جست‌وجوی استاد و پژوهشگر

• Cybersecurity
• AI/Machine Learning
• Wireless Networking
• +۹ مورد دیگر

Dr. Danda B. Rawat is an Associate Dean for Research & Graduate Studies and Full Professor in the Department of Electrical Engineering & Computer Science at Howard University's College of Engineering and Architecture (CEA). He leads several initiatives, including the Howard University Data Science & Cybersecurity Center and the DoD Center of Excellence in AI/ML. His research focuses on cybersecurity, machine learning, and wireless networking for emerging systems like IoT, smart cities, and tactical autonomy. Dr. Rawat has secured over $110M in research funding and graduated 39 PhD students, many from underrepresented groups. He holds numerous awards, including the NSF CAREER Award and DHS Scientific Leadership Award. Education : PhD in Computer Science from Old Dominion University. Research Interests : Cybersecurity, AI/ML, wireless networking, tactical autonomy, federated learning, and quantum computing. His work addresses challenges in secure autonomous systems, edge intelligence, and ethical AI. Awards : Includes NSF CAREER, DHS Leadership Award, Presidents’ Medal (Howard University), and IEEE recognitions. He is a Fellow of the IET and ACM/IEEE Distinguished Lecturer. Labs & Teams : Directs the CWiNs Lab, DoD CoE-AIML, and RITA (UARC). Active in federal consortia linking HBCUs to defense innovation. Grants : Over $110M as PI, including a historic $90M USAF contract for RITA, the first HBCU-led UARC.

Giancarlo Fortinoمشاهده پروفایل

استاد

• Internet of Things
• Wearable Computing
• Distributed Systems
• +۲ مورد دیگر

Giancarlo Fortino is a Full Professor of Computer Engineering at the University of Calabria, where he directs the SPEME lab and serves as Rector's delegate to International Relations. He holds a PhD in Computer Engineering from the University of Calabria and has held distinguished positions at Wuhan University of Technology and Huazhong Agricultural University. His research spans wearable computing systems, Internet of Things, e-Health, and distributed systems. He leads development of open-source frameworks including SPINE for body sensor networks and BodyCloud for cloud-assisted healthcare systems. His work consistently addresses real-world challenges in IoT and edge computing. Professor Fortino has received numerous honors including IEEE Fellow (2022), Highly Cited Researcher recognition (2020-2022), and best paper awards at premier conferences. He has authored over 600 publications and leads multiple EU-funded projects on IoT systems. He co-founded SenSysCal and BigTech spin-offs, serves on editorial boards of premier journals, and has graduated 10 PhD students who now hold academic and industry positions worldwide.

Riccardo Cantiniمشاهده پروفایل

استادیار

• Deep Learning
• Large Language Models
• Sustainable AI
• +۳ مورد دیگر

Riccardo Cantini is an Assistant Professor (RTDA) at the Department of Computer Science, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria. He holds a European Ph.D. in Information and Communication Technologies (2023) and has been a visiting researcher at the Barcelona Supercomputing Center (BSC-CNS, 2021-2022). His research focuses on deep learning (Large Language Models, sustainable AI) and big social data analysis targeting politically polarized data and high-performance distributed systems. Education: B.Sc. (2016), M.Sc. (2019), and Ph.D. (2023) in Computer Engineering from the University of Calabria. Research interests include: Large Language Models and their ethical deployment Sustainable AI and energy-efficient edge computing Political polarization analysis using social media data Optimization of data-intensive workflows in distributed environments Key projects include the FAIR initiative (Green-Aware AI), eFlows4HPC (HPC workflows), and ASPIDE (Exascale data processing). He has authored/co-authored over 30 publications, including works on bias detection in LLMs and explainable AI in healthcare. Awards: 2024 Top 3 Best PhD Thesis in Big Data & Data Science (CINI), 2022 Editor's Choice article in Big Data and Cognitive Computing . Teaching roles include courses on Business Intelligence, High-Performance Computing, and Operating Systems. He has advised over 40 theses in AI, NLP, and big data. Professional services: Guest Editor for Big Data and Cognitive Computing , Program Chair of Green-Aware AI workshops, and reviewer for top journals/conferences (ICLR, IEEE BigData, etc.).

