جستجوی استاد راهنمای دانشگاهی

Jamey Jacob, Ph.D., P.E., is a Professor and John Hendrix Chair in Mechanical and Aerospace Engineering at Oklahoma State University, leading the Oklahoma Applied Research Institute (OAIRE). He holds a Ph.D. from UC Berkeley (1995), with earlier degrees from the same institution and the University of Oklahoma. His research focuses on aerodynamics, UAV design, vortex dynamics, geophysical flows, and autonomous systems. Notable projects include solar balloon flight dynamics, eclipse observations, and advanced air mobility (AAM) weather systems. Jacob has pioneered UAV-based weather sensing and developed innovative aerostructures, including inflatable systems. He has received over 15 prestigious awards, including the Regents Distinguished Teacher (2011) and Oklahoma Innovator of the Year (2010). His recent work emphasizes urban wind field mapping and stratospheric balloon applications for planetary science. Jacob’s lab, OAIRE, integrates aerospace engineering with environmental and operational challenges, advancing both academic and applied frontiers.

• Aerodynamics
• UAV Design & Flight Testing
• Vortex Dynamics
• +۵ مورد دیگر

Dr. Zhong-Ping Jiang is a Professor in the Department of Electrical and Computer Engineering and an Affiliate Professor in the Department of Civil and Urban Engineering at the Tandon School of Engineering, New York University. He has been with NYU since 2007, previously serving as Associate Professor (2002-2007) and Assistant Professor (1999-2002) at Polytechnic University (now part of NYU). Dr. Jiang received his MSc degree in Statistics from the University of Paris XI in 1989 and his PhD degree in Automatic Control and Mathematics from the Ecole des Mines de Paris in 1993. He has maintained strong international collaborations with researchers across Europe throughout his career. Internationally recognized as a key contributor to nonlinear small-gain theory, Dr. Jiang is also well-known for his seminal work in robust adaptive dynamic programming and robust reinforcement learning for real-time safety-critical control applications. His research spans dynamical networks, nonlinear control theory, data-driven optimization, and reinforcement learning with applications to mechanical, information and biological systems. Dr. Jiang's publications have had significant impact in the field, with over 500 peer-reviewed journal and conference papers, more than 34,300 citations, and an h-index of 90 on Google Scholar. He has also published six research monographs since 2011. His notable awards and honors include: Election to European Academy of Sciences and Arts (2023) Stanford's Top 2% Most Highly Cited Scientists (2023) Election to Academia Europaea (2021) Highly Cited Researchers by Clarivate Analytics (2018) Fellow of Chinese Association of Automation (2017) Fellow of International Federation of Automatic Control (2013) Fellow of IEEE (2008) National Distinguished Professor, Chinese Ministry of Education (2009) Dr. Jiang serves as Deputy Editor-in-Chief for the IEEE/CAA Journal of Automatica Sinica and has held editorial positions for numerous prestigious journals including IEEE Transactions on Automatic Control. He has delivered more than 20 plenary, semi-plenary and keynote speeches at major international conferences and workshops.

• Nonlinear Control Theory
• Dynamical Networks
• Data-Driven Optimization
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William (Bill) Eisele serves as a Senior Research Engineer and Program Manager at Texas A&M University's Department of Landscape Architecture & Urban Planning. His work focuses on transportation systems, freight mobility, and urban development impacts. Eisele holds a Ph.D. (Civil Engineering, Texas A&M, 2001), M.S. (Civil Engineering, Michigan State, 1994), and B.S. (Civil Engineering, Michigan State, 1993). Research Interests: Dr. Eisele’s expertise spans Transportation planning and access management, Freight mobility optimization, Congestion monitoring, Transportation system performance measurement, Urban land development impacts, Sustainable infrastructure design. Recent Work Trends: His publications emphasize data-driven solutions for freight challenges, including truck parking behavior, cargo consolidation, and port fluidity. Recent studies apply machine learning to predict driver route choices and evaluate real-time mobility tools. He also explores historical trends in urban freight logistics to guide future innovations. Grants & Advising: While no specific grants or advisees are listed, his extensive publications reflect collaborative work with institutions like the Texas A&M Transportation Institute. He has contributed to statewide programs like Oregon’s operations performance measures and Maryland’s freight fluidity initiatives. Labs/Teams: His affiliations suggest involvement with interdisciplinary teams focusing on transportation systems, though specific lab names are not mentioned in the source text.

