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Mashrur ChowdhuryView profile

Professor

• Cyber-Physical Systems for Connected and Autonomous Vehicles
• Cyber-Physical Systems for Smart Cities
• Intelligent Transportation Systems
• +4 more

Dr. Mashrur “Ronnie” Chowdhury is the Eugene Douglas Mays Chair of Transportation and holds triple professorial appointments in Automotive Engineering, Civil Engineering, and Computer Science at Clemson University. He is the founding director of the USDOT UTC National Center for Transportation Cybersecurity and Resiliency (TraCR) and the USDOT UTC Center for Connected Multimodal Mobility (C2M2), and co-director of the Complex Systems, Analytics and Visualization Institute (CSAVI). Education B.S., Civil Engineering – Bangladesh Institute of Technology, 1988 M.S., Transportation – Morgan State University, 1991 Ph.D., Civil Engineering – University of Virginia, 1995 Research Interests Dr. Chowdhury’s scholarship converges at the intersection of cyber-physical systems , connected and autonomous vehicles , and smart-city transportation . His work advances secure, resilient, and data-rich mobility by integrating big-data analytics , artificial intelligence , and vehicle-to-everything (V2X) communication . Core themes include: Cyber-Physical Systems for Connected and Autonomous Vehicles Cyber-Physical Systems for Smart Cities Transportation Cybersecurity and Resiliency Big-Data-driven Intelligent Transportation Systems Sustainable and Green Transportation Solutions Publication Landscape Between 2009 and 2015, Dr. Chowdhury authored or co-authored more than 45 refereed journal articles. These works collectively trace an evolution from foundational traffic simulation and incident-management studies to cutting-edge research on connected vehicle security , energy-efficient electrified transportation , and big-data-enabled urban mobility analytics . A pronounced emphasis on cyber-physical security , overweight-truck infrastructure impacts , and real-time AI applications is evident across the portfolio. Scientific Awards & Honors Wilbur Smith Distinguished Transportation Educator Award (2015) AASHTO High-Value Research Project Award (2014) Faculty Mentoring Award, CECAS (2013) McQueen Quattlebaum Faculty Achievement Award (2012) National Academy of Engineering Indo-U.S. Frontiers of Engineering Invited Speaker (2012) Clemson Board of Trustees Award for Faculty Excellence (2011, 2010) IDEaS Professor, CECAS (2010) Frank A. Burtner Award for Excellence in Advising (2010) Murray Stokeley Award for Excellence in Teaching (2009) Fellow, American Society of Civil Engineers (ASCE) Senior Member, IEEE Advising & Grants Dr. Chowdhury has mentored more than 30 Ph.D. and M.S. students whose names appear as first or co-authors on his publications. His research funding portfolio includes multi-million-dollar grants from the U.S. Department of Transportation (USDOT) through two national UTC centers—TraCR and C2M2—focused on cybersecurity and multimodal mobility innovation. Laboratories & Teams He directs the Connected Transportation Lab located in 351 Engineering Innovation Building and maintains an office in 216 Lowry Hall. These facilities host interdisciplinary teams of graduate researchers, post-docs, and visiting scholars advancing next-generation connected and autonomous transportation systems.

• Artificial Intelligence
• Wireless Communications
• Cognitive Radio Networks
• +4 more

Prof. Juraj Gazda is a Professor at the Faculty of Electrical Engineering and Informatics, Technical University of Kosice. His research focuses on cognitive radio networks, artificial intelligence, green communications, and agent-based modeling. He holds a PhD in engineering from TUKE (2010) and has extensive industry experience as an external consultant at Nokia Networks (2011–2014), advising on LTE wireless systems. He has been a guest researcher at institutions like Ramon Llull University (Spain), Technical University of Hamburg (Germany), and Delft University of Technology (Netherlands). His teaching includes stochastic modeling and data analysis courses. Gazda’s work bridges academia and industry, emphasizing network security, autonomous systems, and 6G technologies. Research highlights include contributions to UAV-assisted networks, blockchain-based spectrum management, and AI-driven edge computing. His projects address real-world challenges in 5G/6G networks, including energy efficiency, secure communication, and autonomous vehicle coordination. Gazda actively collaborates with global tech firms like Verizon Wireless, contributing to network design and optimization. Publications span AI applications in healthcare, vehicular networks, and quantum computing. He advocates for interdisciplinary research, integrating machine learning, blockchain, and metaverse technologies to address future mobility and communication needs.

