جست‌وجوی استاد و پژوهشگر

Sufian Fannounمشاهده پروفایل

مدرس ارشد

• Project Management
• Knowledge Management
• Information Systems
• +۶ مورد دیگر

Dr Sufian Fannoun is a Senior Lecturer and Programme Leader for MSc Programme and Project Management at the University of Chester's Faculty of Science, Business and Enterprise. With over twenty years of experience in higher education, he specializes in teaching, developing, and managing academic programs in Engineering, Computer Science, and Project Management. His educational background includes: PhD in Software Project Management from University of Chester MSc in Digital Enterprise Management from University of Westminster, London BSc in Computer Engineering from Near East University, Turkey Dr Fannoun's research focuses on Project Management , Knowledge Management , and Information Systems . His work explores how organizations, particularly small software development units, can enhance knowledge capture, transfer, and organizational learning. He has developed approaches for implementing lightweight web-based systems to support knowledge management in resource-constrained environments. His publications demonstrate a consistent focus on bridging theoretical knowledge management concepts with practical software development contexts. The research shows progression from analyzing existing practices to proposing and developing systems that enhance organizational learning and knowledge transfer in small enterprises. Dr Fannoun has received the following recognition: Fellow of Higher Education Academy (FHEA) As an academic supervisor, Dr Fannoun is actively supervising PhD theses and welcomes new PhD students working within his research remit. He serves as a reviewer for reputable journals including SAGE Management Learning, Taylor and Francis Group - Knowledge Management, and Emerald - Learning Organisation Journal. His extensive teaching experience spans undergraduate and postgraduate modules across multiple disciplines in computer science and engineering. Dr Fannoun also contributes to the academic community as a Governor at Chester Blue Coat CE Primary School since July 2023.

Vahid Heydari Fami Tafreshiمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Internet of Things Security
• Network Forensics
• +۲ مورد دیگر

Dr. Vahid Heydari Fami Tafreshi is a Senior Lecturer and Cybersecurity Course Director at Staffordshire University's London Digital Institute. With a PhD in Network Security from the University of Surrey, he leads BSc and MSc Cybersecurity programs while teaching across networking and security modules. His research focuses on Internet Protocols & Architectures, Network Forensics, and IoT Security, evidenced by publications in IEEE, Elsevier, and ZTE Communications. Research interests center on securing next-generation networks through innovations in: Secure packet forwarding architectures IoT authentication frameworks MANET security protocols Software-defined networking security Publications demonstrate consistent focus on practical network security solutions, with recent work exploring AI applications in vulnerability testing and ontology-based supply chain security. Earlier research established foundations in VoIP security, satellite network cryptography, and Byzantine fault tolerance for routing systems. Professional activities include supervision of PhD candidates and examining theses, with industry collaborations spanning Airbus Group, Royal Air Force, and NHS organizations. As Fellow of the Higher Education Academy, he develops cybersecurity curricula for both traditional and apprenticeship programs.

Mehdi Mobliمشاهده پروفایل

استاد

• NMR Spectroscopy
• Structural Biology
• Biomolecular Modeling
• +۲ مورد دیگر

Mehdi Mobli is Professor and Group Leader at the Australian Institute for Bioengineering and Nanotechnology, University of Queensland. His research focuses on biomolecular structure and dynamics using NMR spectroscopy, with applications in peptide engineering and ion channel modulation. Key research areas: Advanced NMR techniques for protein structure determination Peptide toxin engineering for ion channel modulation Computational methods for biomolecular design Structural basis of venom peptide function Development of cyclic peptide therapeutics Honors include the ASBMB Merck Medal, Tregear Award, Sir Paul Callaghan Medal, and ARC Future Fellowship. Research has yielded novel peptide therapeutics and computational tools for structural biology.

