جست‌وجوی استاد و پژوهشگر

Marcia G. Oryمشاهده پروفایل

استاد

• Aging and Health Promotion
• Chronic Disease Management
• Evidence-based Prevention Research
• +۴ مورد دیگر

Marcia G. Ory is a Regents & Distinguished Professor in the Department of Environmental and Occupational Health at Texas A&M University, driving transformative research in aging, chronic disease management, and implementation science. Her work bridges public health theory with community-based interventions to improve health outcomes for vulnerable populations, particularly older adults and caregivers. Education: BA in Sociology/Psychology, University of Texas at Austin MA in Sociology/Human Development, Indiana University Bloomington PhD in Family Studies (Sociology)/Human Development, Purdue University MPH in Chronic Disease Epidemiology, Johns Hopkins Bloomberg School of Public Health Research Focus: Dr. Ory pioneers evidence-based approaches to aging and health promotion, with groundbreaking work in dementia caregiving, diabetes self-management, and opioid crisis response. Her signature integration of health technology empowers patients through digital platforms like GamePlan4Care, while her implementation science expertise translates research into real-world community programs. She champions health equity through rural-focused initiatives addressing disparities in chronic disease management and access to care. Publication Trends: Recent work (2023-2025) reveals three dominant trajectories: (1) Digital health innovations for dementia caregivers and diabetes management; (2) Multi-ancestry genomic analyses of Alzheimer’s risk; (3) Policy-focused studies on opioid surveillance and transportation equity. Her research consistently leverages large-scale data (commercial insurance, national surveys) to expose urban-rural disparities while developing scalable interventions for vulnerable aging populations. Awards & Recognition: Fellow of four national academies (Behavioral Medicine Research, Health Behavior, Gerontology, Behavioral Medicine) World’s Top 2% Scientist (Stanford 2021-2023), Top 1000 Social Sciences Researcher (Research.com) APHA Philip G. Weiler Lifetime Achievement Award, Healthcare Leadership Council Redefining American Healthcare Award Distinguished Alumna/Scholar (Purdue), Distinguished Mentor (Gerontological Society) Mentoring & Leadership: As a nationally recognized mentor (TAMU Women’s Faculty Network Award), she cultivates next-generation researchers through doctoral seminars in implementation science. Her federally funded grants consistently emphasize community engagement, translating findings into evidence-based programs like the LIVE WELL Initiative that serve 50,000+ older adults annually. She directs major NIH-supported dementia caregiving studies while advising federal agencies on aging policy. Research Ecosystem: Dr. Ory leads the Center for Community Health and Aging, coordinating interdisciplinary teams across public health, gerontology, and data science. Her collaborations span the Texas A&M System, Johns Hopkins, and international partners in Ukraine and Australia, with recent projects developing virtual reality interventions for depression and autonomous vehicle interfaces for cognitively impaired older adults.

Ondrej Vaculinمشاهده پروفایل

استاد

• Passive Vehicle Safety
• Automated Driving
• Vehicle Dynamics
• +۳ مورد دیگر

Prof. Ondrej Vaculin, Ph.D., is a Professor at Technische Hochschule Ingolstadt (THI), specializing in passive vehicle safety, mechatronic systems, and automated driving. He joined THI in 2018 and previously held roles at TÜV SÜD Prague (2008–2018) as Vice President for Safety and Security in Automotive, and as a researcher at Czech Technical University (2005–2008) and DLR Oberpfaffenhofen (2000–2005). His research focuses on enhancing vehicle safety through advanced simulation, sensor integration, and machine learning applications. Education: Ph.D. in Mechanics of Solids, Deformable Bodies and Continua from Czech Technical University in Prague (2001), and a degree in Technical Cybernetics from the Faculty of Electrical Engineering at the same university (1991). His work bridges theoretical research and practical implementation, addressing challenges in automated driving systems, crash simulation, and human body diversity in safety design. Research interests include passive safety systems, autonomous vehicle dynamics, and infrastructure integration for safety enhancements. Recent publications emphasize collaborative smart infrastructure, sensor fusion for free space detection, and machine learning in crash detection. He actively contributes to FISITA, serving as a Council Delegate and member of technical committees. Awards/memberships: Active in FISITA, holding leadership roles in technical committees. No explicit awards listed, though his contributions to automotive safety standards are notable. Grants and advising: While no specific grants or students are detailed, his extensive industry and academic collaborations (e.g., IN2Lab testing field projects) highlight his role in applied research and development.

