جست‌وجوی استاد و پژوهشگر

Liang Sunمشاهده پروفایل

دانشیار

• Aerospace Engineering
• Multi-Agent Autonomy
• Airborne Robotic System Dynamics and Control
• +۱۲ مورد دیگر

Liang Sun is an Associate Professor in the Department of Mechanical Engineering at Baylor University's College of Engineering, where he leads the Advanced Vehicle Intelligence and Autonomy (AVIA) Lab. The lab was established in August 2025 as a continuation of his earlier Autonomous Systems Lab at New Mexico State University, reflecting his ongoing commitment to cutting-edge research in autonomous intelligent systems. His research spans key areas in aerospace engineering and autonomy, including: Airborne robotic system dynamics and control Multi-agent autonomy and coordination Energy-aware planning and operation for aircraft efficiency Integration of AI technologies like Large Language Models and reinforcement learning into aerospace systems Tethered and high-altitude airborne wind energy systems Uncertainty-aware learning and reasoning for robust decision-making The AVIA Lab employs methodologies from control theory, machine learning, optimization, and finite-element analysis to solve complex challenges in dynamic and uncertain environments. Research is guided by principles of safety, efficiency, adaptability, and ethical engineering, with a vision to serve humanity and inspire students through transformative experiences. Liang Sun's work bridges aerospace systems with artificial intelligence, focusing on next-generation autonomous vehicles and sustainable energy solutions. His research trends emphasize intelligent planning, energy optimization, and resilient control architectures, particularly in aerial and tethered systems operating under real-world uncertainties. He actively mentors students and welcomes both undergraduate and graduate researchers to join the AVIA Lab. Prospective students are encouraged to contact him directly for research opportunities. The AVIA Lab is engaged in initiatives such as the U.S. Drone Soccer program and continues to expand its impact in autonomous systems education and innovation.

Alba Gonzalez Moreiraمشاهده پروفایل

استادیار

• Educational Transition
• Early Childhood Education
• Primary Education
• +۵ مورد دیگر

Dr. Alba Gonzalez Moreira is an Assistant Professor in the Department of Psychology, Sociology and Philosophy at the Faculty of Education, University of León. Her research focuses on educational transitions, guidance systems, and technology integration in teaching. She leads the EVORI research group on Evaluation, Guidance and Educational Policies. PhD: University of León (2023) Key Affiliation: Faculty of Education, University of León Her work emphasizes: Continuity between Early Childhood and Primary Education Artificial Intelligence applications in university teaching Evaluating educational technologies like infographics and VR Support systems for students with disabilities Classroom spatial organization strategies Teacher training for educational transitions Recent publications address systemic challenges in transition processes, AI integration in curricula, and inclusive orientation systems. She employs systematic reviews and simulation-based methodologies to analyze educational practices across European contexts. Her research has been funded through institutional grants supporting: Educational policy analysis Teacher professional development Technology-enhanced learning environments She collaborates with researchers like Dr. Javier Vidal García and Dr. Camino Ferreira Villa.

• Metamaterials and Metasurfaces
• Electromagnetic Wave Control
• Nanoparticle Engineering
• +۶ مورد دیگر