• Computational Hydrodynamics
• Computational Fluid Dynamics
• Scientific Computing
• +3 more

Anargiros Delis is an Associate Professor of Computational Mathematics at the School of Production Engineering & Management, Technical University of Crete since 2003. He holds a B.Sc. in Mathematics from the University of Crete (1993), an M.Sc. in Numerical Analysis and Computing from the University of Manchester (1994), and a Ph.D. in Applied and Computational Mathematics from the University of the West of England (1998). Education: B.Sc. Mathematics, University of Crete (1993) M.Sc. Numerical Analysis & Computing, University of Manchester (1994) Ph.D. Applied and Computational Mathematics, University of the West of England (1998) His research focuses on computational hydrodynamics, computational fluid dynamics, and scientific computing, with notable contributions to free surface flows, finite volume methods, and applications in coastal engineering, traffic dynamics, and environmental modeling. Recent work includes advancements in numerical simulations for epidemics transport dynamics, optimization of wind turbines using RANS-BEM solvers, and PDE-based traffic flow control systems. Key research themes include macroscopic modeling of epidemics, unstructured grid discretizations for Boussinesq-type models, and the development of high-resolution numerical schemes. His work bridges theoretical advancements with practical applications in renewable energy, urban planning, and hydraulic infrastructure. Delis is affiliated with the Applied Mathematics and Computers Laboratory under the Science Division at the Technical University of Crete, contributing to interdisciplinary projects at the intersection of computational science and engineering.

Ioannis NikolosView profile

Professor

• Computational Fluid Dynamics
• Turbomachinery Design
• Wind Turbine Optimization
• +5 more

Ioannis Nikolos is a Professor at the School of Production Engineering and Management, Technical University of Crete, and holds a Visiting Professor position at the Institute of Plasma Physics & Lasers (IPPL), Hellenic Mediterranean University. With over 30 years of R&D experience, he has coordinated 39 projects and participated in 13 more. His research focuses on Computational Fluid Dynamics (CFD), Turbomachinery, Design Optimization, and Traffic Flow Modeling. He has authored/co-authored 60 journal papers, 110 conference papers, and three books, with an h-index of 24 (Google Scholar). Education: Diploma (1990) and PhD (1996) in Mechanical Engineering from the National Technical University of Athens (NTUA). His expertise spans fluid dynamics, engineering design optimization, and unmanned aerial vehicle aerodynamics. He is a Senior Member of AIAA and serves as an Associate Editor for ASME journals. Research Interests: Computational Engineering, Turbomachinery Component Design, Wind Turbine Optimization, Traffic Flow Modeling, and Plasma Physics applications. His work integrates computational intelligence with traditional engineering methods. Awards: Recipient of the IEEE ITS Society Outstanding Application Award (2018) for contributions to traffic management systems. He leads the Turbomachinery & Fluid Dynamics Laboratory and has supervised 7 completed PhD theses. Grants & Advising: Extensive R&D funding from EU, Industry, and Greek State. Currently supervising 3 PhD students. Editorial roles include ASME Journal of Fluids Engineering and Water. Labs & Teams: Director of the Turbomachinery & Fluid Dynamics Laboratory, collaborating on projects involving CFD, plasma physics, and autonomous systems.

• Flight dynamics and control
• Unmanned vehicle systems
• Morphing wing aircraft structures
• +15 more