• Personal Tutoring
• Student Advising
• Higher Education
• +۳ مورد دیگر

Ben Walker serves as an Associate Lecturer within the College of Arts, Humanities and Education at the University of Lincoln, specializing in personal tutoring systems and student advising frameworks in higher education. His current role focuses on APA script marking while advancing scholarly work on tutoring conundrums and student support mechanisms. His research centers on Personal Tutoring , Student Advising , and Student Success with particular emphasis on: Professional standards for UK personal tutoring Developmental support systems for academic tutors Boundary definitions in student support Widening participation through relationship building Resource-constrained delivery of effective tutoring Impact of coaching on student performance Walker consistently addresses the tension between growing demands for personal tutoring and institutional resource limitations. Analysis of his 14 publications (2015-2020) reveals a cohesive research trajectory examining the structural, professional, and emotional dimensions of personal tutoring. His work demonstrates increasing focus on definitional clarity (2018's "A defining moment"), practical implementation challenges (2019's "More important than ever"), and professional recognition systems (2020's standards paper), all grounded in UK higher education contexts with strong emphasis on the University of Lincoln's institutional practices. Walker has led significant funded research initiatives at the University of Lincoln to enhance personal tutor effectiveness through resource development and professional frameworks. His scholarly contributions have generated substantial institutional impact, with 855 total views and 43 downloads across his publications, reflecting growing recognition of his work in advancing personal tutoring as a critical component of student success infrastructure.

Levent Ertaulمشاهده پروفایل

استاد

• Cyber Security & Privacy
• Cyber War
• Hacking Technologies
• +۹ مورد دیگر

Levent Ertaul is a Professor and Chair of the Department of Computer Science at California State University, East Bay (CSUEB). He holds a PhD in Computer Networks Security from the University of Sussex, UK, and advanced degrees in Electrical and Electronics Engineering from Hacettepe University, Turkey. His expertise spans Cyber Security & Privacy, Cyber War, Cryptology, and Wireless Security. He has led research in IoT Security, Post-Quantum Cryptography, and Enterprise Security Planning. Ertaul has held leadership roles including CSUEB Department Chair and served on committees such as the California Cybersecurity 4 Year Education Program Workgroup. His professional development includes summer faculty positions at Lawrence Livermore National Laboratory (LLNL) focusing on CyberDefenders and Global Security programs. He has authored over 50 publications and presented globally at venues like RSA Conference and IEEE events. Awards include the Cisco Instructor Excellence Award and Keynote Speaker recognitions. He teaches advanced courses in Cyber Security, Cryptology, and Network Security Management. Notable contributions include inventing the L4NE protocol for location-based services and the ERTAUL Crypto Algorithm. His grants exceed $15M, including work on National Military Messaging Systems and Firewall Development. He actively participates in cybersecurity competitions (HackCSUEB, CTFs) and advises on policy matters through roles like Bay Area Council Cyber Security Representative.

Stephan Pareigisمشاهده پروفایل

استاد

• Autonomous Systems
• Robotics
• Reinforcement Learning
• +۳ مورد دیگر

Prof. Dr. Stephan Pareigis is the Head of the Department of Computer Science at Hamburg University of Applied Sciences. He holds a professorship in Applied Mathematics and Technical Informatics. His career includes leadership roles such as Chair of the Examination Board for Computer Science (2005–2018) and founding director of the autosys research lab . His expertise spans autonomous systems, reinforcement learning, robotics, and embedded machine learning. He has extensive industry experience, including roles at Heidelberger Druckmaschinen AG and Siemens AG before joining academia in 2004. His research focuses on bridging simulation and real-world applications in autonomous systems, particularly in miniature platforms for reliable AI development. Education and Academic Journey: 1992: Diplom Mathematiker (LMU Munich, minor in Computer Science) 1998: Dr.rer.nat in Numerical Methods for Reinforcement Learning (CAU Kiel) Research Interests: Autonomous and Intelligent Systems Reinforcement Learning for robotics Embedded Machine Learning Miniature autonomy testing frameworks His work emphasizes real-world applicability through projects like Miniature Autonomy for scalable AI validation. Labs and Teams: Leads the autosys research lab , focusing on autonomous systems research and industry collaboration through the Forschungs- und Transferzentrum Smart Systems .