Dr. Luigi La Spada is a Lecturer in Electrical and Electronic Engineering at Edinburgh Napier University's School of Computing Engineering and the Built Environment. His academic journey includes a PostDoctoral Research Assistant position at Queen Mary University of London (2014-2017) and a Lecturer role at Coventry University (2017-2018). He is actively involved with multiple research groups including the Centre for Artificial Intelligence and Robotic, Centre for Conservation and Restoration Science Engineering Research Group, and Centre for Cybersecurity, IoT and Cyberphysical Systems. His educational background includes: Bachelor's and Master's degree (summa cum laude) in Electronics Engineering from University of RomaTre (2008, 2010) PhD in Electronic Engineering (Biomedical Electronics, Electromagnetics, and Telecommunications) from University of RomaTre and University of Pennsylvania (2011-2014) Dr. La Spada's research spans metamaterials engineering, electromagnetic wave control, and advanced sensor development, with significant contributions to metasurface applications and nanoparticle technology. His work has expanded into AI applications for security systems, quantum cryptography for UAV communications, and medical diagnostics. His interdisciplinary approach bridges theoretical electromagnetic concepts with practical engineering solutions across aerospace, healthcare, and agricultural technology sectors. His publication record shows a clear evolution from fundamental electromagnetic research toward applied technologies, particularly in quantum-enhanced security systems, AI-driven biometrics, and medical applications of metamaterials. Recent work demonstrates strong interdisciplinary connections between electromagnetic theory, quantum physics, and artificial intelligence, with increasing focus on practical implementations in aerospace, healthcare, and agricultural monitoring systems. Dr. La Spada has received significant recognition for his research contributions: 2018 Advances in Engineering (AIE) 'key scientific contributor to excellence in science and engineering research' 2017 URSI Young Scientist Award (Canada) Finalist for 2017 IEEE Young Scientist Award 2016 ISAP Best Paper Award (Japan) 2015 EAI recognition for 'new technologies in telecommunications and sensing' His research has received international scientific recognition and media coverage from CNN, CBS, Times, and Aspen Institute. Dr. La Spada currently supervises PhD student Nida Zeeshan on AI-based biometrics facial recognition. He has secured substantial research funding including a £184,194 European Commission grant for Intelligent Multi-Agent Robotic Systems (iMARS) and multiple Scottish Funding Council projects totaling over £74,000. His current grants span robotics, AI visual systems, medical device development (Airglove technology), and wireless power transfer. Dr. La Spada is actively involved in the Centre for Artificial Intelligence and Robotic and Centre for Cybersecurity, IoT and Cyberphysical Systems, where he contributes to developing innovative methods in AI, Robotics, IoT, and 5G technologies. His work connects theoretical electromagnetic concepts with practical applications in healthcare, aerospace, and security systems.

• Deep Learning
• Reinforcement Learning
• Robotics
• +۷ مورد دیگر

Glen Berseth is an Assistant Professor in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal and a core academic member of Mila – Quebec Artificial Intelligence Institute. He holds the prestigious Canada CIFAR AI Chair position and co-directs the Robotics and Embodied AI Lab (REAL). Previously, he was a postdoctoral researcher at Berkeley Artificial Intelligence Research (BAIR) working with Sergey Levine. Dr. Berseth's research focuses on solving sequential decision-making problems for real-world autonomous learning systems, with particular emphasis on human-robot collaboration, reinforcement learning, and various advanced learning paradigms including continual, meta, multi-agent, and hierarchical learning. His work bridges theoretical machine learning with practical robotics applications, aiming to create more capable and adaptable robotic systems. He has published extensively in top venues for robotics, machine learning, and computer animation. His recent publications demonstrate a strong focus on exploration strategies, representation learning, and efficient reinforcement learning algorithms. These works address critical challenges in scaling RL to real-world applications, improving generalization across different robot morphologies, and enabling autonomous learning without extensive human supervision. His research has practical implications for robotics, power grid control, and other complex systems requiring adaptive decision-making. Canada CIFAR AI Chair Dr. Berseth mentors a large group of graduate students across multiple institutions, supervising PhD and Master's candidates working on diverse aspects of robot learning and reinforcement learning. His lab receives significant research funding through his CIFAR AI Chair position and likely other grants supporting his robotics and AI research. The Robotics and Embodied AI Lab (REAL) he co-directs serves as a hub for interdisciplinary research at the intersection of machine learning and physical systems, fostering collaboration between computer scientists, roboticists, and domain experts.

