جستجوی استاد راهنمای دانشگاهی

Dr. Gulsum Kubra Kaya is a Lecturer in Human Factors at the Centre for Safety & Accident Investigation at Cranfield University. She is a Chartered member of the Chartered Institute of Ergonomics and Human Factors Society (C.Erg.HF) and a Fellow of the Higher Education Academy (FHEA). Dr. Kaya holds a BEng in Industrial Engineering from Sakarya University, an MSc in Systems Engineering Management from University College London, and a PhD in Engineering from the University of Cambridge. Her academic journey includes prior roles as a Lecturer and she earned the title of 'Associate Professor' in Industrial Engineering in 2022. Her research focuses on system safety, human factors, risk assessment, machine learning applications, and decision-making in complex systems. Her work spans various domains including healthcare, transportation, and industrial settings. She is particularly interested in: Air Transport Safety & Investigation Industrial Ergonomics and Human Factors Safety, Resilience, Risk & Reliability Systems Engineering approaches to safety Her recent publications demonstrate a strong focus on applying systems thinking and advanced analytical methods to safety challenges. She has published extensively on topics such as Safety-I and Safety-II approaches, machine learning applications in healthcare safety, risk assessment practices in hospitals, and system-based risk analysis in transportation systems. Dr. Kaya serves on the editorial board of the Ergonomics journal and is an associate editor at the Risk Management and Healthcare Policy Journal. She also serves on the editorial board at the BMJ Health & Care Informatics Journal. She is actively involved in research on safety in liquid-hydrogen-powered aircraft operations and bacteria-type detection. Dr. Kaya is open to supervising PhD students interested in system safety research.

• System Safety
• Human Factors
• Risk Assessment
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Ewan Dolier is a Research Fellow in the Department of Physics at the University of Strathclyde, Faculty of Science. He is actively involved in cutting-edge research on laser-driven ion acceleration and plasma physics, working within the SCAPA (Scottish Centre for the Application of Plasma-based Accelerators) facility. His work bridges experimental physics and machine learning techniques to optimize and diagnose high-energy particle beams. His research interests include: Laser-Plasma Interactions Machine Learning for Physics Optimization Proton and Ion Beam Acceleration Synthetic Diagnostics using Neural Networks High Repetition Rate Laser Systems Relativistic Transparency Regime Physics The recent trend in his publications shows a strong focus on integrating artificial intelligence and deep learning models into the control and analysis of laser-driven particle acceleration experiments. His work spans experimental design, data-driven optimization, and advanced diagnostics using scintillating fiber spectrometers and synthetic models. His scientific contributions have been presented at major plasma physics conferences and published in high-impact journals such as Communications Physics and High Power Laser Science and Engineering . Notable projects include: External Experiment at the Gemini High-Power Laser Facility (Deep Learning for Ion Acceleration) Development of High Repetition-Rate Target Systems at SCAPA Doctoral Training Partnership research (2019–2024) He collaborates extensively with leading researchers such as Paul McKenna and Ross Gray, and contributes to multi-investigator datasets and simulations. Ewan Dolier completed his PhD in 2024 with a thesis on advancing laser-driven ion acceleration using machine learning and instability analysis.

• Laser Physics
• Plasma Physics
• Machine Learning in Physics
• +۷ مورد دیگر

Dr. Stella Pytharouli is a Senior Lecturer in Civil and Environmental Engineering at the University of Strathclyde. With over 20 years of expertise in structural and ground deformation monitoring/analysis, her research focuses on subsurface characterization and slope instability early warning systems through microseismic monitoring, geodetic technologies, and machine learning integration. MEng (2002) - University of Patras MSc (2004) - University of Patras PhD (2007) - University of Patras Her research combines advanced signal processing with geodetic monitoring (terrestrial/aerial) to develop AI-driven solutions for UK landslide sites. Key areas include: Microseismic monitoring of weak seismic events Geometric and kinematic analysis of ground deformations Integration of geotechnical data with machine learning Climate change impact on slope stability Low-cost sensor development for environmental monitoring Recent publications highlight her work on AI-based seismic classification models, tiltmeter applications, and 3D reconstruction techniques. Her group includes 4 PhD students and 1 postdoc. Scientific recognitions include: Geophysical Research Letters front cover selection (2011) EOS Research Spotlight (2019) Lampadarios Prize from Academy of Athens (2009) TOPCON Award for young researchers (2008) As Director of Postgraduate Research (2020-present), she supervises PhD students and teaches land surveying modules. Current projects address slope stability analysis, climate change correlations, and seismic data automation.