Cath Gristyمشاهده پروفایل

مدرس

• Rural Education
• Multigrade Teaching
• Small Schools
• +۵ مورد دیگر

Dr Cath Gristy is a Lecturer in Education at the Plymouth Institute of Education within the School of Society and Culture at the University of Plymouth. Her work focuses on rural education, multigrade teaching, small schools sustainability, and inclusive pedagogical practices. She actively contributes to policy development through research initiatives like the 'Manifesto for Small Schools' and international workshops on rural education revitalization. Her research interests critically examine the intersections between education, space/place, and community engagement. Notable themes include: the role of school buses in rural access, multigrade classroom dynamics, and the paradoxes of cooperative schooling within neoliberal systems. Dr Gristy also investigates lifelong learning journeys and the socio-spatial impacts of educational policies on rural youth. Recent work includes conceptualizing 'multigrade pedagogy' as a promising approach for resource-constrained settings and analyzing SHAPE graduates' civic impacts. Her international collaborations span Europe, Taiwan, and peripheral regions to address global rural education challenges. Contact: cath.gristy@plymouth.ac.uk | Rolle Building, Floor 5

• Privacy and Data Protection
• Cyber Risk Assessment
• Blockchain Security
• +۳ مورد دیگر

Giulia Rafaiani is a Research Fellow and PhD Student at the Department of Information Engineering (DII), Università Politecnica delle Marche. Her work focuses on privacy-preserving technologies, cyber risk assessment frameworks, and blockchain security. She holds a Master’s in Biomedical Engineering (cum laude) and completed her undergraduate studies in the same field at the same institution. Education: Bachelor’s in Biomedical Engineering, Università Politecnica delle Marche (2017) Master’s in Biomedical Engineering, Università Politecnica delle Marche (2020) PhD Student at DII, Università Politecnica delle Marche (2021–present) Research Interests: Blockchain security and decentralized systems Cyber risk quantification and mitigation Data protection in healthcare software Ethical challenges in AI and machine learning Key Projects: “CybeRAMA” Cyber Risk Assessment Project (2020–2021), funded by Cariverona Foundation PhD research on privacy-preserving blockchain applications Lab Affiliation: Department of Information Engineering labs at Università Politecnica delle Marche.

• Emergency Nursing
• Public Health
• Clinical Leadership
• +۲ مورد دیگر

Lisa Kuhn is an Associate Professor in the School of Nursing, Midwifery and Paramedicine at Nebraska Methodist College. Her research focuses on emergency nursing practices, public health responses to conflicts and disasters, cardiovascular care optimization, and occupational health in healthcare settings. She has led numerous studies on clinical protocols in emergency departments and conflict zones. Her research interests span emergency medicine, clinical leadership development, occupational safety for healthcare workers, and innovative approaches to nursing education. She investigates trauma care systems, disaster preparedness, and healthcare worker safety in high-risk environments. Recent publications demonstrate a focus on evidence-based emergency care protocols, conflict medicine competencies, and healthcare system improvements. Her work frequently addresses clinical decision-making in cardiac emergencies, occupational hazards in nursing, and innovative training methodologies. Professional contributions include development of clinical guidelines for emergency departments and conflict zones. She actively researches healthcare delivery optimization through technological innovations and protocol standardization. Her investigations into nursing competencies in armed conflict contexts have established frameworks for emergency response training and clinical practice in resource-constrained environments.