• BioHealth Informatics
• Innovation
• Protein Electrodynamics
• +۳ مورد دیگر

Dr. Ogan Gurel is an interdisciplinary academic holding adjunct professorships in Bioengineering (College of Engineering), Kinesiology (College of Nursing & Health Innovation), Management (College of Business), and Philosophy & Humanities (College of Liberal Arts) at the University of Texas at Arlington. His career spans medicine, industry, and academia, with prior roles at institutions like Columbia University, Harvard, and Samsung. He earned an MD from Columbia University, an M.Phil in Structural Biology, and a Harvard AB in Biochemical Sciences. His research focuses on innovation, protein electrodynamics, medical literacy, and information design, emphasizing interdisciplinary approaches. He has authored 14 peer-reviewed papers, a novel, and holds patents in biomedical engineering. Dr. Gurel’s teaching includes courses on innovation, bioelectromagnetics, and medical literacy, and he advises students on projects like 'Measuring Innovation' and 'The Logical Structure of Psychiatry'. He has also contributed to humanitarian efforts in medical relief following disasters. Education: MD, Columbia University College of Physicians & Surgeons (1996) M.Phil in Structural Biology, Columbia University (1991) AB in Biochemical Sciences, Harvard University (1986) Research Focus: Combining sciences and humanities to drive innovation. Key areas include THz medicine, protein dynamics, medical literacy enhancement, and information design. His work bridges fields like cognitive science, philosophy, and electrical engineering. Teaching & Service: Recent courses include 'Fundamentals & Practice of Innovation' and 'Principles of Bioelectromagnetics'. He serves as a judge in university research showcases and has organized interdisciplinary conferences. Inventions & Recognition: Co-inventor on 10 patent applications (4 granted), including microfluidics and THz imaging technologies. His novel Waves explores intersections of science and art.

Fuxin Huangمشاهده پروفایل

عضو هیئت علمی

• Ship Design and Optimization
• Hydrodynamics
• Computational Fluid Dynamics
• +۳ مورد دیگر

Fuxin Huang holds the position of Research Assistant Professor in the Physics & Astronomy Department at George Mason University. His work focuses on computational methods in naval architecture and hydrodynamics, particularly ship hull design optimization using advanced algorithms and numerical techniques. He is affiliated with the university's research programs in marine engineering and fluid dynamics. Research Interests: Dr. Huang specializes in hydrodynamic optimization of ship hull forms, computational fluid dynamics (CFD), and the application of bio-inspired algorithms like the Artificial Bee Colony (ABC) for solving complex engineering problems. His work bridges theoretical fluid mechanics with practical ship design challenges, emphasizing drag reduction and seakeeping performance. Key Research Themes: His recent publications highlight contributions in NURBS-based hull modification techniques, validation of Neumann-Michell wave theories, and error analysis in Green function applications for ship wave simulations. The studies often combine numerical modeling with experimental validation to ensure practical relevance. Advising & Grants: No specific grants or advisees are listed in the provided materials. Dr. Huang's work primarily centers on collaborative computational projects within the naval engineering domain.