• Transportation Planning
• Access Management
• Urban Development Impacts
• +۴ مورد دیگر

Professor Zhifeng Bao is a faculty member at RMIT University's School of Computing Technologies. His research focuses on enhancing data usability across heterogeneous domains, including structured, unstructured, and spatial-temporal data. His work spans database management, keyword search optimization, social network analysis, and spatio-textual data processing. He coordinates the course COSC1169: Intranet and Internet Data Engineering and supervises PhD/Masters students in projects such as trajectory data processing, data asset valuation, and edge computing optimization. Research interests emphasize improving data accessibility and efficiency through methodologies like query relaxation, visual analytics, and provenance tracking. His recent projects include cost-effective edge node placement, traffic accident risk prediction, and differentially private federated learning. Teaching and supervision activities highlight a commitment to bridging theory and practical data engineering challenges.

• Database Management
• Spatial-Textual Data Processing
• Heterogeneous Data Usability
• +۶ مورد دیگر

Erdem Coleri is an Associate Professor at Oregon State University's College of Engineering, Department of Civil and Construction Engineering. He joined OSU in 2014 after postdoctoral work at the University of California Pavement Research Center. His research focuses on sustainable pavement materials, energy-efficient design, and infrastructure health monitoring using wireless sensor networks. He directs the OSU Asphalt Materials and Pavements (AMaP) Lab, emphasizing recycled materials and pavement sustainability. Education: Ph.D., Civil and Environmental Engineering (UC Davis, 2011); M.S. and B.S., Civil Engineering (Middle East Technical University, Turkey). Research interests include asphalt characterization, pavement management systems, and wireless sensor networks for infrastructure monitoring. Notable awards include the John and Jean Loosley Faculty Fellow (2015) and Oregon State University Teaching Excellence (2020). He advises students like David Covey and Aiman Mahmoud, focusing on tack coat performance and recycled materials. His lab develops technologies to reduce environmental impact and improve pavement longevity. Key projects include the AMaP Lab's work on permeable pavements, warm-mix asphalt, and energy-efficient designs. He collaborates with ODOT and agencies on field tests and sensor systems. Recent publications address balanced mix design, recycled materials, and fuel efficiency linked to pavement roughness.

• Sustainable Pavement Materials
• Energy-Efficient Pavement Design
• Infrastructure Health Monitoring
• +۳ مورد دیگر

Dr. Xiang Sun is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM). He holds a Ph.D. in Electrical Engineering from New Jersey Institute of Technology (2018), and M.E. and B.E. degrees from Hebei University of Engineering (2011 and 2008). His research focuses on Mobile Edge Computing, IoT, Drone-assisted Networks, Green Computing, and Data Center Optimization. Dr. Sun has been recognized with awards such as the 2018 InterDigital Innovation Award and NJIT Hashimoto Prize. Education: Ph.D., Electrical Engineering, NJIT (2018) M.E., Computer Applications Technology, Hebei University (2011) B.E., Electronic Information, Hebei University (2008) Research Interests: His work emphasizes IoT resource caching, semantic discovery, green communications, and drone-based mobile access networks. He also explores machine learning applications in edge computing and cybersecurity. Publications & Contributions: Dr. Sun has authored over 40 journal/conference papers, including impactful work on cloudlet networks and IoT semantic mashup. His research has been published in IEEE Transactions, Communications Letters, and top-tier conferences like ICC and GLOBECOM. Awards: 2018 InterDigital Innovation Award 2018 NJIT Hashimoto Prize 2017 IEEE Communications Letters Exemplary Reviewer 2016 IEEE ICC Best Paper Award Professional Activities: He serves as a TPC member for IEEE CCNC and MobiEdge, and reviewer for top journals like IEEE Transactions on Cloud Computing and IEEE Internet of Things Journal. He co-chairs the Social Computing and Semantic Data Mining symposium at IEEE ICNC 2019. Labs & Teams: Active in UNM's Electrical & Computer Engineering labs, focusing on mobile edge computing and IoT innovation. Collaborates with industry partners like InterDigital Communications.