Fuyuki Ishikawaمشاهده پروفایل

دانشیار

• Dependability in Cyber-Physical Systems
• Machine Learning Systems Engineering
• Formal Methods
• +۱۰ مورد دیگر

Fuyuki Ishikawa is an Associate Professor at the Information Systems Architecture Science Research Division of the National Institute of Informatics (NII) in Tokyo, Japan, where he also serves as Director of the GRACE Center. Additionally, he holds positions as an Associate Professor at Sokendai (The Graduate University for Advanced Studies) and as a Visiting Associate Professor at The University of Electro-Communications, focusing on Trustworthy & Smart Software Engineering. His research spans multiple institutions and international collaborations, with a strong emphasis on dependable software systems. Dr. Ishikawa's research interests focus on "Smart Systems and Smart Dependability Assurance," with particular emphasis on dependability in Cyber-Physical Systems and Machine Learning Systems. His work investigates techniques of verification, reasoning, optimization, automated test generation, and self-adaptation by making use of various models for requirements, specifications, and designs. Key research areas include Formal Methods (Formal Specification, Refinement), Testing (Search-based Testing, Model-based Testing), Goal-Oriented Requirements Analysis, Self-Adaptation (Models@run.time), and Machine Learning Systems Engineering. His research also extends to Service-Oriented Computing, Cloud Computing, IoT, and Cyber-Physical Systems, particularly in automotive applications. Analysis of Dr. Ishikawa's recent publications reveals a strong focus on applying formal methods and search-based techniques to ensure the reliability of AI-enabled systems, particularly in safety-critical domains. His work increasingly addresses challenges in testing and repairing deep neural networks within cyber-physical contexts, with significant contributions to autonomous driving systems verification. There's also a growing interest in quantum-classical hybrid systems and the application of evolutionary computation to software engineering problems. His research bridges theoretical formal methods with practical industrial applications, often through large-scale collaborative projects. Dr. Ishikawa has received numerous prestigious awards: Awards for Science and Technology (Research Category) by the Minister of Education (April 2024) IPSJ/IEEE Computer Society Young Researcher Award (March 2020) Multiple Best Paper Awards at ICFEM, SEKE, ICECCS, and ISSRE Best Artifact Award at ISSTA 2015 Dr. Ishikawa leads the Ishikawa Lab at NII, which participates in several major research projects including the ERATO-MMSD Project, MIRAI-eAI Project, REFENG Project, and PerQAS Project. His lab consists of members from different organizations and actively promotes international and industry-academia collaborations. He also offers internship opportunities through NII for students interested in trustworthy software engineering, particularly focusing on generative AI applications and testing of AI systems.

• Artificial Intelligence
• Deep Learning
• Robot Vision
• +۷ مورد دیگر

Kaushik Roy is a Postdoctoral Research Fellow at CSIRO, Australia's national science agency, where he develops deep learning strategies for robot vision and mobile manipulation. His research focuses on designing adaptive AI models that generalize across diverse environments while maintaining robust performance and retaining prior knowledge through lifelong learning. Institution: CSIRO PhD: Monash University, Australia (2023) Research Focus: Adaptive AI, Lifelong Learning, Robot Vision His work has been published in top-tier venues including Neural Networks, ICRA (CORE A*), and MICCAI (CORE A), and he actively contributes as a reviewer for leading AI journals and conferences such as IEEE TPAMI and ICLR. Dr. Roy brings together academic rigor and practical engineering experience, having worked as a Computer Vision Engineer prior to his current role. He is proficient in deep learning frameworks like PyTorch and TensorFlow, and programming languages including Python and C++. Committed to open science, he advocates for transparency and reproducibility in AI research. His expertise spans artificial intelligence, machine learning, computer vision, and neural networks. The body of his published work reflects a strong emphasis on developing intelligent systems capable of continuous adaptation in dynamic environments, with applications in robotics and healthcare. Kaushik Roy has made significant contributions to the global developer community through platforms like Stack Overflow, where he has shared technical insights on deep learning, TensorFlow, Keras, and PyTorch, earning recognition from peers. He has advised no students listed in the available data and has not received any scientific awards explicitly mentioned. There is no indication of part-time status or retirement.