Eduardo Alonsoمشاهده پروفایل

استاد

• Artificial Intelligence
• Reinforcement Learning
• Computational Neuroscience
• +۲ مورد دیگر

Professor Eduardo Alonso is Director of the Artificial Intelligence Research Centre (CitAI) and Department Research Director at City St George's, University of London. His research bridges novel AI techniques with Explainable AI and Artificial General Intelligence, with significant focus on legal and ethical implications. Research spans: Computational neuroscience and evolutionary biology modeling Deep learning architectures for reinforcement learning Mathematical models of emergence in complex systems Industrial AI applications with societal impact Professor Alonso has secured over £1M in funding from Innovate UK, EU EIT-Digital, and US NSF grants. He currently supervises 13 PhD students working on ethical AI, reinforcement learning, and cybersecurity. Recent publications focus on transformer architectures for multi-agent systems, power grid optimization via GNNs, and adversarial robustness in security systems. Awarded the IEEE Computational Intelligence Society Spotlight Paper Award in 2013.

• Operations Research
• Data Analytics
• Machine Learning
• +۴ مورد دیگر

Dr. Katie McConky is a Professor and Department Head of Industrial and Systems Engineering at Rochester Institute of Technology (RIT). She holds a Ph.D. in Industrial Engineering from SUNY Buffalo and prior experience as a research scientist at CUBRC Inc., where she worked on military and data mining projects. Her research focuses on operations research, machine learning, and energy systems optimization, addressing challenges in combinatorial optimization, cyberattack forecasting, and sustainable energy management. She has secured funding from agencies like ONR, AFRL, NASA, and NYSERDA. Education: BS and MS (RIT), Ph.D. (SUNY Buffalo) Key Roles: Department Head, Faculty Member, Research Scientist (CUBRC) Her work spans applications such as kidney exchange optimization, rover mission planning, and energy demand forecasting. She emphasizes interdisciplinary collaboration in her research, integrating machine learning with traditional optimization techniques. Dr. McConky’s publications highlight advancements in forecasting methodologies for cyber threats, energy systems, and transportation logistics. She teaches courses including Operations Research and Forecasting Methods, emphasizing practical software tools like Gurobi. Her contributions include patents on remote activity detection and energy storage optimization. Her research is supported by grants from federal agencies and industry partners, reflecting her expertise in both academic and applied domains.

• Generative Programming
• Model-Based Development
• Software System Families
• +۷ مورد دیگر

Krzysztof Czarnecki is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering, with a cross-appointment to the School of Computer Science. He serves as leader of the Waterloo Intelligent Systems Engineering Lab and holds the title of University Research Chair. His research focuses on generative software development, model-driven engineering, and autonomous systems, particularly in automotive cybersecurity and perception safety. Education: Doctorate in Computer Science, Technical University of Ilmenau (1999) Master of Science in Computer Science, Technical University of Ilmenau (1995) Bachelor of Science in Computer Science, California State University (1994) Research Interests: Dr. Czarnecki's work spans generative programming, software product lines, and safety-critical AI for autonomous vehicles. Recent projects address robust perception systems, uncertainty quantification in neural networks, and strategic driving behavior modeling. He co-authored Generative Programming (Addison-Wesley, 2000), a foundational text in the field. Publications Trends: Recent work emphasizes multimodal AI integration (e.g., LEO-MINI), 3D object detection improvements (OV-SCAN), and safety assurance frameworks for autonomous systems. His research bridges theoretical software engineering with applied robotics challenges. Awards: Premier’s Research Excellence Award (2004) British Computing Society’s Upper Canada Award (2008) University Research Chair, University of Waterloo (2023) Teaching & Leadership: Teaches courses like ECE 495 (Autonomous Vehicles) and ECE 651 (Software Engineering Foundations). Oversees WatCAR initiatives and collaborates on industry projects through the NSERC Bank of Nova Scotia Industrial Research Chair (previous). Labs & Teams: Directs the Waterloo Intelligent Systems Engineering Lab, focusing on AI-driven solutions for autonomous systems and safety-critical software. Active in cross-disciplinary collaborations with automotive and robotics partners.

