جست‌وجوی استاد و پژوهشگر

Youngwook Koمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Wireless Communications
• Signal Processing
• +۳ مورد دیگر

Dr. Youngwook Ko is a Senior Lecturer in the Department of Electronic Engineering at the University of York. He holds a B.S.E. from Hannam University (South Korea), an M.Sc. from Arizona State University (USA), and a Ph.D. in Electrical Engineering from Arizona State University. His research focuses on applying machine learning and signal processing to wireless communications, including multi-dimensional index modulation, NOMA-ALOHA systems, and reinforcement learning-driven networks. Dr. Ko has authored/co-authored over 50 publications in top-tier IEEE journals and conferences. Educational Background Bachelor of Science in Information and Communications Engineering, Hannam University, South Korea Master of Science in Electrical Engineering, Arizona State University, USA Ph.D. in Electrical Engineering, Arizona State University, USA Research Interests Dr. Ko's work centers on machine learning and signal processing for advanced wireless systems. Key areas include: Machine learning for 6G communications NOMA-ALOHA systems and reinforcement learning applications Multi-dimensional index modulation (IM) techniques Edge computing and network autonomy Awards & Grants Recipient of the EPSRC First Grant Award and member of the EPSRC Peer Review College. His editorial roles include the IEEE Open Journal of Vehicular Technology and Elsevier Journal on Physical Communications. Grants & Collaborations EPSRC-funded project on smart farm radio technology International collaborations in 6G NTN, reinforcement learning, and digital twins Labs & Teams Conducts research within the Department of Electronic Engineering, focusing on next-generation wireless systems and AI-driven communication technologies.

Elva Robinsonمشاهده پروفایل

استاد

• Animal Behavior
• Conservation Biology
• Ecology
• +۳ مورد دیگر

Professor Elva Robinson is a Professor in Ecology at the University of York's Department of Biology. Her research focuses on understanding the social structure of animal groups, particularly ants, and its implications for conservation and invasive species management. She combines lab experiments, fieldwork, and computational modeling to explore how environmental changes affect social behaviors and colony resilience. Her work includes studying Formica rufa wood ants and invasive species like Lasius neglectus, with a focus on network dynamics and intergroup cooperation. Her research interests span behavioral ecology, conservation biology, and the application of systems analysis to biological networks. She collaborates with the York Cross-disciplinary Centre for Systems Analysis (YCCSA) and the European MonitAnt project to assess wood ant conservation statuses. Her teaching emphasizes active engagement, including animated videos and science communication projects. Professor Robinson supervises PhD and MSc projects on topics like ant colony networks, wood ant conservation, and invasive species. She has received a Royal Society Dorothy Hodgkin Fellowship and holds grants supporting research into ant behavior and conservation. Her work bridges ecological theory and practical conservation, with implications for both natural and engineered systems.

Hui Gongمشاهده پروفایل

مدرس

• Artificial Intelligence
• Blockchain
• Cryptocurrencies
• +۲ مورد دیگر

Dr. Hui Gong is a Lecturer in Fintech at Westminster Business School, University of Westminster, where he leads modules on Computational Methods for Finance and Blockchain Technologies & Cryptocurrencies. He holds a doctorate in Financial Mathematics from University College London (UCL) and has prior experience in quantitative finance and fintech projects for investment banks and hedge funds in London. His research focuses on Artificial Intelligence, Blockchain, Cryptocurrencies, and High-Frequency Trading. He co-authored the book Blockchain and Token Economics: A New Economic Era (2019) with Professor Dong Yang. Dr. Gong is a recipient of the 11th Big Ben Award - Golden Seagull UK Ten Outstanding Chinese Students. His teaching responsibilities include leading two postgraduate modules in the MSc FinTech and Business Analytics program. While specific grants or lab affiliations are not detailed here, his work emphasizes practical applications of fintech innovations. For full publication details, visit his research profile .