• Mobile Edge Computing
• Internet of Things (IoT)
• Drone-assisted Mobile Access Networks
• +۵ مورد دیگر

Dr. Selçuk Uluağaç is an Eminent Scholar Chaired Associate Professor at Florida International University (FIU), leading the Cyber-Physical Systems Security Lab. He holds a courtesy appointment in the Knight Foundation School of Computing and Information Science. Previously, he worked at Georgia Tech and Symantec, with degrees from Georgia Tech (PhD) and Carnegie Mellon University (MS). His research focuses on cybersecurity, privacy, and IoT/CPS systems, funded by NSF, DOE, and industry partners exceeding $18M. He has authored hundreds of publications, secured 17 patents (one licensed), and serves on editorial boards of IEEE journals. Education: PhD in Electrical and Computer Engineering, Georgia Institute of Technology (200X); MS in Computer Science, Carnegie Mellon University (200X). Research Interests: Developing security frameworks for IoT devices, privacy-preserving techniques, machine learning for cybersecurity, and CPS threat mitigation. Notable projects include sensory channel threat analysis, IoT fingerprinting, encrypted traffic privacy leakage detection, wearable-based authentication, and cryptomining activity detection. Awards: Recognized with prestigious NSF CAREER Award and multiple institutional awards for research and teaching excellence. Active in professional service, including conference chairs (ACM WiSec 2019, IEEE CNS 2022 TPC Chair) and NIST panels. Grants & Funding: Over $18M from NSF, DoE, US Air Force, Google, Microsoft, and Cisco. Entrepreneurial focus with patents commercialized. Labs & Teams: Directs the Cyber-Physical Systems Security Lab, collaborating on applied security solutions. Media-featured research highlights societal cybersecurity impacts.

• Cybersecurity
• Privacy Engineering
• Internet of Things (IoT)
• +۳ مورد دیگر

Erdinç Altuğ serves as a Professor in the Department of Mechanical Engineering at Istanbul Technical University, specializing in advanced aerial robotics and control systems. His work bridges theoretical control methodologies with practical UAV applications. Research interests focus on Unmanned Aerial Vehicle design and fault tolerance Quadcopter dynamics and vertical takeoff systems Adaptive control for parametric variations Rapid prototyping of hybrid VTOL platforms His recent publications demonstrate consistent innovation in autonomous flight systems, particularly in fault-tolerant operational modal analysis and modular multi-drone configurations. Current projects include: Hibrit İnsansız Hava Aracı Ile Otonom Teslimat Sistemi Geliştirilmesi (TUBITAK, 2020-2022) Mini Jet Motorlu Dikine Kalkıp İnebilen Otonom Taşıyıcı Robot Geliştirilmesi (TUBITAK, 2018-2021) Kampüs içi ve bina içi ortamlarda çalışacak otonom taşıma aracı algoritmaları (SRP, 2018-2021) Supervising 26 graduate works, his research impacts both academic and industrial UAV development.

• Unmanned Aerial Vehicles (UAVs)
• Quadcopter Design
• Flight Control Systems
• +۵ مورد دیگر

Diala Naboulsi is a Professor at the École de technologie supérieure (ÉTS) in the Department of Software Engineering and IT. Her research focuses on mobile networks, wireless systems, and cybersecurity, with a strong emphasis on machine learning applications in network optimization. She holds an M.Eng. from the Lebanese University and M.Sc. and Ph.D. degrees from INSA Lyon. Research Units: Summit Tech Research Chair, LASI Lab, Imagin Lab Expertise: Network virtualization, resource allocation, mobility management, UAV-based computing Her work spans resilience in wireless backhaul networks, energy-efficient frameworks in RAN slicing, and federated learning for privacy-aware traffic forecasting. She has advised numerous doctoral students, including Ahmed Abdelmoaty, Hnin Pann Phyu, and Philippe Lavoie. Key contributions include deep reinforcement learning approaches for network topology optimization and UAV-assisted MEC systems for Industry 5.0. Recent publications highlight advancements in 6G networks, network slicing, and edge computing. Her research aligns with strategic initiatives in sustainable and secure communication systems.