• Microseismics
• Geodetic Deformations
• Slope Instability
• +۶ مورد دیگر

Dr Marieke Meelen is an Associate Professor in Historical Linguistics at the University of Cambridge, affiliated with the Faculty of Modern and Medieval Languages and Linguistics. She serves as a Fellow, Tutor, and Director of Studies at Trinity Hall. Research Interests: Historical Linguistics, Comparative Syntax, Information Structure, Grammaticalisation & Pragmaticalisation, NLP for low-resource languages, Celtic & Tibeto-Burman languages Projects: PI for ELDP-funded endangered language documentation in Nepal; collaborator on ERC-funded 'PaganTibet' and AHRC-funded 'Emergence of Egophoricity' Key Contributions: Development of ASR and HTR models for Tibeto-Burman languages; historical treebank of Welsh; computational approaches to Celtic and Tibeto-Burman syntax Publications & Grants focus on syntactic reconstruction, corpus creation, and NLP for endangered languages. She mentors PhD students working on Celtic or Tibeto-Burman languages and consults for computational linguistics projects.

• Historical Linguistics
• Comparative Syntax
• Information Structure
• +۵ مورد دیگر

Dr. Benjamin Evans is an Assistant Professor in Computer Science & AI (Informatics) at the University of Sussex , affiliated with the School of Engineering and Informatics . His research integrates computational neuroscience and artificial intelligence, focusing on biologically inspired neural networks. Current Position: Assistant Professor, Department of Informatics, University of Sussex Previous Roles: Research Associate at University of Bristol, University of Exeter, Imperial College London, and University of Oxford Education: DPhil in Computational Neuroscience (University of Oxford), MSc in Intelligent Systems (UCL), BA in Experimental Psychology (Oxford) His research centers on how neural systems self-organize to produce intelligent behavior, studied through both biological and computational modeling. He investigates spiking neural networks , convolutional neural networks , and the role of biological constraints in enhancing AI robustness and human-like perception. He is particularly interested in how spike-based information processing contributes to adaptive cognition in noisy environments. His recent publications reveal a strong trend in evaluating deep neural networks as models of human vision, questioning their biological plausibility while proposing bio-inspired improvements. He also works on optogenetics simulation (e.g., PyRhO platform), developmental biology modeling , and reproducible data science through containerization tools like Docker. His scientific contributions have been recognized through publications in high-impact journals such as Nature Communications , PLoS Computational Biology , and Behavioral and Brain Sciences . EPSRC Grant: "Exploring the multiple loci of learning and computation in simple artificial neural networks" (2023–2024) EPSRC Grant: "Using ant biology and natural environments to enhance models of vision and robot navigation" (2022–2026) Dr. Evans actively contributes to open science through GitHub repositories (e.g., PyRhO, DPE, BioNet) and promotes reproducible research. He has no listed advisees in the provided data, but leads funded research projects involving junior researchers. He is a core member of the Informatics research group at Sussex, contributing to both AI and neuroscience domains.