Xiaoyu Chenمشاهده پروفایل

استادیار

• Machine Learning
• Advanced Manufacturing
• Cyber Manufacturing Systems
• +۵ مورد دیگر

Xiaoyu Chen serves as an Assistant Professor in the Department of Industrial and Systems Engineering within the School of Engineering and Applied Sciences at the University at Buffalo. His academic foundation includes a PhD in Industrial and Systems Engineering (2021) and an MEng in Computer Science (2021) from Virginia Tech, complemented by a BS in Optical Information Science and Technology from Beijing Institute of Technology (2015). Dr. Chen's research spans machine learning methodology for advanced manufacturing, networked data analytics in cyber manufacturing systems, statistical methods for Bayesian deep learning, smart connected health applications for organ transplantation and perioperative medicine, and human behavior/performance modeling. His work bridges industrial engineering with cutting-edge AI techniques to solve complex problems in manufacturing and healthcare systems. Analysis of recent publications reveals a strong focus on developing interpretable and context-aware AI systems for manufacturing and clinical applications. Key trends include multimodal learning frameworks, distributed data processing for fog manufacturing, human-AI collaboration paradigms, and medical diagnostics through novel data modalities like breath analysis. Dr. Chen actively teaches core engineering courses including Probability & Statistics for Engineers (IE 360/560), Simulation (IE 541), and Predictive Analytics (Deep Learning) (IE 463/663), demonstrating commitment to both foundational and emerging topics in industrial engineering education.

• Machine Learning
• Edge Computing
• Networking Technologies
• +۵ مورد دیگر

Mounir Bensalem is a Ph.D. candidate and research assistant at the Institute of Computer and Network Engineering within the Faculty of Electrical Engineering, Information Technology, and Physics at Technical University of Braunschweig, Germany. His research focuses on integrating machine learning and edge computing into next-generation network architectures, particularly in optimizing LoRa, analyzing reconfigurable intelligent surfaces (RIS), and applying reinforcement learning to edge serverless functions. He holds an Engineering Diploma and M.Sc. in Information Systems from the National Engineering School of Tunis. Education: Master’s Degree in Information System Techniques (2017), National Engineering School of Tunis. Engineering Diploma in Industrial Engineering (2017), National Engineering School of Tunis. Key Research Areas: Machine Learning, Edge Computing, 5G/6G Networks, Network Security, and Reconfigurable Intelligent Surfaces. Projects: EU Horizon MANOLO (2024–2026), H2020 FISHY (2020–2023), DFG FOR 2863 (2019–2022), and H2020 mF2C (2017–2020). Awards: Best Paper Award (2022) for work on IoT buffer size benchmarking. Lab/Team: Part of Prof. Jukan’s group at TU Braunschweig, focusing on communication networks and edge computing.

Sayed Ahmad Salehiمشاهده پروفایل

استادیار

• VLSI Circuits
• Stochastic Computing
• DNA Computing
• +۷ مورد دیگر

Sayed Ahmad Salehi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Kentucky's College of Engineering, where he directs the Computing with Unconventional Technologies (CUT) Lab. His research spans energy-efficient VLSI circuits for deep learning, stochastic computing, and DNA-based molecular programming. His research focuses on unconventional computing paradigms to address limitations in traditional electronics. Key areas include stochastic and approximate computing for energy-efficient deep learning hardware targeting IoT and edge devices, and biomolecular computing using DNA for environments incompatible with silicon. His lab develops tools like FUNSC (stochastic computing) and FUNDNA (DNA computing) that enable mathematical function computation through novel encoding schemes. Analysis of his recent publications reveals strong emphasis on in-memory computing architectures (particularly for DRAM and phase-change memory), stochastic-to-binary conversion techniques , and DNA circuit synthesis for mathematical operations. His work bridges theoretical computer science with practical hardware implementations for resource-constrained environments. Award highlights include: BIOMOD competition silver award (2023) Best paper nomination at Asilomar Conference (2022) ESWEEK Student Travel Grant (2019) He actively mentors PhD and undergraduate researchers, with recent graduates joining companies like Applied Materials. His lab secures significant NSF funding for interdisciplinary projects in stochastic computing and DNA-based systems. Current initiatives include CUT Lab's Kentucky iGEM team and collaborations on photonics-integrated computing. The CUT Lab operates at the intersection of computer architecture, molecular biology, and signal processing, with research impacting edge AI hardware, biocompatible computing, and next-generation memory systems.

