffic engineering with data science. Media engagements include commentary on NJ Transit operational challenges and freight industry trends. Notable grants include a USDOT-funded project (2018–2019) assessing environmental and performance impacts of automated vehicles. His work integrates computational methods (e.g., genetic algorithms) with real-world transportation infrastructure challenges.

• Optimization Theory
• Traffic Control Systems
• Automated Vehicle Networks
• +۳ مورد دیگر

Ioannis Papamichail is a Professor at the Technical University of Crete (TUC), leading the Dynamic Systems and Simulation Laboratory. He holds academic positions since 2004 and has been a Visiting Scholar at UC Berkeley (2010). His expertise spans Mathematical Programming, Optimal Control, and Traffic Systems Optimization . Education : - PhD in Chemical Engineering (2002), Imperial College London - MSc in Process Systems Engineering (1999), Imperial College London - Diploma in Chemical Engineering (1998), National Technical University of Athens Research Interests : Focuses on Nonlinear Programming, Global Optimization, and Optimal Control , applied to traffic and transportation systems. His work addresses challenges in automated vehicle coordination, lane-free traffic systems, ramp metering, and intelligent transportation systems (ITS). Recent trends in his publications emphasize deep reinforcement learning for autonomous driving , microscopic/macroscopic traffic modeling , and multi-agent decision-making algorithms . Key Contributions : Developed lane-free automated traffic control frameworks using LQR and model-free controllers Pioneered vehicle nudging strategies for path planning in complex networks Validated control algorithms via SUMO-based microscopic simulations Awards : 2010 IEEE Transition to Practice Award (Ramp Metering Algorithms) 2014 TRB Best Paper Award (Freeway Operations) 2020 IEEE-ITS Best Paper Award Labs & Teams : Directs the Dynamic Systems and Simulation Laboratory , collaborating on projects like: Autonomous vehicle trajectory optimization Urban traffic signal control with connected vehicle data Macroscopic traffic model calibration

Patrick LESERFمشاهده پروفایل

دانشیار

• Embedded Systems Engineering
• Model-Based Systems Engineering (MBSE)
• Automotive Software Architecture
• +۴ مورد دیگر

Patrick LESERF is an Associate Professor at ESTACA, a French engineering school specializing in transport systems, where he serves as a Teacher-researcher in ESTACA'Lab. Since joining in 2005, he has founded the embedded systems laboratory, developed academic programs including a specialized master's degree in Embedded Lighting Systems (with IOGS, Renault, and PSA), and led research collaborations with CEA-LIST on transport systems reliability using model-based approaches. His research centers on Model-Based Systems Engineering (MBSE) for embedded automotive systems, with expertise in SysML modeling, safety-security co-optimization, and AUTOSAR methodology. Key contributions include architecture optimization for critical systems, real-time communication networks (CAN/LIN/FlexRay), and embedded OS design. Recent work expands into intelligent transportation systems and electric vehicle powertrain optimization. Analysis of his 2023-2024 publications reveals a strategic shift toward AI-integrated solutions: neural architecture search for efficient deep learning models, predictive analytics for urban traffic optimization using Eclipse MOSAIC, and multi-objective optimization of battery/motor systems in electric vehicles. This evolution demonstrates integration of traditional embedded systems engineering with data-driven approaches. Scientific Awards: No major awards documented in source materials. Advising and Grants: Co-supervises PhD candidate Léo Pouy on MBSE for autonomous decision-making systems. Led the European Matelo project (statistical testing for embedded software) during industrial tenure and established ESTACA's joint research team with CEA-LIST. Directs curriculum development for embedded systems education across multiple specialized master's tracks. Labs and Teams: Founded ESTACA'Lab's embedded systems research group in 2005, scaling it to four teacher-researchers. The lab focuses on model engineering, transport communication networks, and software architecture optimization, supported by a 350-hour teaching program covering embedded networks, OS, and microcontrollers. Current activities include steer-by-wire systems and IoV applications.

• Civil Engineering
• Transportation Engineering
• Hydraulic Modelling
• +۵ مورد دیگر