• Computational Neuroscience
• Spiking Neural Networks
• Convolutional Neural Networks
• +۷ مورد دیگر

Professor Michael Clarke is a distinguished academic at the University of Huddersfield , serving as Director of IRiMaS (Interactive Research in Music as Sound) and holding leadership roles including former Dean of the School of Music, Humanities and Media and Dean of the Graduate School . His career spans over three decades at Huddersfield, where he has pioneered innovative software for music composition, pedagogy, and analysis. Education: PhD in Music (Durham University), MTC in Teaching (UCL Institute of Education) Clarke's research focuses on composition , particularly in live interactive works , and the development of software like Max/MSP for musicological analysis and sound synthesis. His work intersects with UN Sustainable Development Goals , emphasizing technological innovation in education and cultural preservation. Recent publications highlight his contributions to interactive aural analysis and fluid corpus manipulation tools. Clarke has secured major funding, including a €2.5m ERC Advanced Grant for IRiMaS and AHRC grants for collaborative projects. Awards include the National Teaching Fellowship (2011) and multiple European Academic Software Awards . Scientific Awards: National Teaching Fellowship (2011) European Academic Software Awards (record 3 wins) As a Principal Investigator , he has led projects with Prof Peter Manning and Dr Frédéric Dufeu, while actively supervising PhD students and contributing to REF assessments.

• Computer Music
• Electroacoustic Music
• Music Technology
• +۶ مورد دیگر

Farshad Arvin is a Professor of Robotics in the Department of Computer Science at Durham University. Prior to this, he held academic positions at The University of Manchester (2018-2022) and worked as a Research Assistant at the University of Lincoln (2012-2015). He holds a BSc in Computer Engineering (2004), an MSc in Computer Systems Engineering (2010), and a PhD in Computer Science (2015). His research focuses on Swarm Robotics , Bio-inspired Swarms , and Autonomous Multi-agent Systems . He pioneered the Swarm & Computation Intelligence Laboratory (SwaCIL) at Durham, leading projects like H2020-FET RoboRoyale (€3.27M), Horizon Europe Sensorbees (€3.2M), and BioDiMoBot (€8M), with total funding exceeding £4M. Recent publications highlight advancements in swarm trajectory optimization (T-STAR), collision-free multi-robot coordination, and bio-hybrid environmental monitoring. His work integrates bio-inspired algorithms with practical applications in autonomous vehicles, aerial drones, and hazardous environments. Scientific Awards: Marie Skłodowska-Curie fellowship Notable Projects: EU H2020-FET RoboRoyale (2021-2026) Horizon Europe Sensorbees (2024-2029) Horizon Europe BioDiMoBot (2025-2030) H2020-FET Robocoenosis (2020-2025) Supervision: Mentors 8 postgraduate students at Durham, including Hanadi Alhamdan, Hang Wang, and Honghao Pan.

• Swarm Robotics
• Bio-inspired Swarms
• Multi-agent Systems
• +۴ مورد دیگر

Dr. Lateef Akanji is a Senior Lecturer in the Department of Petroleum Engineering at the School of Engineering, University of Aberdeen, where he has been contributing since 2014. He previously served as Lecturer and Head of the Petroleum Technology Research Group at the University of Salford, Assistant Professor at King Saud University, and Visiting Lecturer at the University of Leoben. His academic journey includes a PhD from Imperial College London and degrees from the University of Ibadan. University: University of Aberdeen School: School of Engineering Position: Senior Lecturer, Petroleum Engineering Email: l.akanji@abdn.ac.uk Education: PhD, Petroleum Engineering, Imperial College London M.Sc., Petroleum Engineering, University of Ibadan B.Sc. (Honours), Petroleum Engineering, University of Ibadan DIC (Diploma of Imperial College) Research Interests: Dr. Akanji's research centers on multiphase flow in porous and permeable media, with applications in enhanced oil recovery (EOR) in clastic, carbonate, and unconventional shale reservoirs. His work integrates theoretical, experimental, and computational fluid dynamics, utilizing platforms like Python, C++, and Fortran. He is pioneering the application of artificial intelligence in petroleum engineering, particularly in EOR screening and production optimization. His research includes pore-scale modeling, gas-lift systems, and nuclear reactor flow dynamics. Publication Trends: His recent publications (2025–2021) reflect a strong focus on fluid displacement in porous media, shale reservoir characterization, AI applications in energy, and nuclear safety. Notable themes include computational modeling of multiphase flow, biosurfactant EOR, and advanced numerical methods for reservoir simulation. Scientific Awards and Honors: Fellow of the Higher Education Academy (FHEA) Chartered Engineer (CEng) Chartered Petroleum Engineer European Engineer (Eur Ing) Member of the Energy Institute (MEI) Advising and Grants: Dr. Akanji supervises numerous PhD students in areas such as AI-based production optimization, permeability upscaling, and biosurfactant EOR. He leads research funded by PTDF, TETFUND, Sonangol, and Elphinstone, focusing on high-pressure high-temperature flow loops, gas-lift pilot rigs, and neuro-fuzzy screening systems. His collaborative projects involve institutions in the UK, Austria, and Australia. Laboratories and Research Platforms: He contributes to the development of the Complex System Modelling Platform (CSMP++), a C++-based API for simulating multi-physics flow in porous systems, co-developed with ETH Zurich and Montanuniversität Leoben. He also leads a technology innovation platform for EOR, including experimental rigs for biosurfactant screening and gas-lift stability testing.