• Mobile networks
• Wireless networks
• Network virtualization
• +۷ مورد دیگر

F. Richard Yu is a Professor at the School of Information Technology , Carleton University , Canada, since 2016. He served as Assistant/Associate Professor at the same institution from 2006 to 2015. His academic work spans machine learning, blockchain, autonomous vehicles, and network security. Ph.D., Electrical Engineering, University of British Columbia (2003) M.A.Sc., Computer Engineering, Beijing University of Posts & Telecomm. (1998) B.A.Sc., Electrical Engineering, Dalian University of Technology (1995) His research focuses on machine learning , blockchain , autonomous vehicles , network security , and mobile wireless networks . Trends in his publications include deep reinforcement learning for computation offloading , blockchain applications in edge computing , and network optimization for IoT and 5G systems . Highly Cited Researcher (2019-2023), Clarivate Electronics and Electrical Engineering Leader in Canada (2023), Research.com Fellow of Canadian Academy of Engineering (CAE) (2021), Engineering Institute of Canada (EIC) (2019), IEEE (2017), and IET (2016) Best Paper Awards: IEEE ICC (2022), IEEE GLOBECOM (2020), IEEE VTC (2017), IEEE TAOS (2012), IEEE TrustCom (2009) Research Achievement Award, Carleton University (2021, 2012) Early Researcher Award (2011), Ontario; Leadership Opportunity Fund Award (2009), Canada Foundation for Innovation His work has resulted in 800+ papers , 30 patents , and 48,000+ citations (H-index 107), with grants including the 2009 Canada Foundation for Innovation award.

• Machine learning and artificial intelligence
• Connected and autonomous vehicles
• Blockchain and distributed ledger technology
• +۲ مورد دیگر

Alex X. Liu is a Professor in the Department of Computer Science & Engineering at Michigan State University (2016-2022), currently serving as Chief Information Security Officer and President of Midea Software Engineering Institute. His academic career includes roles as Associate Professor (2012-2016) and Assistant Professor (2006-2012) at the same institution. He holds a Ph.D. and M.S. in Computer Science from The University of Texas at Austin, and a B.S. in Computer Science from Jilin University, China. Education Ph.D. in Computer Science (UT Austin, 2006) M.S. in Computer Science (UT Austin, 2002) B.S. in Computer Science (Jilin University, 1996) Liu's research focuses on Dependable computing , Networking algorithms , Cloud computing , Mobile computing , Privacy computing , and Computer/network security . His work spans secure systems, network protocols, and resource optimization in distributed environments. Recent publications address quantum neural networks , microservices autoscaling , RFID tag recognition , network traffic classification , and hybrid physical-layer authentication , demonstrating expertise at the intersection of AI and network security. Key trends include deep learning applications for cloud systems and robust security protocols. Scientific Awards IET Fellow (2021) IEEE Fellow (2019) ACM Distinguished Scientist (2019) Withrow Distinguished Scholar Awards (Senior 2019, Junior 2011) NSF CAREER Award (2009) IEEE & IFIP William C. Carter Award (2004)

• Dependable computing
• Networking algorithms
• Cloud computing
• +۳ مورد دیگر

Shaurya Agarwal is an Associate Professor in the Department of Civil, Environmental, and Construction Engineering at the University of Central Florida (UCF), where he has been a faculty member since 2018. He is the founding director of the URBANITY Lab (Urban Intelligence and Smart City Lab) and currently serves as the director of the Future City Initiative. Prior to joining UCF, he was an Assistant Professor in the Electrical and Computer Engineering Department at California State University, Los Angeles (2016–2018). Ph.D. in Electrical Engineering, University of Nevada, Las Vegas (2015) Postdoctoral Research, New York University (2016) B.Tech. in Electronics and Communication Engineering, Indian Institute of Technology (IIT), Guwahati Dr. Agarwal's research lies at the intersection of cyber-physical systems, intelligent transportation systems, and smart cities. He employs interdisciplinary methodologies integrating control theory, data-driven techniques, physics-informed machine learning, and mathematical modeling to address challenges in connected and autonomous mobility. His work emphasizes real-world applications such as traffic state estimation, signal-free intersections, and pedestrian safety using LiDAR perception. His recent publications demonstrate a strong trend in applying physics-informed deep learning and Koopman operator theory to model complex traffic dynamics. These works leverage both Lagrangian and Eulerian data frameworks and aim to improve accuracy under sparse sensor conditions. The research spans transportation, public health, and social systems, indicating a broad interdisciplinary impact. Dr. Agarwal is a senior member of IEEE and serves as an Associate Editor for IEEE Transactions on Intelligent Transportation Systems . His research has been funded by agencies including the Federal Highway Administration (FHWA), Florida Department of Transportation (FDOT), and Oculus. Senior Member, IEEE Associate Editor, IEEE Transactions on Intelligent Transportation Systems He actively mentors Ph.D. students in the Civil, Environmental, and Construction Engineering Department and leads the URBANITY Lab, a research team focused on next-generation urban mobility solutions. The lab develops real-time 3D object detection algorithms, operates a small-scale CAV test-bed, and explores hybrid approaches bridging theory, simulation, and practice.