Jeremy Singerمشاهده پروفایل

دانشیار

• Systems Software
• Garbage Collection
• Compilers
• +۴ مورد دیگر

Jeremy Singer is a Reader in Programming Language Implementation at the School of Computing Science, University of Glasgow. He specializes in systems software, compilers, garbage collection, and secure runtime environments. His research focuses on advancing memory management techniques, many-core parallelism, and edge computing. Singer holds a PhD from the University of Cambridge (2006) in Static Program Analysis based on Virtual Register Renaming. He is a Senior Member of the ACM and a Fellow of the BCS. His academic roles include supervising PhD students in areas such as quantum memory management, federated graph neural networks, and secure memory systems. He has led multiple EPSRC-funded projects, including M4Secure (2023-2026), Capable VMs (2020-2024), and FRuIT (2017-2019). He teaches courses like COMPSCI1016 (Computational Thinking) and COMPSCI4021 (Functional Programming in Haskell). Singer’s research spans compiler design, runtime systems, and security. Notable contributions include work on SSA-based compiler techniques, Raspberry Pi cluster systems, and secure microPython implementations. He has authored over 80 publications and co-developed MOOCs on functional programming and data science. His awards include Fellow of the BCS and Senior ACM Membership. Current research interests include secure memory management, compiler optimizations for heterogeneous architectures, and edge computing security.

• Urban Meteorology
• Atmospheric Boundary Layer
• Climate Modeling
• +۳ مورد دیگر

Lewis Blunn is a Research Fellow at the University of Reading, specializing in urban meteorology and atmospheric boundary layer dynamics. His work focuses on high-resolution weather modeling, scalar dispersion in urban environments, and anthropogenic heat emissions, often leveraging numerical simulations and remote sensing techniques. PhD thesis: 'Characterising mixing and pollution transport in the urban boundary layer' (University of Reading, 2021) Research interests include: Urban canopy parameterization for climate models Convective motion impacts on pollution dispersion Thermal remote sensing applications Anthropogenic heat flux analysis in tropical cities Multi-scale urban-atmosphere interactions Publications (2022-2025) demonstrate expertise in computational fluid dynamics, numerical weather prediction, and urban climate adaptation strategies. Collaborative projects span Germany (urbisphere-Berlin), Colombo, and other urban regions.

Zsofia Krausslمشاهده پروفایل

مدرس ارشد

• Digital Transformation in Finance
• Innovation in Finance
• Data as an Emerging Asset Class
• +۳ مورد دیگر

Dr. Zsofia Kraussl is a Senior Lecturer in Finance and Technology at Bayes Business School (formerly Cass) at City, University of London. She holds a PhD in Information Systems Management from the Free University Amsterdam (2011). Her research focuses on digital transformation in finance, valuation fundamentals, and socio-economic impacts of data as an asset class, with empirical work on marketplace lending and digitization effects. She also investigates higher education curriculum design and performance metrics, having developed an MSc program in Digital Transformation in Finance at the University of Luxembourg. Additionally, she is a visiting scholar at UC Berkeley’s Center for Studies in Higher Education (CSHE). Education: PhD in Information Systems Management, Free University Amsterdam (2011) Her research interests span innovation in finance, digital infrastructure for sustainability, and blockchain applications like tokenization of sukuk. She actively contributes to interdisciplinary studies at the intersection of finance, technology, and education. Recent work includes AI-driven market regime forecasting and differential privacy in smart contracts. Advising and grants focus on curriculum development and digital finance initiatives. Her work often involves collaborations across academic disciplines and industry partners to address emerging trends in financial technology and educational policy. Labs/teams: Collaborates with the CSHE at UC Berkeley and leads interdisciplinary projects at Bayes Business School focusing on digital finance innovation and higher education frameworks.