Karsten Schwarzمشاهده پروفایل

پژوهشگر

• Business Information Systems
• Operations Research
• Healthcare Resource Planning
• +۴ مورد دیگر

Karsten Schwarz is a Researcher at the Medical Faculty of Martin Luther University Halle-Wittenberg. He has been affiliated with the Dorothea Erxleben Learning Center Halle (DELH) since 2016 and contributes to the research project FORMAT CONTINUUM. Educational Background: Business Information Systems (BSc) and a doctorate focused on data-driven clinical pathways for hospital resource planning. Professional Background: Researcher at the Medical Faculty (2016–present), Research Assistant at the Chair of Business Information Systems and Operations Research (2008–2016). Research Interests: Karsten specializes in process mining, simulation, and optimization for healthcare resource planning. His work bridges business informatics with clinical decision support systems to enhance hospital operations. Recent Publications: His articles focus on simulation models for hospital logistics, robotic systems in geriatric care, and technology-driven solutions for dementia caregivers. These studies highlight interdisciplinary applications of informatics to improve healthcare efficiency and fairness. Collaborations: He has partnered with institutions like OR-Soft GmbH and contributed to projects involving flexible ward clusters and patient flow modeling.

Massimo Bertozziمشاهده پروفایل

دانشیار

• Computer Vision
• Real-Time Image Processing
• Autonomous Driving
• +۱۲ مورد دیگر

Massimo Bertozzi is an Associate Professor in the Department of Engineering and Architecture at the University of Parma, Italy. He has held a permanent academic position since 1997 and is a leading researcher in computer vision and intelligent vehicles. His work spans real-time image processing, autonomous driving, pedestrian detection, and embedded systems. He earned his Dr.Eng. in Electronic Engineering from the University of Parma in 1994 and completed his PhD in Information Technologies in 1998. His academic journey progressed from PhD student to assistant researcher and eventually to Associate Professor. His research focuses on vision-based systems for autonomous vehicles, including stereo vision, CNNs, SWIR imaging, and sensor fusion. He has been instrumental in pioneering projects such as ARGO, VIAC, TerraMax, and V-Charge. His current work includes collaboration with the IMP Lab on deep learning for computer vision. His recent publications (2022–2025) demonstrate a strong trend in AI-driven image synthesis, disentangled representations, 3D reconstruction, and real-time autonomous driving algorithms. Key themes include diffusion models, GANs, transformers, and efficient neural architectures applied to vision tasks. Scientific Awards: Best Paper Award, CONTROLO 2022 Best Paper Award, VISAPP 2022 He has advised numerous researchers and co-authored with PhD students and collaborators such as Tomaso Fontanini, Leonardo Rossi, and Alex Ergasti. He has not been mentioned to have received major external grants, but his involvement in EU-funded projects (PReVENT, PEGASE, V-Charge) indicates significant collaborative funding. He teaches courses including Computer Science and Programming Laboratory, Fundamentals of Computer Vision, and Deep Learning for Engineering Applications. He is affiliated with the Computer Engineering Group and the IMP Lab at the University of Parma, contributing to a vibrant research environment focused on intelligent systems and autonomous technologies.

• Formal Methods
• Hybrid Systems
• Probabilistic Systems
• +۱۰ مورد دیگر

Erika Ábrahám is a University Professor in the Department of Computer Science at RWTH Aachen University, Germany, where she leads the research group on the Theory of Hybrid Systems. Her work is centered on formal methods for cyber-physical systems, with a strong focus on hybrid and probabilistic systems, SMT solving, and symbolic computation. Her research interests include Formal Methods, Hybrid Systems, Probabilistic Systems, Satisfiability Modulo Theories (SMT), Symbolic Computation, Cyber-Physical Systems, Model Checking, Reachability Analysis, Automated Reasoning, Verification of Safety-Critical Systems, Robotics, Energy Optimization, and Artificial Intelligence . She develops theoretical foundations and practical tools for the analysis and verification of complex systems, especially in safety-critical domains like automotive and robotics. Her recent publications demonstrate a consistent focus on advancing SMT solving techniques, particularly in real algebra and cylindrical algebraic decomposition, and on analyzing probabilistic hybrid systems, including reachability and hyperproperties. She frequently contributes to and organizes major conferences and workshops in her field. Scientific Awards: No specific awards were mentioned in the provided text. Erika Ábrahám actively supervises students and researchers, with advisees including Jasper Kurt Ferdinand Nalbach, Valentin Maxim Promies, Stefan Schupp, and others. She has been involved in projects related to railway timetables, energy load control, and AI-based robotics. She also contributes to academic service through editing conference proceedings and promoting gender equality in software engineering. She is a key contributor to the HyPro library for hybrid systems reachability analysis and continues to publish in top venues such as LNCS, Springer, and Elsevier journals. Her recent work spans from core theoretical advances in SMT to applied research in sonar object detection and robotics.