• Cyber-Physical Systems
• Intelligent Transportation Systems
• Smart Cities
• +۷ مورد دیگر

Anna Brunström is a Full Professor and Head of the Distributed Intelligent Systems and Communications Research Group (DISCO) at Karlstad University's Department of Computer Science. She holds a part-time role as a Researcher at the University of Malaga's Institute of Software Engineering and Technologies (ITIS). Her research focuses on computer networking, Internet architectures, low latency communication, and 5G/6G mobile systems. She leads the nationally funded DRIVE initiative and collaborates on European projects like 6G-PATH. She actively contributes to IETF standardization, notably as a former rmcat WG chair. Her work spans over 200 publications, emphasizing network measurement, latency optimization, and multipath protocols. Education: Ph.D. (1996) and M.Sc. (1993) from College of William & Mary, B.Sc. (1991) from Pepperdine University. Research Interests: Distributed systems, IoT networking (NB-IoT), satellite communication (Starlink), machine learning for positioning, and transport protocols (QUIC, MPTCP). Recent work includes latency-aware scheduling, 5G/6G performance analysis, and edge computing frameworks. Publications highlight trends in: 1) Satellite network throughput modeling, 2) 5G/6G architecture validation, 3) Machine learning applications for positioning and network analysis, 4) Cross-layer optimization of latency-critical services. Collaborations with industry and academia drive applied research in smart grids, healthcare, and automotive communication. Labs/Teams: DISCO group at Karlstad University, leading the DRIVE research profile and 6G-PATH consortium involvement.

• Computer Networking
• Internet Architectures
• 5G/6G Mobile Systems
• +۳ مورد دیگر

Prof. Constantinos Antoniou is a Full Professor in the Chair of Transportation Systems Engineering at the Technical University of Munich (TUM), part of the TUM School of Engineering and Design. He holds a Diploma in Civil Engineering from the National Technical University of Athens (1995), an MS in Transportation (1997), and a PhD in Transportation Systems (2004) from MIT. His research focuses on transportation systems engineering, including modeling/simulation, intelligent transport systems (ITS), behavioral economics in transport, road safety, and sustainable transport systems. He has authored over 500 scientific publications, including over 210 peer-reviewed journal papers, and serves as Co-Editor-in-Chief of Transportation Research Part A . Awards include the Francquis Chair (2023), IEEE ITS Outstanding Application Award (2011), and Marie Curie Fellowship (2006–2008). He has secured over €4M in third-party funding, leading projects such as SCUDO, CulturalRoad, and PHOEBE. Currently supervising 17 PhD students, he has mentored seven graduates who now hold academic positions at institutions like UCL and UPC. Research interests span autonomous vehicles, traffic resilience, and policy-driven transport solutions. Key projects include analyzing urban air mobility, MaaS potential, and pandemic impact on transport networks. His work contributes to UN Sustainable Development Goals, emphasizing sustainable cities and communities.

• Transportation Systems Engineering
• Intelligent Transport Systems (ITS)
• Behavioral Economics in Transport
• +۵ مورد دیگر

Rakotonirainy Andry is a Professor at Queensland University of Technology (QUT), affiliated with the Centre for Accident Research & Road Safety - Queensland (CARRS-Q). His research focuses on transportation safety, automated vehicles, human factors, and intelligent transportation systems (ITS). He leads interdisciplinary projects exploring driver behavior, connected vehicle technologies, and the societal impacts of automation. Key areas include accident prevention, human-vehicle interaction, and equity in transport systems. His work integrates machine learning, simulation studies, and behavioral analysis to address challenges in road safety. Notable contributions include studies on driver stress detection, automated vehicle acceptance, and the Australian Naturalistic Driving Study (ANDS). He collaborates with institutions globally, advancing innovations like connected vehicle pilots and multimodal AI for traffic safety. Research interests span automated driving systems, vulnerable road user protection, and policy implications of emerging technologies. His findings contribute to safer transportation policies and technologies, emphasizing both technical and human-centric perspectives.

• Transportation Safety
• Automated Vehicles
• Human Factors in Transportation
• +۳ مورد دیگر