Dr. Marc Miska is a Senior Lecturer at Queensland University of Technology (QUT), affiliated with the School of Civil & Environmental Engineering. He holds a PhD from Delft University of Technology and has over 15 years of experience in applied informatics for civil engineering, spanning hydraulics, transport systems, and container logistics. His research focuses on data-driven solutions, including smoothed particle hydrodynamics for urban flood simulation, digital twins in stormwater management, and ontology-based hydraulics models. He teaches construction methodologies and contracting regulations, and has contributed to projects like the Brisbane Metropolitan traffic simulation framework. Key research interests include transport modeling, urban hydrology, and integrating new technologies into civil engineering practice. Recent work emphasizes flood modeling using SPH methods and improving decision support systems through simulation. His publications span 20+ years, addressing traffic simulation, sensor data fusion, and sustainable construction practices. Miska has supervised doctoral and master’s students on topics like BRT station design, traffic signal optimization, and worker productivity in harsh climates. Education: Doctor of Philosophy (Civil Engineering), Delft University of Technology, Netherlands Professional Experience: Senior Lecturer, QUT (2018–present) Project Leader, Smart Transport Research Centre, QUT (2010–2018) Postdoctoral Research Fellow, University of Tokyo (2007–2010) Teaching: Coordinates EGB382 (Construction Methodologies) and EGB482 (Contracting Regulations) Guest lectures on mobile computing (IAB230) Research Contributions: His work bridges theory and practice through tools like OpenTrafficSim and SPH-based flood models. Recent trends in publications emphasize environmental engineering (soil-carbon analysis, rainfall simulators) and smart transport systems (BRT optimization, Bluetooth data analysis). His frameworks are used in urban planning and disaster risk mitigation. Awards: None explicitly listed. Grants & Supervision: Supervised 6+ doctoral projects (e.g., heterogeneous traffic modeling, BRT station design) and 2 master’s studies. Collaborates with industry on transport data standards and infrastructure resilience. Labs/Teams: Active in QUT’s Civil Engineering discipline, contributing to the School’s focus on sustainable infrastructure and digital innovation.

• Stochastic Partial Differential Equations
• Road Traffic Modeling and Simulation
• Mathematical Modeling of Porous Media
• +۳ مورد دیگر

Rim FAYAD is a Researcher affiliated with INSA Rouen's Mathematical Engineering Department. She completed her PhD in November 2017 to January 2021, focusing on microscopic and macroscopic modeling of road traffic, supervised by N. Forcadel and I. Ciotir. Her research interests include stochastic PDEs, road traffic systems, and porous media modeling. She served as an ATER (Teaching and Research Contract) from 2020/21 to 2022, teaching at the L3, M1, and STPI levels. She also conducted a 12-month postdoc in 2022/23 on the DEPHY3GEO project, funded by the Normandy Region and ERDF, studying porous media modeling with I. Ciotir. Her work bridges applied mathematics and real-world systems, including contributions to traffic flow models published in ESAIM: M2AN . She is part of the LMI (Control theory, optimization, and probability/statistics) team at INSA Rouen.

Mohamed Abdel-Atyمشاهده پروفایل

استاد

• Traffic Safety
• Intelligent Transportation Systems
• Connected and Automated Vehicles
• +۱۲ مورد دیگر

Mohamed Abdel-Aty is a Pegasus Professor and former Chair of the Department of Civil, Environmental and Construction Engineering at the University of Central Florida (UCF), College of Engineering and Computer Science. He holds the prestigious Trustee Chair and is globally recognized for his transformative work in transportation safety and intelligent transportation systems. Education: Ph.D. in Civil Engineering, University of California, Davis, 1995 His research focuses on traffic safety, big data analytics, connected and automated vehicles, real-time crash prediction, and active traffic management. He has pioneered methods that shift road safety from reactive to proactive, using real-time data to predict crashes 5–10 minutes in advance. His work integrates machine learning, simulation, and computer vision to enhance transportation safety and efficiency. His recent publications reflect a strong trend in applying advanced statistical and AI models—such as random parameters, bivariate probit, and mixture-of-experts architectures—to analyze crash severity, vehicle conflicts, driver behavior, and trajectory prediction. These studies leverage real-world data from connected vehicles, drones, and traffic sensors, emphasizing practical implementation and policy impact. Scientific Awards and Honors: Pegasus Professor, UCF (2015) Trustee Chair, UCF (2017) Roy W. Crum Distinguished Service Award, TRB (2020) Prince Michael International Road Safety Award (2019) Francis C. Turner Award, ASCE (2019) Clarivate Highly Cited Researcher (2020–2023) UCF Medal of Societal Impact (2025) Lifetime Achievement Safety Award, ARTBA (2019) Abdel-Aty has secured over $32 million in research funding and has graduated 44 Ph.D. and 63 master’s students. He currently mentors 15 Ph.D. students. He served as graduate program coordinator and led the development of UCF’s master’s program in smart cities. He is Editor-in-Chief of Accident Analysis & Prevention and serves on multiple editorial boards, significantly shaping the field’s scholarly discourse. He leads the UCF Smart and Safe Transportation (SST) Lab, which developed CitySim—a drone-collected trajectory database used by over 480 researchers globally. His team created software for detecting traffic conflicts and near-misses, and their real-time crash risk prediction system is implemented by the Florida Department of Transportation and emulated internationally.