• Petroleum Engineering
• Multiphase Flow in Porous Media
• Enhanced Oil Recovery (EOR)
• +۷ مورد دیگر

Richard Charles Wilson is a Professor of Pattern Analysis in the Department of Computer Science at the University of York, where he leads the Artificial Intelligence research group and serves on the Departmental Research Committee. His work bridges theoretical and applied aspects of machine learning and computer vision, with a focus on structural pattern recognition using graphs and networks. Research Interests: His research spans Pattern Analysis , Machine Learning , Computer Vision , and Graph-based Pattern Recognition . He applies these to diverse domains including bioinformatics, navigation systems, and neural network design. His recent work explores deep learning without backpropagation, GNSS interference detection, and AI in drug discovery. The most recent publications reflect a strong trend in applying AI to real-world challenges in healthcare and signal integrity, combining deep learning with novel architectures and semi-supervised techniques. His work often appears in high-impact journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics and The Journal of Navigation. Scientific Awards: IAPR Fellow Award (2010) Wilson actively contributes to academic service, including PhD examination, editorial board membership for Pattern Recognition , and research evaluation for institutions like the Czech Academy of Sciences. He has led and contributed to multiple funded research projects, including those supported by EPSRC and The Royal Society. His leadership in the UKRI AI Centre for Doctoral Training in Safe AI Systems highlights his role in training the next generation of AI researchers. He is involved in significant research projects such as the Graphical Modeling of Brain project funded by The Royal Society and the UKRI AI Centre for Doctoral Training in Safe AI Systems (SAINTS) , where he serves as a co-investigator. These projects emphasize safe, interpretable, and biologically inspired AI systems.

• Pattern Analysis
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Dr. Nicholas Cummins is a Lecturer in AI for Speech Analysis at King’s College London, specializing in applying machine learning to health conditions, particularly mental health disorders. He holds roles in the Department of Biostatistics & Health Informatics and is affiliated with the NIHR Maudsley Biomedical Research Centre. His research focuses on speech processing, affective computing, and digital phenotyping, with projects like RADAR-CNS and DE-ENIGMA. He earned his PhD from UNSW Australia (2016) and conducted postdoctoral work in Germany before becoming habilitation candidate at the University of Augsburg. Education: PhD in Electrical Engineering, UNSW Australia (2016) Habilitation Candidate, Chair of Embedded Intelligence for Healthcare, University of Augsburg Research Interests: Machine learning for mental health monitoring Speech-based biomarkers for depression and psychosis Wearable device integration for health tracking Multilingual speech analysis Key Projects: RADAR-CNS: Data analysis for neurological conditions DE-ENIGMA, TAPAS, sustAGE (Horizon 2020) National Science Foundation of China project on speech-based depression diagnosis Grants & Awards: Over 100 peer-reviewed publications (h-index: 23) NSFC-funded project on speech analysis for depression Reviewer for IEEE, ACM, ISCA journals Labs & Teams: Involved in the NIHR HealthTech Research Centre in Brain Health and the EMBRACE initiative for maternal/child health with AI.