Alessandro Di Stefanoمشاهده پروفایل

مدرس ارشد

• Game Theory
• Network Science
• Machine Learning
• +۴ مورد دیگر

Dr. Alessandro Di Stefano is a Senior Lecturer in Computer Science at Teesside University's Department of Computing & Games within the School of Computing, Engineering & Digital Technologies. He holds a PhD in Systems Engineering from the University of Catania (2015) and has held academic and research positions at King’s College London, the University of Cambridge, and the University of Catania. His research focuses on interdisciplinary methodologies combining game theory, network science, and machine learning to study socio-technological systems, human cooperation, and complex dynamics. Education: BSc (2009) and MSc (2012) in Telecommunications Engineering from the University of Catania; PhD in Systems Engineering (2015). Professional Qualifications: Postgraduate Certificates in Learning & Teaching in Higher Education (FHEA, 2022). Research Interests: Game Theory, Network Science, Machine Learning, Human Cooperation, Social Dynamics, Homophily, Epidemic Spreading. He collaborates globally, including with the University of Cambridge, Missouri S&T, and King’s College London. Grants/Projects: Lead PI on projects such as KTP - TaperedPlus (AI-driven design systems) and KTP - CSX Carbon (peatland restoration via deep learning). Active in conferences like CCS, ALIFE, and IJCAI, and serves as a reviewer for top journals (IEEE Transactions, Nature Scientific Reports). Labs/Teams: Part of the Interpretable & Beneficial AI group at Teesside, focusing on AI ethics, regulatory frameworks, and complex network modeling. Collaborates with industry partners on AI applications in construction, healthcare, and environmental monitoring.

• Structural Integrity
• Composite Materials
• Fracture Mechanics
• +۳ مورد دیگر

Dr. Shiyao Lin is an Assistant Professor in Mechanical and Aerospace Engineering at the University of Texas at Arlington and member of the Institute for Predictive Performance Methodologies. He holds a PhD from University of Michigan and BS/MS from Huazhong University of Science and Technology, with prior industry experience at Intel and postdoctoral research at University of Michigan. His lab (LIRAM) investigates structural integrity challenges across multiple scales, including progressive failure in composites, semiconductor reliability, bio-inspired 3D printed materials, and impact damage. Research employs experimental characterization, computational modeling, and data-driven approaches to enhance material performance and reliability. Recent grants include DURIP funding for composite damage characterization systems ($183K, AFOSR) and a UTA seed grant for biomimetic composites ($12K). Awards: Rising STARs award (2023), AIAA Structures Paper Awards (2020, 2021), ASC Scholarship (2020), NSF Travel Grant (2024).

• Wireless Sensor Networks
• Internet of Things
• Cloud Computing
• +۲ مورد دیگر

Dr. Byungseok Kang is a Lecturer in Computing at the University of Derby's College of Science and Engineering. His research focuses on advanced networking technologies, particularly in the domains of Internet of Things (IoT), wireless sensor networks, and distributed systems. With expertise spanning cloud computing integration and network protocol optimization, Dr. Kang develops innovative solutions for scalable and efficient communication infrastructures. His research primarily investigates energy-efficient routing protocols, mobility management frameworks, and autonomous network architectures. Recent projects explore IoT-based platforms for real-world applications including drone-based sensing systems and cloud-integrated service platforms. Dr. Kang's work emphasizes practical implementations through experimental testbeds and performance evaluations. Analysis of Dr. Kang's recent publications reveals a consistent focus on optimizing network performance under constrained resources. His work demonstrates strong thematic alignment with emerging needs in low-latency communication systems and distributed computing infrastructures, particularly relevant for next-generation IoT ecosystems.

Reuth Mirskyمشاهده پروفایل

استادیار

• Artificial Intelligence
• Robotics
• Human-Computer Interaction
• +۵ مورد دیگر

Reuth Mirsky is an Assistant Professor in the Department of Computer Science at Tufts University's School of Engineering. She holds a PhD from Ben Gurion University (2019). Her research focuses on artificial intelligence, robotics, and human-robot interaction, with particular emphasis on goal recognition, multi-agent systems, and ethical AI. She has taught courses including Special Topics in Data Analysis, Multi-Agent Systems, and Dissertation Research. Her work explores themes like collaborative control, social navigation, and the theory of mind in AI systems. Education: PhD in Computer Science from Ben Gurion University (2019) Research interests include advancing AI's ability to recognize and adapt to human goals, particularly in dynamic and exploratory environments. Key areas include developing robust algorithms for real-time goal recognition and improving trust in AI through ethical design principles. Recent work addresses challenges in human-AI teamwork, including intelligent disobedience and perception of robotic teammates. Her publications highlight contributions to social robot navigation, ad hoc teamwork, and the ethical implications of AI agency. She actively contributes to interdisciplinary research, co-editing special issues on AI-HRI and organizing workshops on human-interactive robot learning (HIRL).