Bosen Lianمشاهده پروفایل

استادیار

• Cooperative Control
• Graphical Games
• Inverse Reinforcement Learning
• +۹ مورد دیگر

Bosen Lian is an Assistant Professor in the Department of Electrical and Computer Engineering at Auburn University's College of Engineering. He received his Ph.D. in Electrical Engineering from the University of Texas at Arlington, where he also served as a postdoctoral researcher and adjunct professor before joining Auburn in August 2023. His research focuses on distributed control, reinforcement learning, game theory, and their integration in cyber-physical and robotic systems. Research Interests: His work centers on designing safe, optimal, and resilient multi-agent systems through data-driven control and inverse reinforcement learning. Key areas include cooperative control, graphical games, robotics, distributed estimation, and anomaly detection in autonomous systems. He applies these methods to robotic platforms such as robot arms, unmanned vehicles, and sensor networks. His recent publications show a strong trend in leveraging inverse reinforcement learning for multi-agent and adversarial systems, with applications in tracking, estimation, and optimal control. He frequently publishes in top IEEE journals and Automatica, demonstrating consistent contributions to control theory and machine learning integration. Scientific Awards and Recognition: Appointed Associate Editor at IEEE Transactions on Neural Networks and Learning Systems Appointed Associate Editor at IEEE Transactions on Cybernetics Appointed Associate Editor at Transactions of the Institute of Measurement and Control Published first textbook: 'Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games' Advising and Grants: He actively mentors students and researchers such as Wenqian Xue, Vrushabh S. Donge, and others, many of whom are co-authors on his publications. While specific grant details are not listed, his continuous publication output and editorial appointments suggest strong research support and funding. His lab conducts rigorous theoretical analysis alongside practical robotic applications. Labs and Teams: His research group focuses on cyber-physical feedback systems, working on both theoretical algorithms and real-world implementations. The team explores dynamic clustering, consensus, and learning-based control in networked environments, maintaining a balance between provable guarantees and data efficiency.

• Stochastic Control
• Probabilistic Modeling
• Decentralized Control Systems
• +۷ مورد دیگر

Dr. Yuyang Zhou is a Lecturer in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University, where he contributes to the Centre for Artificial Intelligence and Robotics. His research focuses on advanced control systems, probabilistic modeling, and intelligent robotics, with active involvement in EU-funded projects such as iMARS (2024–2028). Institution: Edinburgh Napier University School: School of Computing Engineering and the Built Environment Research Centre: Centre for Artificial Intelligence and Robotics Role: Lecturer Email: Y.Zhou@napier.ac.uk Dr. Zhou's research centers on stochastic and nonlinear control systems, with a strong emphasis on decentralized and probabilistic frameworks. His work integrates machine learning, entropy-based monitoring, and message-passing algorithms to enhance system performance under uncertainty. Key domains include smart grids, industrial prediction systems, and robotics. The recent publications highlight a consistent trend in developing innovative control strategies for complex stochastic systems. These include event-triggered relearning, variance and entropy assignment, and fully probabilistic design methods. The research spans applications in industrial automation, energy systems, and future grid technologies, demonstrating a strong interdisciplinary approach combining AI, control theory, and IoT. Dr. Zhou supervises postgraduate research students, including Anna Chernikova (Hybrid and Switched Control Systems) and Fatima Mumtaz (AI-driven smart banking). He collaborates extensively with Prof. Randa Herzallah and is a co-investigator on the European Commission-funded iMARS project, which aims to develop intelligent multi-agent robotic systems for first responders using AI, IoT, and 5G technologies.