• Artificial Intelligence
• Machine Learning
• Affective Computing
• +۶ مورد دیگر

Professor Iain Fraser is a faculty member at the University of Kent's School of Economics, holding the position of Professor of Agri-Environmental Economics. He obtained his PhD from the University of Manchester in 1992 and has held roles at institutions including the University of Manchester, Manchester Metropolitan University, Imperial College, and La Trobe University in Australia. His research focuses on agri-environmental economics, biodiversity conservation, and applied econometrics. Current research projects include UKRI-funded initiatives on sustainable food systems and healthy diets. Fraser’s academic contributions span over 100 publications, with recent work addressing topics like wildlife trade dynamics, consumer preferences for food labeling, and pollinator deficit impacts. He leads the Professional Economics Degree Apprenticeship and serves as Editor-in-Chief of Q Open . His affiliations include the Durrell Institute of Conservation and Ecology (DICE) and DEFRA's Economic Advisory Panel. Notable projects include BEESPOKE (pollination management) and studies on country-of-origin labeling. Fraser supervises PhD students researching topics such as elephant-human conflict and wine waste valuation. He has advised on DEFRA and FSA projects and contributed to policy analysis in environmental economics and agricultural policy. Fraser’s work integrates econometric methods with conservation challenges, emphasizing practical applications in policy and market design. His lab affiliations and editorial roles highlight his leadership in advancing interdisciplinary research at the intersection of economics and environmental science.

• Agri-Environmental Economics
• Environmental Economics
• Natural Resource Economics
• +۴ مورد دیگر

Mengqiu Cao is a Lecturer in Urban Systems Predictive Analytics and Machine Learning at the University College London (UCL) within the Bartlett School of Environment, Energy and Resources . He integrates academia and industry expertise to advance interdisciplinary research at the intersection of transport analysis and urban studies. Research Focus : Sustainable transport, urban mobility, logistics, social equity, and low carbon transitions. Teaching : Coordinates modules on climate sciences, data-driven consumer behavior analysis, and transport policy. Awards : Holds fellowships with the Royal Geographical Society, Royal Statistical Society, and Royal Society of Arts. Publications : Recent works examine green space impacts on mobility, equitable EV charging access, dockless bike-sharing patterns, and 15-minute city frameworks.

• Sustainable Transport
• Urban Mobility
• Logistics and Supply Chains
• +۸ مورد دیگر

Dame Til Wykes is a Clinical Professor at King’s College London, leading the School of Mental Health & Psychological Sciences and the Service User Research Enterprise (SURE) . Her work focuses on psychological treatments for schizophrenia , cognitive remediation therapy , and digital mental health services , with international impact on research strategies through projects like European ROAMER and UK Mental Health Research Goals . Education : PhD (University of Sussex), MPhil (King’s College London), BSc (University of Nottingham) Leadership : Head of School (2020–present), Co-Director of SURE, NIHR Maudsley BRC Cluster Lead Research Themes : • Cognitive Remediation Therapy for schizophrenia and psychosis • Digital Mental Health Tools (RADAR-CNS, CIRCuiTS™ software) • Service User Involvement in research design and implementation • Ward Design and Therapeutic Environments in psychiatric inpatient care Selected Scientific Awards : British Psychological Society (2014) GUINNESS WORLD RECORD for Largest Mental Health Lesson Damehood from the Queen (2016) EPA Outstanding Achievement Award SIRS Lifetime Achievement Award (2024) Leadership and Collaborations : President of the Schizophrenia International Research Society (SIRS), Fellow of multiple academies (Medical Sciences, Social Sciences), and Trustee of Weight Concern. She co-leads projects like ECLIPSE and MEMReD , and has contributed to 17 Pharmacological and Psychosocial Treatments in Schizophrenia (3rd ed.).