Yaguang Zhangمشاهده پروفایل

استادیار بالینی

• Data Science
• Digital Agriculture
• UAV-Aided Wireless Communication Systems
• +۴ مورد دیگر

Dr. Yaguang Zhang is a Clinical Assistant Professor at Purdue University, jointly appointed in the Department of Agricultural & Biological Engineering (ABE) and the Department of Agricultural Sciences Education & Communication (ASEC) . Holding a Ph.D. in Electrical and Computer Engineering from Purdue (2021), he specializes in data science , digital agriculture , and UAV-aided wireless communication systems , with applications in intelligent transportation, proactive road maintenance, and engineering education. Education: Ph.D. and M.Sc. in Electrical and Computer Engineering (Purdue), B.Eng. in Communication Engineering (Tianjin University) Research Interests span cutting-edge domains including: Digital Agriculture: GPS-based field shape generation, product traceability trees, and automated metadata collection for agricultural operations Wireless Communication: Millimeter-wave channel modeling, UAV relay systems, and rural network coverage optimization Smart Infrastructure: Pavement condition assessment tools, sun-shadow simulation for road treatment, and vehicle automation platforms Recent Publications emphasize scalable solutions for agricultural IoT, machine learning in crop monitoring, and interoperable data frameworks. His scientific awards include: 2024 Outstanding Engineering Teacher (Purdue) 2024 ASABE Superior Paper Award 2020 FFAR Student Poster First Prize Multiple NSF/IEEE travel supports Grants from USDA, NSF, INDOT, and industry partners (CableLabs, Nokia) fund projects like tractor autopilot development, rural 6G networks, and pavement monitoring systems. He mentors graduate students in agricultural robotics , data science , and connected vehicle research .

John Dolanمشاهده پروفایل

استاد

• Robotics
• Autonomous Driving
• Human-Robot Interaction
• +۴ مورد دیگر

John Dolan is a Courtesy Professor in the Department of Electrical and Computer Engineering and a Senior Systems Scientist at the Robotics Institute of Carnegie Mellon University. He works in 3109 Newell-Simon Hall and focuses on creating systems that enable collaboration between robots and humans for practical tasks.

• Computer Vision
• 3D Reconstruction
• Perceptual Information Processing
• +۷ مورد دیگر

SATO Jun holds the position of Professor at the Department of Information Engineering (メディア情報分野) within the Faculty of Engineering at Nagoya Institute of Technology. He received his Ph.D. in Information Engineering from the University of Cambridge (1993–1996) and previously served as a Research Assistant at Cambridge (1996–1998). His research focuses on perceptual information processing and intelligent informatics, with specializations in computer vision, 3D reconstruction, and optical engineering applications. He has authored influential books like Computer Vision - Geometry of Vision (1999) and Computer Graphics (2017), and contributed to international publications such as Springer's Computer Vision: A Reference Guide (2020). Key professional roles include serving as President of the IEEE Nagoya Branch since 2023, Associate Editor of the International Journal of Computer Vision (Springer, 2010–present), and committee member for various organizations including Japan's Ministry of Education (2015–present) and the Nagoya City Business Potential Evaluation Committee (2008–2015). He has been recognized with prestigious awards including the BMVC Best Science Paper Prize (1994, 1997) and ITE Niwa-Takayanagi Prize (2015). His research extends to industrial collaborations, evidenced by patents like the "3D Information Presentation Device" (2014–2017) and "Position Detecting Device" (2016–2019). Recent work emphasizes applications in automotive safety, occluded object reconstruction, and novel imaging systems using advanced optical configurations and neural networks.

Mecit Cetinمشاهده پروفایل

استاد

• Intelligent Transportation Systems
• Traffic Flow Theory
• Connected and Automated Vehicles
• +۴ مورد دیگر