Dr. Kamesh Subbarao is a Professor and director of the Aerospace Systems Laboratory (ASL) in the Mechanical and Aerospace Engineering Department at The University of Texas at Arlington (UTA). He has been a faculty member at UTA since 2003, progressing from Assistant Professor to Associate Professor and finally to Professor in 2019. His academic journey began with a PhD from Texas A&M University in 2001, followed by work at The MathWorks Inc. before joining UTA. Dr. Subbarao's educational background includes a PhD in Aerospace Engineering from Texas A&M University (2001), an MS in Aerospace Engineering from the Indian Institute of Technology (1995), and a BS in Aerospace Engineering from the Indian Institute of Technology (1993). His research interests span flight dynamics and control, unmanned vehicle systems, morphing wing aircraft structures, air traffic management, reduced order modeling of fluid-structure interactions, cooperative control of large scale interconnected systems subject to communication delays, multi-sensor fusion applied to aircraft guidance and spacecraft navigation, bipedal locomotion, and uncertainty characterization in orbital mechanics. His work focuses on nonlinear and adaptive control, linear and nonlinear filtering/estimation approaches, and cooperation and coordination for multiple unmanned vehicles subject to measurement uncertainties and distributed time delays. Dr. Subbarao's recent publications demonstrate strong focus on uncertainty quantification, cooperative control of multiple vehicles, UAV swarms, lunar exploration, and aircraft safety. His research shows a consistent trajectory toward more complex multi-agent systems, incorporating machine learning techniques for improved prediction and control, with applications spanning both terrestrial and space environments. President's Excellence in Teaching Award (2021) Lockheed Martin Aeronautics Company Excellence in Teaching Award (2016) AIAA Foundation Award for "Model Reference Adaptive Control" (2001) Best Paper of the Space Flight Mechanics Conference, American Astronautical Society (2021) Multiple Outstanding Reviewer awards from AIAA Journal of Guidance, Control, and Dynamics Dr. Subbarao has been actively involved in advising students, as evidenced by his nomination for the Outstanding Advisor Award in 2018-19. His research has been generously funded by major organizations including DARPA, NSF, AFRL, ONR, NASA, Lockheed Martin, Whirlpool Inc., Nextgen Aeronautics, and Hypercomp Inc. His laboratory work, particularly through the Aerospace Systems Laboratory, has produced significant contributions to the field of aerospace engineering and control systems. He is a Fellow of the Royal Aeronautical Society (FRAeS), an Associate Fellow of AIAA, and Senior Member of IEEE, ASME, and the American Astronautics Society (AAS), reflecting his standing in the academic and professional community.

• Intelligent Transportation Systems (ITS)
• Traffic Signal Systems
• Smart Traffic Sensors
• +3 more

Taylor Li is an Associate Professor in the Department of Civil Engineering at The University of Texas at Arlington (UTA). He specializes in Intelligent Transportation Systems (ITS), Traffic Signal Systems, and Smart Traffic Sensors. His work focuses on improving traffic management through advanced technologies like LiDAR, connected vehicles, and data-driven optimization. Education PhD in Civil Engineering, Virginia Polytechnic Institute and State University (2009) MS in Systems Engineering, Beijing Jiaotong University (2002) BS in Mechanical Engineering and Control, Beijing Jiaotong University (1999) Research Interests Dr. Li's research emphasizes traffic signal optimization, sensor-based safety systems, and the integration of connected and automated vehicles (CAVs) into infrastructure. His work addresses challenges in urban traffic efficiency, pedestrian safety, and resilient transportation networks. Recent projects include developing dynamic signal timing algorithms using real-time data and LiDAR-based tracking systems to reduce red-light running incidents. Grants & Awards Recipient of multiple grants from USDOT, TxDOT, and NSF totaling over $3 million Finalist for TRB Network Modeling Committee Best Paper Award (2016) Best Paper Awards from ITS America and the International Road Federation (2009) Professional Service Associate Editor, ASCE Journal of Urban Planning and Development Chair, TRB Traffic Signal Systems Committee (ACP25) Member, Transportation Research Board Simulation Committees (ACP80) Labs & Teams Leads the Smart Transportation Systems Lab at UTA, collaborating with industry partners like PTV AG and TxDOT on real-world deployment of innovative traffic management solutions.