Nikolaos Polatidisمشاهده پروفایل

عضو هیئت علمی

• Machine Learning
• Automated Machine Learning (AutoML)
• Cybersecurity
• +۷ مورد دیگر

Nikolaos Polatidis is a Principal Lecturer in Computer Science at the University of Brighton, within the School of Architecture, Technology and Engineering. He has been a continuous academic staff member since 2017, progressing from Research Fellow to Principal Lecturer by 2022. He holds a PhD in Applied Informatics from the University of Macedonia, an MSc in Internet Software Systems from the University of Birmingham, and a BSc in Computer Science from Heriot-Watt University. BSc, Computer Science, Heriot-Watt University, 2008 MSc, Internet Software Systems, University of Birmingham, 2011 PhD, Applied Informatics, University of Macedonia, 2017 His research centers on machine learning and cybersecurity, with a strong focus on practical applications such as Android malware detection, automated machine learning (AutoML), and ethical AI. He explores how large language models (LLMs) can be used for code generation in security contexts and how ethical narratives can improve the trustworthiness of AI-generated models. His work often integrates deep learning, natural language processing, and privacy-preserving techniques in mobile and IoT environments. The recent publication trends show a strong emphasis on the intersection of AI and cybersecurity, particularly leveraging LLMs and AutoML for malware detection and ethical model generation. Many of his recent papers involve collaborative filtering, recommender systems, and deep learning architectures like convolutional neural networks. There is a clear trajectory toward intelligent, ethical, and automated AI systems in real-world applications. He has received recognition as a Fellow of the Higher Education Academy (FHEA) and serves on the editorial boards of several journals, including The Computer Journal , IET Networks , and Applied Artificial Intelligence . Nikolaos actively supervises postgraduate research in machine learning and cybersecurity. He has led curriculum development by integrating research into teaching, such as introducing Machine Learning for Cybersecurity modules and guiding student projects that result in peer-reviewed publications. He is the Principal Investigator (PI) of the ALFIE project (Assessment of Learning technologies and Frameworks for Intelligent and Ethical AI), funded from 2024 to 2027, which explores ethical and intelligent learning technologies. His grant work emphasizes AutoML, learning frameworks, and ethical AI in education. He is involved in several research teams and collaborates internationally, particularly in AI for cybersecurity and educational technologies. His lab activities focus on developing and testing machine learning models for Android malware detection, ethical AI frameworks, and recommender systems. The ALFIE project indicates an active research group working at the intersection of AI, ethics, and learning technologies.

• Software Engineering
• Software Architecture
• Autonomous Systems
• +۴ مورد دیگر

Patrizio Pelliccione is a Full Professor in Computer Science and Software Engineering at Gran Sasso Science Institute (GSSI) and an Associate Professor at Chalmers | University of Gothenburg. He holds a PhD in Computer Science from the University of L'Aquila. His research focuses on Software Architecture and Autonomous Systems, with applications in automotive and robotics domains. He has extensive international experience, including roles as Associate Professor at University of L'Aquila and Visiting Professor at Charles University. His research interests include software architecture design, autonomous systems, robotics, and automotive systems engineering. He actively collaborates with industry partners globally and has contributed to over 100 peer-reviewed publications across journals and conferences. Pelliccione chairs the Computer Science area at GSSI and leads research initiatives in value-based software ecosystems, continuous compliance, and architecture-driven development. He serves on program committees for major conferences like ICSE and ICSA, and has authored/co-authored books on software architecture and fault-tolerant systems. His work emphasizes practical industry applications, with contributions to automotive systems engineering frameworks, robotic mission specification languages, and safety-critical software development. Current projects explore AI integration in safety-critical domains like space systems and medical devices.