Dr. Mecit Cetin is a Professor at Old Dominion University (ODU) and Director of the Transportation Research Institute (TRI). He specializes in Intelligent Transportation Systems (ITS), connected/automated vehicles, traffic flow theory, and infrastructure resilience. His academic background includes a Ph.D. in Transportation Engineering from Rensselaer Polytechnic Institute (2002), an M.S. in Civil Engineering (1999), and a B.S. from Boğaziçi University (1995). Research focuses on big data analytics for traffic prediction, congestion pricing, and floodwater detection using LIDAR and computer vision. He has secured over $3M in grants including Federal funding for SMARTc systems and state projects on truck turnaround reduction. Notable awards include the 2011 Best Paper Award at the World Congress on Intelligent Transport Systems and multiple Shining Star Awards from ODU. Key projects include developing auction-based tolling systems for connected vehicles, enhancing traffic signal control with probe data, and modeling secondary incident impacts. His work bridges transportation engineering with emerging technologies like IoT and AI. Dr. Cetin collaborates with state agencies (VDOT) and institutions like EVMS. His lab develops tools for urban flood monitoring, eco-routing algorithms, and safety service patrol optimization using discrete-event simulation.

Symeon Papavassiliouمشاهده پروفایل

استاد

• Computer Networks
• Wireless Networks
• Complex Networks
• +۷ مورد دیگر

Symeon Papavassiliou is a Professor at the Department of Communications, Electronics and Information Systems, School of Electrical and Computer Engineering, National Technical University of Athens since 2004. Previously held positions include Associate Professor at New Jersey Institute of Technology (1996-2004) and senior researcher at AT&T Labs (1995-1999). He leads the Network Management and Optimal Design Laboratory and has served in various academic leadership roles, including Deputy Director since 2005. His research focuses on computer networks, wireless systems, and AI-driven network management with over 400 publications. Recognized with multiple best paper awards and NSF Career Award (2003). Education: B.A. Electrical Engineering, NTUA (1990) MSc & PhD Electrical Engineering, Polytechnic University, NY (1992/1996) Key Roles: Founder, New Jersey Center for Wireless Networks & Internet Security Member, EETT (National Telecommunications Commission) 2006-2009 Editorial Board Member, multiple journals Research Interests: Specializes in mobile/distributed systems optimization, wireless networks, complex systems, IoT, and AI applications in network management. Active in 6G architecture research, edge computing orchestration, and secure federated learning frameworks. Publications highlight innovations in network resource allocation, game theory models for positioning systems, and symbiotic computing continuum architectures. Recent work emphasizes resilience in critical infrastructure and smart grid optimization. Awards: Over 10 best paper awards from IEEE conferences, AT&T recognition, and Greek Excellence in Research Grant (2012). Grants: Funded by EU Framework Programs, NSF, ESA, and industry partners like Panasonic and Northrop Grumman. Leads interdisciplinary projects like HEROES (UAV-based emergency response) and NEPHELE (multi-cloud ecosystems). Active in digital twin development for cultural heritage preservation and SDG tracking via knowledge graphs.

• Control Engineering
• Automation
• Model Predictive Control
• +۵ مورد دیگر

Martin Steinberger is an Associate Professor at the Institute of Control and Automation (IRT) at Graz University of Technology (TU Graz). His work focuses on advanced control systems, networked control, model predictive control (MPC), and automation in manufacturing and autonomous systems. He leads research into real-time optimization, fault diagnosis, and safety-critical applications in industries like pharmaceuticals and automotive. Research interests include: Networked Control Systems Model-Based Control Autonomous Vehicle Trajectory Planning Process Automation Robotics and Industrial Automation His work bridges theoretical control engineering with practical applications in manufacturing lines, chemical processes, and autonomous driving. Recent studies emphasize digital real-time release testing for pharmaceuticals, universal control concepts for manufacturing systems, and safety-aware trajectory optimization for automated vehicles. His publications frequently address challenges in time-varying delays, packet loss mitigation, and robust observer design for nonlinear systems. Steinberger collaborates on EU-funded projects and regularly contributes to conferences like the International Workshop on Variable Structure Systems. His research often involves experimental validation, as seen in work with compact pharmaceutical manufacturing setups and small-scale autonomous vehicle testing platforms.