Gabriel Ibarra-MejiaView profile

Associate Professor

• Occupational Health
• Environmental Health
• Ergonomics
• +6 more

Dr. Gabriel Ibarra-Mejia is an Associate Professor of Public Health Sciences at the University of Texas at El Paso (UTEP), combining clinical expertise as an MD with a PhD in Ergonomics. His research focuses on occupational health disparities, environmental exposures (e.g., PM2.5, BTEX compounds), and musculoskeletal injury prevention in vulnerable populations, particularly along the U.S.-Mexico border. He leads NIH/CDC/EPA-funded projects like the $200K environmental health impact assessment near the Bridge of the Americas and studies PM2.5 exposure at border crossings. His work integrates biomechanical modeling, biomarker analysis, and community-engaged research to develop culturally appropriate interventions. Notable collaborations include Texas Tech and UC Berkeley in expanding climate-related health research, such as valley fever trends and heat stress in outdoor workers. He prioritizes health equity through bilingual health literacy programs and ergonomic training for Hispanic/Latino communities. Dr. Ibarra-Mejia has over 85 peer-reviewed publications and serves in leadership roles at ASTM International and the Human Factors Society. Recent studies emphasize dust events' health impacts, short-term air pollution effects, and occupational risks for construction workers. His interdisciplinary approach addresses both clinical and engineering challenges, translating research into practical safety solutions and environmental justice advocacy. Grants: $200K NIH project, $142K CDC study, collaborations with EPA Leadership: President of International Ergonomics and Safety Organization Labs/Teams: Interdisciplinary environmental health teams, community-engaged research initiatives

Xiaowei ShiView profile

Assistant Professor

• Connected and Automated Vehicles
• Transportation Systems
• Vehicle-to-Everything Communications
• +2 more

Dr. Xiaowei (Tom) Shi is an Assistant Professor in Civil and Environmental Engineering at the University of Wisconsin-Milwaukee's College of Engineering & Applied Science and serves as the Founder and Director of the Automated, Connected & Electric Mobility Systems (ACES) Lab. He holds a PhD in Transportation Engineering from the University of South Florida with additional graduate degrees from Beijing Jiaotong University. His research specializes in evaluating and developing technologies for connected/automated vehicles (CAVs), utilizing hardware-in-the-loop methodologies to advance cooperative driving automation systems. His work integrates transportation engineering, control systems, optimization, and data science. Publications demonstrate consistent focus on CAV technologies with evolving emphasis on human factors and sustainability (2021-2024). Early work centered on fundamental traffic modeling and vehicle operations, while recent publications increasingly address user acceptance, energy efficiency, and neural network applications in transportation systems. He teaches courses covering transportation systems analysis, intelligent transportation technologies, and traffic operations modeling. He maintains active participation in IEEE technical committees and TRB's Emerging Technologies in Network Modeling panel.

Alina VereshchakaView profile

Assistant Professor

• Optimal control in complex systems
• Social behavior modeling
• Deep reinforcement learning
• +5 more

Alina Vereshchaka is an Assistant Professor of Teaching in the Department of Computer Science and Engineering at the University at Buffalo. She holds a PhD in Computer Science from the same institution (2021). Her research focuses on optimal control in complex systems, including social behavior modeling, deep reinforcement learning, multi-agent systems, adversarial machine learning, transportation dynamics, and large-scale social system dynamics. She leads projects involving epidemic modeling, smart city infrastructure optimization, and disinformation detection. Education: PhD in Computer Science, University at Buffalo, 2021 Her work bridges theoretical machine learning advancements with real-world applications in public health, transportation, and crisis management. Key research themes include: Optimizing epidemic intervention strategies using reinforcement learning Urban traffic prediction through vehicle trajectory analysis Automated disinformation detection systems Multi-agent resource allocation during disasters Dr. Vereshchaka's recent publications (2018-2024) emphasize data-driven decision-making frameworks across transportation networks, healthcare systems, and social media platforms. Though no specific grants or awards are listed, her work reflects interdisciplinary collaboration with engineering and public health domains. She currently advises no listed students and maintains an active research website and dblp profile for further details.