Riad Shamsمشاهده پروفایل

مدرس ارشد

• Strategic Marketing
• Social Business
• Sustainable Development
• +۵ مورد دیگر

Riad Shams is a Senior Lecturer in Marketing at the Newcastle Business School, Northumbria University, where he also holds roles as Programme Leader for Business with Marketing Management and leads strategic marketing modules. He joined Northumbria in 2019, following academic and industry experience in Australia, Bangladesh, and Russia. His academic credentials include a DBA from Central Queensland University, an MBA and BBA (Honours in Marketing) from the University of Dhaka, PGCAP from Northumbria, and a PGCE. He is a Fellow of the Higher Education Academy. Research focuses on stakeholder relationships, strategic marketing for sustainability, social business, digital marketing, and pedagogical innovation. He has co-authored Marketing Management: Past, Present and Future (4th ed.) and contributed over 111 scholarly publications across journals like Journal of Business Research and Technological Forecasting and Social Change . His work contributes to UN SDGs, particularly sustainability and education. Editorial roles include Associate Editor of the Journal of Social Entrepreneurship , Editor-in-Chief of the International Journal of Big Data Management , and guest editorships for top-tier journals. He has chaired conference tracks on entrepreneurship and innovation at EuroMed Academy of Business and led initiatives on smart technologies in sustainable business. Awards include the Emerald Literati Award (2019) for Outstanding Paper, Emerald Literati Reviewer Award (2018), EuroMed Research Award (2014), and recognition as one of the top-cited authors in social business research (Google Scholar). He is a visiting academic at Belgrade Banking Academy and served as an external examiner at Universities of Lincoln and Nicosia. Teaching expertise spans blended learning, curriculum design, and evaluation. He supervises doctoral candidates in strategic marketing, social business, and digital innovation. Active in international academic networks, he balances research, editorial leadership, and pedagogical innovation.

Djamila Ouelhadjمشاهده پروفایل

استاد

• Operational Research
• Mathematical Optimisation
• Meta-heuristics and Hyper-heuristics
• +۶ مورد دیگر

Professor Djamila Ouelhadj of the University of Portsmouth is a leading academic in Operational Research, affiliated with the School of Mathematics and Physics and Centre for Operational Research and Logistics . She serves as Course Leader for MSc Logistics and Supply Chain Management and contributes to EU-funded projects like SEABILLA and LEANWIND . Her work spans mathematical optimization, meta-heuristics, and decision support systems applied to logistics, transportation, healthcare, and renewable energy. Research Themes : Operational Research, Logistics Analytics, AI for Decision Making, Sustainable Transportation Her recent publications focus on Mobility-as-a-Service (MaaS) systems, drone scheduling for wind farm inspection, and multi-criteria frameworks for inclusive transport. Articles highlight integration of machine learning , stochastic modeling , and robotics in solving real-world optimization problems. She employs multi-objective methods , simheuristics , and clustering techniques to address challenges in renewable energy, urban mobility, and security. Scientific Contributions include: Co-investigator on EU grants for maritime security and wind farm optimization Principal investigator for HEIF-funded Operational Research Centre Chair of scheduling streams at OR53-OR55 conferences Her advising extends to 15 theses, covering topics from nurse rostering to carbon footprint reduction. Collaborative grants include TSB and EU Horizon 2020 projects. She actively contributes to European Journal of Operational Research and leads the Logistics and Operational Research Group (LORG) in developing intelligent decision support systems for complex scheduling problems.

Xiaohui Qiمشاهده پروفایل

استادیار

• Geotechnical Engineering
• Risk and Reliability Analysis
• Probabilistic Site Investigations
• +۳ مورد دیگر

Dr. Xiaohui Qi is an Assistant Professor in the Department of Mechanical and Construction Engineering at Northumbria University since 2020. His research focuses on reliability analysis of geotechnical structures, probabilistic site investigations, and data-driven methods for predicting geotechnical and geological properties. Prior affiliations include postdoctoral roles at Nanyang Technological University (2017-2020) and the University of Macau (2015-2017), alongside a PhD from Wuhan University (2015) and an exchange at the National University of Singapore (2012-2015). His work addresses uncertainty in geotechnical engineering through Bayesian back-analysis, spatial variability characterization, and AI-driven predictive modeling. Key interests include slope stability, braced excavations, and soil parameter estimation using limited data. Recent research trends emphasize integrating machine learning (e.g., Bayesian methods, generalized additive models) with geostatistical techniques for 3D site reconstruction and geological interface prediction. His studies often compare methodologies (e.g., coupled Markov chains vs. stochastic simulations) to optimize spatial prediction accuracy. Collaborations span institutions in Singapore, China, and elsewhere, with a focus on applications like subway construction and foundation design uncertainties. No scientific awards are listed, but his 1625 citations highlight impactful contributions to geotechnical reliability and data analytics.