Chunming Qiaoمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Optical Networks
• Wireless Networks
• +۶ مورد دیگر

Dr. Chunming Qiao is a SUNY Distinguished Professor and Chair of the Department of Computer Science and Engineering at the University at Buffalo (SUNY) , leading the Lab for Advanced Network Design, Evaluation and Research (LANDR) since 1993. His work spans cyber-physical systems , optical networks , and Internet of Things (IoT) , with a focus on safety, reliability, and protocol design. Education: PhD in Computer Science from the University of Pittsburgh (1993) BS in Computer Science and Engineering from the University of Science and Technology of China (1985) Dr. Qiao’s research interests combine theoretical and applied network design, including autonomous vehicles , quantum computing , and cloud services . He pioneered optical burst switching (OBS) and iCAR systems for wireless convergence, cited in BusinessWeek and Wireless Europe . His recent publications emphasize quantum networking , federated learning , and autonomous driving security , with projects on entanglement routing , edge inference optimization , and LiDAR adversarial attacks . Articles span IEEE and ACM venues , and include best paper awards . Scientific Awards: TC-CSR Distinguished Technical Achievement Award (2015) SUNY Chancellor's Award for Excellence (2013) IEEE Fellow (2009) UB Exceptional Scholar-Sustained Achievement Award (2005) Dr. Qiao has secured over two dozen NSF grants and collaborations with Google , Cisco , and NEC Labs . His 7 US patents and consulting experience highlight his industry impact, while his editorial roles and conference leadership underscore academic influence. He actively contributes to multi-disciplinary research through the New York State Center of Excellence in Bioinformatics and Life Sciences and CEDAR , advancing high-performance computing and document analysis .

Jakob PUCHINGERمشاهده پروفایل

استاد

• Logistics
• Urban Mobility
• Disruptive Technologies
• +۳ مورد دیگر

Jakob Puchinger is a Professor in Supply Chain Management and Logistics at EM Normandie since 2022. He also serves as an affiliate professor at the Laboratoire Génie Industriel at CentraleSupélec, Université Paris-Saclay, and co-director of the Future Cities Lab with Centrale Pékin. He holds a PhD in Computer Science from TU Wien (2006), focusing on metaheuristics and integer programming for cutting and packing problems. His research spans logistics, urban mobility, disruptive technologies, and transport system optimization. Professional roles include Head of the Operations Management team at CentraleSupélec (2019–present), holder of the Anthropolis Chair at IRT SystemX (2015–2022), and scientist at the Austrian Institute of Technology (2008–2014). He has authored over 80 publications and supervised six theses, with five ongoing. Research interests emphasize sustainable urban logistics, last-mile delivery optimization, and shared mobility systems. Key contributions include studies on electric vehicles, autonomous systems, and policy frameworks for decarbonization. His work integrates optimization algorithms, agent-based modeling, and real-world case studies to address complex mobility challenges. Recent publications focus on route optimization for cold chain logistics, decarbonization policies, and collaborative truck-robot delivery systems. He actively contributes to conferences like Transportation Research Board and ROADEF, and co-authored books on urban mobility futures and robomobility revolution.

• Artificial Intelligence
• Machine Learning
• Spatial Reasoning
• +۳ مورد دیگر

Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.

Pedro Nardelliمشاهده پروفایل

استاد

• Cyber-physical Systems
• IoT in Energy Systems
• Smart Grids
• +۵ مورد دیگر

Pedro Nardelli is a Full Professor (tenured) of IoT in Energy Systems at the LUT School of Energy Systems, Lappeenranta University of Technology (Finland). He holds a double doctoral degree in electrical engineering from the University of Campinas (Brazil) and communications engineering from the University of Oulu (Finland). As a Docent in Information Processing and Communications Strategies for Energy Systems, he leads research in cyber-physical systems, smart grids, and 6G-enabled energy networks. Research Interests : His work focuses on integrating IoT, AI, and communication technologies into energy systems. Key areas include cyber-physical systems, UAV-enabled networks, sustainable energy management, and cybersecurity in critical infrastructure. He emphasizes interdisciplinary approaches to address challenges in the green-digital transition. Projects & Leadership : He is Principal Investigator for projects such as 'Energy-Conscious Operation: Network Efficiency for Wireless Sustainability' (2024–2026) and coordinates the Finnish-Brazilian AI and 5G training program. Past roles include leadership in the 'Hydrogen and Carbon Value Chains in Green Electrification' initiative (2021–2024). Publications : Recent work explores topics like hybrid optimal power flow models, UAV-IRS NOMA systems, and energy-centric analysis. His research bridges theoretical frameworks with practical applications, emphasizing sustainability and resilience in energy networks. Labs & Teams : Leads the IoT Solutions group within LUT's MORE SIM research platform, focusing on simulation-driven innovation for energy systems.