Nizam UddinView profile

Professor

• Design and Analysis of Experiments
• Linear/Nonlinear Models
• ANOVA/Covariance Analysis
• +5 more

Dr. Nizam Uddin is a Professor and Undergraduate Coordinator in the Department of Statistics and Data Science at the University of Central Florida (UCF), part of the College of Sciences. He has held this position since joining UCF and oversees undergraduate academic programs while maintaining an active research agenda. Education: Dr. Uddin holds a Ph.D. in Statistics from Old Dominion University (1989), an M.S. in Mathematics from the University of Saskatchewan (1985), and dual M.S. and B.S. degrees in Statistics from the University of Dhaka, Bangladesh (1979 and 1977). Research Interests: His work focuses on statistical methodology including experimental design (linear/nonlinear models, ANOVA/covariance analysis), regression techniques, and categorical data analysis. He has applied these methods to diverse domains such as transportation safety engineering, biostatistics, environmental science, and healthcare analytics. Recent research emphasizes predictive modeling for traffic safety interventions, analysis of driver behavior patterns, and statistical methods for environmental contamination studies. Professional Contributions: Dr. Uddin has authored over 100 peer-reviewed articles spanning experimental design theory, transportation safety analytics, and interdisciplinary applications of statistical methods. His work bridges theoretical statistical advancements with real-world problem-solving in areas like infrastructure safety optimization and public health policy analysis. Office & Contact: Located in TC2 Room 208, Dr. Uddin can be reached at 407-823-2692 or via email at Nizam.Uddin@ucf.edu.

Robert L. MullenView profile

Professor

• Computer Modeling of Engineering Systems
• Biomechanics
• Mechanical Behavior of Micro Electro-Mechanical Systems
• +2 more

Robert L. Mullen is a Professor in the Department of Civil and Environmental Engineering at the Molinaroli College of Engineering and Computing, University of South Carolina. His work bridges computational mechanics, uncertainty quantification, and interdisciplinary applications in biomechanics and transportation systems. Ph.D. in Applied Mechanics, Northwestern University (1981) M.S. in Structural Mechanics, University of Illinois (1977) B.S. in Structural Engineering, University of Illinois (1976) Research focuses on: Computer modeling of engineering systems Biomechanics Mechanical behavior of micro electro-mechanical systems Coupled field problems Interval methods for uncertainty Key trends in his 2018-2025 publications include: Advancements in interval finite element methods for structural analysis Machine learning integration in transportation infrastructure monitoring Uncertainty quantification across mechanical and civil engineering domains Innovations in data fusion for traffic management Biotechnological applications (vaccine stabilization) Durability studies in transportation assets Scientific recognition includes: Fellow, American Society of Civil Engineers Professional contributions extend to patents in material science, biotechnology, and structural systems.

Mark HolmesView profile

Professor

• Applied Mathematics
• Biomechanics
• Mathematical Biology
• +3 more

Mark Holmes is a Professor at Rensselaer Polytechnic Institute (RPI), affiliated with the Center for Modeling, Optimization and Computational Analysis (MOCA). His research focuses on applied mathematics, particularly in mechanoreception (e.g., tactile sensing in skin and auditory systems) and the mathematical modeling of the sleep-wake cycle. He integrates biomechanical principles with nonlinear dynamics and numerical analysis to address problems in biological systems. Dr. Holmes has authored influential textbooks including Introduction to the Foundations of Applied Mathematics (2009), Introduction to Perturbation Methods (2013), and Introduction to Scientific Computing and Data Analysis (2016). His work bridges theoretical mathematics with real-world applications in engineering and biology, emphasizing interdisciplinary collaboration. His recent publications explore optimization methods, numerical techniques for differential equations, and biomechanical models of sensory systems. He has contributed to understanding the cochlear amplification mechanism and the role of neurotransmitters in sleep regulation. His research often employs perturbation methods and computational modeling to dissect complex biological phenomena. Dr. Holmes’ academic contributions are further evident through his editorial roles, conference presentations, and involvement in curriculum development at RPI. He remains active in both foundational mathematical research and its applied extensions in health and engineering.