Eric Tytellمشاهده پروفایل

دانشیار

• Biomechanics
• Neural Control of Locomotion
• Fish Swimming
• +۵ مورد دیگر

Eric Tytell is an Associate Professor in the Department of Biology at Tufts University, within the School of Arts and Sciences. He holds a PhD in Biology from Harvard University (2005), an MPhil in Zoology from the University of Cambridge (1999), and a BA in Biology and Physics from the University of North Carolina (1998). His research focuses on the biomechanics and neural control of locomotion in fishes, particularly how they generate propulsive forces and maintain stability in dynamic environments. His work integrates experiments, computational modeling, and robotics to explore feedback loops between sensory input, neural circuits, and body mechanics. Key research themes include the role of the lateral line system in schooling behavior, the biomechanics of rapid turns, and the design of bio-inspired swimming robots. He leads the Tytell Laboratory, which collaborates on projects involving fluid dynamics, muscle physiology, and evolutionary adaptations. Notable grants include NSF-funded studies on locomotor biomechanics and Army Research Office projects on neuromechanical control. He teaches courses such as Experiment in Physiology and advises graduate students in neurobiology and ecology.

Thomas Wennekersمشاهده پروفایل

دانشیار

• Neural Networks
• Cognitive Modeling
• Computational Neuroscience
• +۲ مورد دیگر

Thomas Wennekers is an Honorary Associate Professor at the University of Plymouth's School of Engineering, Computing and Mathematics. His research focuses on developing biologically constrained neural network models to understand cognitive functions such as language processing, memory formation, and sensory integration. He specializes in hierarchical temporal memory systems and spiking neural networks. Wennekers investigates neural mechanisms underlying semantic processing, cognitive impairments like dementia, and cross-modal plasticity in sensory systems. His work combines computational neuroscience with robotics to create bio-inspired cognitive systems, examining how neural constraints shape learning and perception. His publications explore neurobiological models of language, visual processing, and memory, with applications in neuromorphic computing and cognitive robotics. Recent work simulates neural reorganization in blind individuals and models cognitive disorders using brain-constrained architectures.

Alex Azizمشاهده پروفایل

مدرس

• Computational Materials Science
• Energy Storage
• Defective Graphene
• +۲ مورد دیگر

Dr. Alex Aziz is a Lecturer in Materials/Physical Chemistry at Manchester Metropolitan University’s Joint Education Institute with Hubei University. He holds a PhD in computational chemistry (University of Reading) and completed postdocs at CICEnergiGUNE (Spain), Tohoku University (JSPS fellowship, Japan), and University of Bath. Research employs density functional theory (DFT) and molecular dynamics to optimize materials for energy storage/generation, especially defective graphene supercapacitors and battery systems. Collaborates internationally on photovoltaic and thermoelectric materials. Recent articles (2021-2024) focus on computational design of carbon nanomaterials, battery cathodes, and biomimetic hybrids, with emerging work in AI for materials discovery. Teaches thermodynamics, kinetics, and materials characterization at undergraduate/postgraduate levels. Member of Royal Society of Chemistry and JSPS Alumni. Reviews for Scientific Reports and ACS journals.

Hossein Haj-Haririمشاهده پروفایل

استاد

• Computational Mechanics
• Theoretical Applied Mechanics
• Fluid Mechanics
• +۷ مورد دیگر