• Clinical Psychology
• Rehabilitation Psychology
• Schizophrenia Research
• +۵ مورد دیگر

Enda Hayes serves as Professor of Air Quality & Carbon Management and Director of Research and Enterprise at the School of Architecture and Environment, University of the West of England (UWE Bristol). With over a decade of professional experience in environmental science, he specializes in atmospheric emissions management including odour, bioaerosols, traditional air pollutants, and greenhouse gases. His work spans technical modeling, policy development, and community engagement across multiple international projects. Dr. Hayes holds a PhD, MSc, and BSc (Hons), along with professional memberships MIEnvSc and MIAQM. His educational foundation has enabled extensive collaboration with governmental bodies including Defra, Devolved Administrations, South African government, Irish EPA, European Environment Agency, and European Commission. His research focuses on Air Quality Management, carbon management, emission inventories, dispersion modeling, bioaerosols, water-energy-food nexus, Water Security, and ammonia emissions. Recent work demonstrates interdisciplinary approaches combining environmental science with social dimensions of pollution management. He has particular expertise in urban air quality, agricultural emissions, and health impacts of traffic-related pollution. Analysis of Dr. Hayes' 136 publications reveals evolving research trajectories from technical emission modeling toward integrated socio-technical approaches. His recent work (2023-2025) shows strong emphasis on citizen science applications, health impacts (especially on children), advanced air quality forecasting techniques, and the psychological dimensions of climate decision-making. A consistent theme across his publications is bridging technical environmental solutions with social equity considerations. Dr. Hayes leads significant research initiatives including the Horizon 2020 ClariCity Project as Technical Director, the AmmoniaN2K Project with University College Dublin and Irish EPA, multiple NERC-funded bioaerosol studies, and European Commission support on Ambient Air Quality Directive review. His projects consistently integrate scientific rigor with practical policy applications and community engagement.

• Air Quality Management
• Carbon Management
• Emission Inventories
• +۷ مورد دیگر

Theodore Kypraios is a Professor of Statistics at the School of Mathematical Sciences, University of Nottingham, United Kingdom. He serves as Course Director for the MSc in Statistics and MSc in Statistics with Machine Learning programmes, and as Head of the Statistics and Probability Section. Kypraios joined the University of Nottingham in September 2006 as a Research Fellow and was appointed as Lecturer in 2008. His research focuses on developing novel statistical methodology for Bayesian inference and model selection for high-dimensional complex data, with particular emphasis on stochastic epidemic models and infectious disease outbreak data. Kypraios has made significant contributions to Bayesian nonparametric methods, as evidenced by his PNAS publication on heterogeneously mixing infectious disease models which enables more data-driven approaches to understanding transmission mechanisms without strict parametric assumptions. Kypraios has been actively involved with the Royal Statistical Society, serving as Chair of the Computational Statistics and Machine Learning Section until December 2020, and currently sits on the Academic Advisory Group committee. He has presented his work at major conferences including the International Symposium for Bayesian Analysis and the Bayesian Inference for Stochastic Processes Workshop. As an educator, Kypraios has taught Statistical Inference and Data Analysis and Modelling modules at Nottingham, and has been an instructor for the 'MCMC II for Infectious Diseases' module at the Summer Institute in Statistics and Modeling in Infectious Diseases since 2010. His teaching emphasizes both classical and Bayesian approaches to statistical inference with applications to real-world problems. He has supervised PhD students including Dr. Rowland Seymour, whose thesis work formed the basis of the PNAS publication. His research has practical implications for understanding disease transmission mechanisms, as demonstrated by his analysis of the 2001 UK foot and mouth disease outbreak, and contributes to the development of more effective disease control strategies.

• Bayesian Inference
• Statistical Methodology
• Infectious Disease Modeling
• +۵ مورد دیگر