Thar Baker Shamsaمشاهده پروفایل

استاد

• Internet of Things (IoT)
• Edge AI
• Federated Learning
• +۱۲ مورد دیگر

Thar Baker Shamsa is Professor of Industry 4.0/5.0 and Associate Dean (Research and Knowledge Exchange) at the School of Architecture, Technology and Engineering, University of Brighton. He is a Senior Member of IEEE and Senior Fellow of the Higher Education Academy, with extensive leadership in academic governance, research evaluation, and international collaboration. PhD in Autonomic Cloud Engineering, Liverpool John Moores University PGCert in Teaching and Learning in Higher Education, Liverpool John Moores University His research centers on the integration of cyber-physical systems for real-world impact, with key interests in IoT, edge AI, federated learning, and Industry 4.0/5.0. These technologies are applied across digital health, smart cities, transportation, and sustainable engineering, emphasizing inclusivity and quality-of-life enhancement. His work demonstrates a strong interdisciplinary approach bridging computing, engineering, and societal needs. The recent publications highlight a consistent trend in secure, scalable, and intelligent systems—particularly in federated learning security, autonomous vehicle charging, and green transportation using multi-agent reinforcement learning. These works span top IEEE journals and emphasize privacy, efficiency, and robustness in industrial and urban applications. Senior Member, IEEE (SMIEEE) Senior Fellow, Higher Education Academy (SFHEA) Chair, Board of Governors, eSystems Engineering Society (eSES) Member, Council of Professors and Heads of Computing External Assessor for Full Professor promotions at multiple international universities Prof. Baker has successfully supervised over 15 PhD students and continues to mentor new researchers in cutting-edge domains. He leads the REF2029 submission for Engineering (UoA 12) and contributes to Computer Science and Art & Design units. He has evaluated research proposals for Horizon Europe, EU-FP7, British Council, and UNISCO, demonstrating significant grant-related leadership. His editorial roles include Editor-in-Chief of the International Journal of Cyber Research and Education. He leads a dynamic research team focused on IoT, edge AI, and blockchain for Industry 4.0, with active projects in smart factories, intelligent transportation, and secure SDN solutions. He chairs international conferences and collaborates globally, especially in emerging technologies for developing countries.

• Corpus Linguistics
• Influence and Persuasion
• Information Warfare
• +۱۲ مورد دیگر

Dr Keith Scott is a Senior Lecturer in English Language at De Montfort University, affiliated with the School of Humanities and Performing Arts within the Faculty of Arts, Design and Humanities. He serves as Chair of the Faculty Research Ethics Committee and is the Admissions Tutor for the English Language Programme. He is also a member of the DMU Cyber Security Centre and the Media, Culture and Technology research group. His research spans the intersection of language, influence, and cyber conflict, with a strong focus on corpus linguistics, persuasion, information warfare, cyber warfare, and the sociocultural dimensions of 'cyber' . He actively supervises PhD research and delivers subject talks for schools and colleges. Dr Scott’s recent publications (2020–2024) reflect a consistent trajectory in cyber warfare, AI in conflict, information operations, and serious gaming . His work appears in prominent venues such as the Journal of Information Warfare , Frontiers in Psychology , and proceedings of the European Conference on Cyber Warfare and Security (ECCWS). Themes include irony in extremism, multi-domain conflict modeling, influence theory, and ethical AI in military contexts. Vice-Chancellor's Distinguished Teaching Award (2010, 2012, 2017) Centre for Academic Innovation Sabbatical (2021) Education Leadership Programme (2020–2021) He leads and participates in externally funded research projects, notably with the UK Ministry of Defence and the Australian Defence Force, including the POTENTIUM Project and the interdisciplinary PROMETHEUS Research Group , which shapes military doctrine. He is also an active member of professional bodies such as the Royal United Services Institute and the Cybernetics Society, and serves on the organising committee for ECCWS 2024.