• Data Science
• Blockchain Technology
• Transportation Systems
• +۷ مورد دیگر

John Easton is a Professor in the School of Social Sciences at Heriot-Watt University, United Kingdom. His research bridges technology, data science, and transportation systems, with a strong focus on blockchain applications, data quality, and railway infrastructure. He actively contributes to advancements in smart cities and industrial information integration. Research Interests: His work centers on data-driven decision-making in industrial and transport contexts. Key areas include blockchain-based systems for public transit ticketing, data quality in industry, railway track monitoring, and digital transformation in transportation. His research supports UN Sustainable Development Goals through innovations in sustainable infrastructure and smart mobility. The recent publications indicate a strong trend in applying blockchain and data analytics to transportation and industrial systems. Topics such as decision-making frameworks for blockchain adoption, integrated data platforms for railway maintenance, and secure data sharing in smart cities reflect a cohesive research agenda focused on technological innovation for societal benefit. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: While no direct information on students or grants is available, his senior academic rank and extensive publication record suggest active supervision and research leadership. Collaborations with researchers like J.D. Preece and Q. Fu indicate team-based research projects likely funded by external grants. Labs and Teams: Although no specific lab or research group is named, his collaborative work and focus areas suggest involvement in interdisciplinary research teams working on smart transportation, blockchain applications, and industrial data systems at Heriot-Watt University.

• Cybersecurity
• Resilience Engineering
• Critical Infrastructure Protection
• +۳ مورد دیگر

Professor Paul Smith holds a Chair in Networking at the Department of Computing and Communications , Lancaster University , and serves as Interim Head of Department . His research focuses on cybersecurity and resilience engineering for critical networked systems , particularly in digitalized nuclear infrastructure . His work explores risks of digital innovation in critical sectors, resilience frameworks , and cyber-attack mitigation . He leads national and international research projects , collaborating with the International Atomic Energy Agency (IAEA) to enhance computer security programs in nuclear facilities. Current projects include DSI: DVAC (2025), JUNO Mini Project (2023-2024), and Resilience for Cyber-Physical Energy Systems (2022-2024). Prioritizing knowledge exchange , he contributes to cybersecurity education via cyber ranges and international workshops . His team, Security Lancaster , supports nuclear sector cybersecurity through practical tools like the Goosewolf intrusion detection system and PLCblockmon for industrial control systems .

• Highway Asset Management
• Road Pavement Analysis
• Road Safety Engineering
• +۵ مورد دیگر

Harry Evdorides is a Lecturer in the Department of Civil Engineering at the University of Birmingham. He holds academic and administrative roles including Welfare Tutor and Senior Road Executives Programme Leader. His professional qualifications include Dipl.-Ing. (Aristotle University of Thessaloniki, Greece) and PhD (University of Birmingham, 1994), alongside certifications like CEng, EurIng, and MIHT. Education Background: Dipl.-Ing. in Civil Engineering, Aristotle University of Thessaloniki, Greece PhD (Civil Engineering), University of Birmingham Research Interests: Focused on highway asset management, pavement structural analysis, and road safety engineering. His work integrates expert systems, finite element analysis, and data-driven approaches. Key areas include pavement performance prediction, road infrastructure maintenance optimization, and pavement design for developing countries. Publishing Trends: Recent works emphasize pavement reliability (2007), road safety asset management (2006), and educational innovations in engineering (2005). Earlier contributions include foundational research on knowledge-based systems for pavement analysis (1994-1996). Awards: Recipient of the 1997 Telford Premium (ICE) for impactful contributions to civil engineering knowledge. Academic Contributions: Supervised numerous MPhil/PhD/MSc projects on topics like road data reliability, sustainable pavement management, and multi-criteria analysis for road works scheduling. Active in curriculum development, notably the MSc Roads and Public Policy program and the Senior Road Executives Programme. Labs/Teams: Leading member of the Accident Research Group and involved in the Highways Group's R&D projects since 1990.