• Cybersecurity
• Software Defined Networks
• Digital Forensics
• +4 more

Dr. Suleman Khan is an Associate Professor at the University of Bradford's School of Computer Science, AI & Electronics. He holds a PhD (Distinction) in Cybersecurity from Universiti Malaya (2017) and previously worked as a Senior Network Officer at Pakistan International Airlines. His academic career includes roles at Monash University, Northumbria University, and the University of Central Lancashire. He leads the Innovate UK-funded CyberASAP project as PI and has published over 90 high-impact articles. His research focuses on cybersecurity, software-defined networks, digital forensics, IoT, and AI. Education: PhD in Cybersecurity, Universiti Malaya, Malaysia (2017) Research Interests: Network forensics, privacy preservation, trust management, SDN security, IoT security, AI-driven defense mechanisms. His work emphasizes innovative solutions for cyber threats in modern networks and intelligent systems. Awards: Fellow Member of the HEA IEEE Member Grants & Projects: Innovate UK - CyberASAP (Cyber Security Academic Startup Accelerator Programme) Teaching Areas: Cybersecurity, Networking, and Information Systems.

• Indoor Air Quality
• Particle Resuspension
• Human Exposure Science
• +3 more

Professor Andrea Ferro holds a professorship in Civil and Environmental Engineering at Clarkson University, where she directs research on indoor air quality, particle resuspension dynamics, and respiratory aerosol emissions. Her NSF ADVANCE SPACES project promotes community engagement in STEM fields. A registered professional engineer, Dr. Ferro teaches courses in environmental engineering, atmospheric chemistry, and human exposure analysis. Her research combines experimental methods with modeling to understand pollutant fate in built environments. Her research program focuses on: Mechanisms of particle resuspension from indoor surfaces Respiratory aerosol generation during speech and breathing Impacts of human activities on indoor air quality Airborne disease transmission mechanisms Exposure assessment methodologies Current projects investigate factors influencing virus resuspension and respiratory particle emissions across age groups. Analysis of her recent publications reveals substantial contributions to: Pediatric respiratory emission characterization Surface-to-air pathogen transfer mechanisms Electrostatic detachment of particles Impact of flooring materials on resuspension Computational modeling of aerosol transport This work informs building ventilation standards and infection control practices. Professor Ferro's scientific awards include Fellowship in AAAR (2023) and ISIAQ (2020), multiple Distinguished Service Awards, and an NSF CAREER Award (2008). Her laboratory develops novel methodologies for exposure assessment and particle characterization.

Virginia P. SisiopikuView profile

Professor

• Traffic Engineering
• Intelligent Transportation Systems
• Congestion Management
• +5 more

Virginia P. Sisiopiku is a Professor in the Department of Civil, Construction, and Environmental Engineering at the University of Alabama at Birmingham (UAB). She is the founding director of the UAB Transportation Engineering and Development (TREND) Lab and has over 25 years of experience in transportation engineering as an academic and consultant. Her research focuses on traffic operations, intelligent transportation systems (ITS), sustainable transportation, and emerging technologies like connected and autonomous vehicles (AVs). Sisiopiku has authored over 235 peer-reviewed publications and received numerous awards, including ITE Fellow (2014) and the 2018 Engineering Educator of the Year Award. She is also actively involved in university committees and serves as advisor to the UAB ITE Student Chapter and Society of Women Engineers (SWE). Education: Ph.D. in Civil Engineering (University of Illinois at Chicago), M.S. in Civil Engineering (University of Illinois at Chicago), B.S. in Civil Engineering (Aristotle University of Thessaloniki). Research Interests: Traffic congestion management, traffic safety, simulation modeling, micromobility, and sustainable urban transportation systems. Her work integrates data analytics and emerging technologies to enhance transportation efficiency and safety, with a focus on livable communities and accessibility. Grants & Leadership: Principal investigator (PI) or co-investigator (Co-PI) on over 50 funded projects totaling millions of dollars, including USDOT STRIDE initiatives. She leads collaborations with regional and national agencies, such as the Alabama Department of Transportation (ALDOT) and the Regional Planning Commission of Greater Birmingham. Awards & Recognition: Recognized for mentorship (2010 Dean’s Award) and teaching (2007 Presidential Award). Her contributions to advancing transportation engineering have been acknowledged by the Federal Highway Administration (FHWA), IEEE, and Women’s Transportation Seminar (WTS). Labs & Teams: Directs the UAB TREND Lab, which focuses on innovative transportation solutions. Collaborates with interdisciplinary teams at the UAB Sustainable Smart Cities Research Center and the Southeastern Transportation Research, Innovation, Development, and Education (STRIDE) Center.