Hossein Haj-Hariri is the Dean of the Molinaroli College of Engineering and Computing at the University of South Carolina (since 2016) and holds the title of USC Educational Foundation Distinguished Professor. Previously, he spent 27 years at the University of Virginia, serving as Chair of Mechanical and Aerospace Engineering (2005–2015) and co-Director of the K-12 Engineering Design Laboratory. He earned his Ph.D., S.M., and S.B. in Mechanical and Civil Engineering from MIT. His research focuses on computational and theoretical applied mechanics, including fluid mechanics of swimming, thermal management systems, and interfacial phenomena. He has secured over $30M in research funding, published over 100 papers, and holds patents in thermal management and carbon-fiber composites. Key areas of expertise include aero-acoustics, hydrodynamic stability, and fluid-structure interactions. Education: S.B. in Civil Engineering, MIT S.M. and Ph.D. in Mechanical Engineering (Applied Mechanics), MIT His work bridges fundamental science and applied engineering, with recent emphasis on biomimetic robotics (e.g., manta ray-inspired designs) and high-heat-flux thermal systems. He has mentored over 35 researchers and 50+ undergraduates. Awards: USC Educational Foundation Distinguished Professor Grants and leadership: Spearheaded strategic initiatives to advance engineering education and research at USC. His lab collaborations include projects on microfluidics, flow control, and sustainable energy systems. Current initiatives focus on transforming healthcare through engineering innovation, advanced manufacturing, and smart infrastructure.

Chinwendu Enyiohaمشاهده پروفایل

استادیار

• Distributed Optimization
• Cyber-Physical Systems (CPS)
• Networked Control Systems
• +۵ مورد دیگر

Chinwendu Enyioha is an Assistant Professor at the University of Central Florida (UCF), jointly appointed in the Department of Electrical and Computer Engineering and the Department of Computer Science. He holds a Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania (2014), with postdoctoral research at Harvard University and Tufts University. His research focuses on distributed optimization, control of networked systems, and safety in Cyber-Physical Systems (CPS), emphasizing resource-aware computation and adversarial resilience. He has received prestigious awards including the Ford Foundation Fellowship and the William Fontaine Scholar distinction. Education: Ph.D., Electrical and Systems Engineering, University of Pennsylvania, 2014 B.S., Mathematics (Summa Cum Laude), Gardner-Webb University, 2008 Research Interests: His work addresses challenges in distributed optimization, decision-making under communication constraints, and security in CPS. Applications include multi-robot systems, energy grids, and epidemic control. Current projects include information-efficient distributed sensing and reinforcement learning for autonomous systems. Awards and Activities: Fellow, Ford Foundation (administered by the NRC of the National Academies) William Fontaine Scholar, University of Pennsylvania Patterson Award, MAA Southeast Section Session Organizer, IEEE American Control Conference (ACC) 2016–2018 Technical Reviewer for IEEE/ACM journals and conferences Teaching and Mentorship: He teaches graduate courses in Linear Systems Theory, Nonlinear Control, and Digital Control Systems at UCF. His group includes PhD and MS students working on distributed algorithms, CPS security, and AI-driven control. He advises on over $20M in grants from NSF, NASA, and industry partners like L3Harris. Labs and Collaborations: His research integrates theoretical foundations with practical applications in robotics, energy systems, and network security, leveraging UCF’s interdisciplinary environment and partnerships in the Central Florida Research Park.

Dimitrios Makrisمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Video Analysis
• +۳ مورد دیگر

Dimitrios Makris is a Professor in Computer Vision and Machine Learning at Kingston University's Department of Computer Science, within the Faculty of Engineering, Computing and the Environment. He holds a PhD in Computer Vision from City University London and an MEng in Electrical and Computer Engineering from Aristotle University of Thessaloniki. As Faculty Director of PGR Studies, he oversees postgraduate research programs and leads investigations into video analysis, motion tracking, and neuromorphic vision systems. His research focuses on: Multi-dimensional time-series analysis for human motion tracking Neuromorphic vision sensors for robotic grasping applications Medical video analysis using contrast-enhanced ultrasound Scene semantic modeling and multi-camera systems He has secured multiple research grants from national and international organizations to advance these areas. Publication analysis reveals consistent focus on computer vision fundamentals with growing emphasis on healthcare applications and neuromorphic computing. Recent works demonstrate increased integration of machine learning with sensor technologies for real-time robotic and medical systems. Awards and leadership roles include: Deputy Editor-in-Chief for Special Issues, IET Image Processing Journal Member of Steering Committee, IET Vision and Imaging Network He actively contributes to academic communities through editorial responsibilities and steering committee membership for major vision and imaging networks.