Pantelis Sopasakisمشاهده پروفایل

مدرس

• Model Predictive Control
• Embedded Numerical Optimization
• Stochastic Optimal Control
• +۵ مورد دیگر

Dr. Pantelis Sopasakis is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast, Northern Ireland. His research focuses on developing efficient numerical optimization algorithms and model predictive control (MPC) methodologies for uncertain systems, with applications in autonomous vehicles, smart infrastructure networks, and advanced manufacturing. He leads projects on embedded optimization solvers, GPU-accelerated MPC, and stochastic control for systems like water networks and microgrids. His work emphasizes real-time implementation and safety-critical applications in robotics and energy systems. He teaches postgraduate and undergraduate courses in control theory and signals, and is actively involved in supervising PhD students in areas like parallel algorithms and MPC for uncertain systems. Key achievements include the development of the Open-Source Optimization Engine , widely used for embedded MPC. Research interests span distributed embedded intelligence, intelligent uncertain-aware MPC, and biomedical applications of control systems. He collaborates internationally on projects involving risk-averse control, multi-agent systems, and circular economy applications. His interdisciplinary work bridges optimization theory, robotics, and energy systems, with a focus on scalable and real-time solutions. Teaching includes modules on control systems fundamentals and advanced MPC concepts, supported by his textbook Control Systems: An Introduction . Dr. Sopasakis has contributed to over 50 publications, with recent work on conformal prediction for stochastic control, distributed collision avoidance, and thermodynamical material networks. He participates in conferences and editorial activities, and has organized events like the 2025 IEEE UK and Ireland Robotics Conference. His research group is part of the Energy, Power, and Intelligent Systems and Control clusters at Queen's.

• Medical Oncology
• Lung Cancer
• Mesothelioma
• +۶ مورد دیگر

Professor Michael Lind is a Foundation Professor of Oncology at the University of Hull and Head of the Joint Centre for Cancer Studies . With 35 years in medical oncology (25 as a consultant), he focuses on lung cancer, mesothelioma, oncogeriatrics, and translational research. Chairs National Cancer Registration and Analysis Service lung group for Public Health England Leads projects on physical activity interventions, geriatric assessment, and cancer care equity Supervises 10 completed PhD/MDs and 1 current PhD/MD Research Trends: Recent works span precision oncology (EGFR mutations), healthcare disparities (geographical/socioeconomic), palliative interventions (venting gastrostomy), and pandemic-related cancer care disruptions. Keywords include Lung Cancer, Mesothelioma, Geriatric Assessment, Health Equity, Palliative Care . Labs & Collaborations: Works with the Institute for Clinical and Applied Health Research (ICAHR) and Hull Molecular Imaging Centre (HuMic) .

• Computer Vision
• Intelligent Robot Control
• 3D Computer Graphics
• +۱۲ مورد دیگر

Dr Jiacheng Tan is a Senior Lecturer in the School of Computing at the University of Portsmouth , where he has been a faculty member since 2002. He is actively involved in research and PhD supervision, with a strong focus on intelligent systems and robotics. Dr Tan earned his BEng in Mechanical Engineering from Jilin University of Technology (1983), an MSc in Mechatronics from Xidian University (1989), and a PhD in Computer Graphics from De Montfort University (2001). Prior to joining Portsmouth, he served as a Visiting Researcher in robotics at the University of Salford (1996–1997) and a Research Fellow in artificial intelligence at the Open University (2000–2002). His research centers on computer vision, intelligent robot control, 3D graphics, and human-robot interaction . He investigates how robots can understand and act upon natural language commands by grounding spatial relations, recognizing objects, and reasoning about tasks in unstructured environments. His work integrates fuzzy logic, knowledge engineering, and machine learning to enable robots to learn from demonstrations and interact meaningfully with humans. The trends in his publications reveal a consistent focus on robotics and intelligent systems , evolving from early work in virtual environments and telerobotics to recent contributions in cloud-based scientific visualization and machine learning applications in astrophysics. His interdisciplinary research spans computer science, control theory, and cognitive systems. Dr Tan has not received any explicitly mentioned scientific awards in the provided text. He serves as a PhD supervisor and has contributed to multiple research projects, including the development of integrated AI frameworks for robotic manipulation. While specific grant details are not listed, his collaborations and publications suggest active involvement in funded research initiatives. He has worked with researchers across institutions on topics ranging from scientific visualization to intelligent interfaces. Dr Tan is affiliated with the Computational Intelligence Research Group at the University of Portsmouth. His lab work involves developing virtual environments, symbolic representations of 3D scenes, and natural language interfaces for robot control, supporting both academic research and practical applications in automation.