Amine Mezghaniمشاهده پروفایل

استادیار

• Wireless Communication
• Digital Signal Processing
• Communication Systems
• +۱۲ مورد دیگر

Dr. Amine Mezghani is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Manitoba's Price Faculty of Engineering. His research focuses on wireless communication systems, signal processing, and antenna engineering, particularly under hardware constraints like 1-bit quantization and phase-only DACs. Education: PhD (2015) in Electrical Engineering, Technical University of Munich; Dipl.-Ing. (Electrical Engineering), Technical University of Munich; Diplôme d'Ingénieur, École Centrale Paris His work explores sustainable wireless infrastructure, with emphasis on reconfigurable intelligent surfaces (RIS), millimeter-wave Massive MIMO, V2X communications, and physically consistent modeling combining Shannon and Maxwell theories. Publications include over 100 papers on hardware-constrained systems. Scientific contributions have earned him the 2021 IEEE Signal Processing Society Best Paper Award and the 2016 Rohde & Schwarz Outstanding Dissertation Award . He serves as an Associate Editor for IEEE Transactions on Wireless Communications . Current research includes electromagnetic consistency in multi-band MIMO, unlabeled compressed sensing, and VAMP-based algorithms. He advises graduate students in wireless communications and signal processing at the Intelligent Communication and Sensing Lab .

Jianyi Yangمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Computing Systems
• +۷ مورد دیگر

Jianyi Yang is an Assistant Professor in the Department of Computer Science at the University of Houston. He holds a PhD from UC Riverside (2023), advised by Prof. Shaolei Ren, and has held postdoctoral positions at Caltech and UC Riverside. His research focuses on advancing trustworthy and efficient AI through methodologies like reinforcement learning, online optimization, and learning-augmented algorithms. Education: PhD in Computer Science (UC Riverside, 2023); Postdoctoral work at Caltech and UC Riverside. Research interests include AI/ML applications in computing systems, safety guarantees for AI systems, and sustainable computing. Recent work addresses energy-efficient water infrastructure control and equitable public AI models. Key publications include papers on online budgeted matching, learning-augmented control for water systems, and socially equitable AI. He advises PhD/Master's students and collaborates widely, with a focus on fostering interdisciplinary research. Labs/Teams: Member of the UH Computational Intelligence Group (CIG), mentoring students in AI/ML and systems research.

• Distributed Machine Intelligence
• Low-Power AI for IoT
• Indoor Localization
• +۳ مورد دیگر

Anuradha Ravi is a Research Assistant Professor in the Department of Information Systems at the University of Maryland, Baltimore County (UMBC). Previously, she served as a Research Scientist at the Living Analytics Research Center, Singapore Management University (2018-2023), and as an Assistant Professor at Shiv Nadar University (2016-2018). She holds a Ph.D. in Computer Science from the Indian Institute of Technology Roorkee, where her doctoral research focused on optimizing energy efficiency and latency reduction for mobile devices through intelligent offloading strategies in heterogeneous networks. Her research interests span multiple cutting-edge domains in computing and networking: Distributed machine intelligence at the edge Low-power AI systems for IoT devices Indoor localization and occupancy sensing Wireless networking protocols Mobile and ubiquitous computing Smart building management systems Analysis of her recent publications (2015-2025) reveals a consistent focus on efficiency optimization in constrained environments, with key themes including autonomous robotics, AI-driven compression techniques, multi-sensor localization, and energy-aware mobile systems. Her work increasingly emphasizes real-world applications in contested or resource-limited settings, leveraging machine learning for adaptive solutions. She actively mentors graduate students at UMBC in projects related to perception systems for unmanned vehicles, compression-aware federated learning, and network middleware development. During her tenure at Shiv Nadar University, she supervised undergraduate research on cooperative IoT strategies and 5G edge computing. She previously contributed to the Living Analytics Research Center's initiatives in smart building occupancy detection and collaborative machine intelligence frameworks for IoT devices.