جست‌وجوی استاد و پژوهشگر

Daniel Richardsمشاهده پروفایل

مدرس

• Design Innovation
• Digital Ethics
• Sustainable Technologies
• +۵ مورد دیگر

Dr. Daniel Richards is a Lecturer in Data Prototyping and Visualisation at the Lancaster Institute for the Contemporary Arts (LICA), part of the Faculty of Arts and Social Sciences (FASS) at Lancaster University. His research focuses on speculative design, digital ethics, sustainable technologies, and innovation ecosystems. He explores provocative concepts such as 'Good Digital Identities' and 'Disruptive Innovation Ecosystems,' emphasizing co-creation and ethical technology integration. Key projects include the Digital Good Network (2022–2027), investigating equity and sustainability in digital relationships, and Qualified Selves (2019–2020), examining post-big data meaning-making. He also leads the Chatty Factories initiative (2018–2021), reimagining IoT-driven manufacturing. Richards has received the FASS Staff Award for Early Career Researcher of the Year and engages in public outreach through exhibitions like the Festival of Futures and workshops such as Speculative Woolgathering . His work bridges art, design, and technology, addressing societal challenges through speculative and participatory methods. He collaborates with interdisciplinary research groups including DSI - Society , Imagination Lancaster , and the Worldbuilding collective, fostering cross-disciplinary innovation. His activities span invited talks on AI in design, business engagement with Stratasys , and academic committee roles.

• Cognitive Neuroscience
• Inner Speech
• Auditory Verbal Hallucinations
• +۶ مورد دیگر

Dr Bo Yao is a Senior Lecturer at Lancaster University's Department of Psychology, Fylde College. His research focuses on the cognitive neuroscience of language and inner speech, exploring neural mechanisms underlying inner speech's role in cognition and mental health. He employs methods like EEG, fMRI, eye tracking, and computational modeling. Yao supervises 4 postgraduate students and leads the Language, Inner Speech, and Neuroscience (LISN) Lab. Research Interests: Inner speech's neural basis, auditory verbal hallucinations, embodied cognition, and psycholinguistics. Recent work examines rhythmic foundations of thought and emotional processing in language. His 2025 publications highlight innovations in parafoveal preview benefits and predictive coding frameworks. Publications span cognitive neuroscience, psycholinguistics, and neuroimaging, with a focus on reading comprehension, speech processing, and emotional word analysis. His work bridges phenomenological experience with neural mechanisms, using meta-analyses and experimental paradigms. Advising and Labs: Supervises students in language cognition and inner speech research. The LISN Lab develops interdisciplinary approaches to understand language and consciousness.

Harita Dellaportaمشاهده پروفایل

پژوهشگر

• Robust Bayesian Inference
• Model Misspecification
• Distributionally Robust Optimization
• +۳ مورد دیگر

Harita Dellaporta is a postdoctoral researcher in the Department of Statistical Science at University College London (UCL), working with Dr. François-Xavier Briol. Previously, she completed her PhD at the University of Warwick under Prof. Theo Damoulas, focusing on robust Bayesian inference and distributionally robust optimization. Her research addresses model misspecification challenges, with applications in Bayesian methods, optimization, and simulator-based models. Education: PhD (2025), CDT in Mathematics and Statistics, University of Warwick MSc (2020), Computational Statistics and Machine Learning, University College London BSc (2019), Mathematics, University of Warwick Research Interests: Her work emphasizes robust methodologies to handle model misspecification, including robust Bayesian inference, distributionally robust optimization (DRO), and measurement error correction. She also explores applications in simulator-based models and exponential family distributions. Recent Work Trends: Her publications focus on integrating Bayesian methods with DRO frameworks, addressing decision-making under uncertainty, and developing robust statistical tools for complex models. Notable contributions include advancements in ambiguity sets for DRO and MMD-based posterior bootstrapping for simulator-based inference. Awards: Best Paper Award at AISTATS 2022 Teaching & Engagement: Exercise classes for STAT0043 (Inference at Scale) at UCL (2024–2025) Previously taught probability modules at the University of Warwick Active presenter at workshops and conferences, including talks at NeurIPS, PHYSTAT-SBI, and the Alan Turing Institute Labs & Groups: Member of UCL’s Fundamentals of Statistical Machine Learning group and previously part of Warwick’s Machine Learning Group.

• Climate Science
• Environmental Data Management
• Geographic Information Systems (GIS)
• +۳ مورد دیگر

Jon Blower is an academic affiliated with the University of Reading's Department of Geography and Environmental Science. His work focuses on climate data management, environmental data visualization, and geospatial technologies. He has contributed to projects like the C3S ECEM climate service, the CHARMe metadata initiative, and the GODIVA2 web mapping system. His research spans cloud computing applications in environmental science, oceanographic data dissemination, and urban density analysis. He has authored over 40 peer-reviewed publications and technical reports, including foundational work on Climate Forecast metadata conventions and cloud-based GIS systems. Blower has led interdisciplinary efforts in integrating environmental data quality frameworks and developing open-source tools for geospatial analysis. Education & Background: While specific educational details are not explicitly stated, his extensive contributions to environmental science and computing imply advanced training in these fields. His work often bridges computer science and environmental applications, suggesting a multidisciplinary academic background. Research Focus: Key areas include: Data interoperability standards (e.g., CF metadata conventions) Climate service development for energy policy Interactive environmental data visualization systems Cloud computing for large-scale environmental datasets Oceanographic data synthesis and quality frameworks Recent Trends in Publications: Recent work emphasizes urban systems analysis (2023), renewable energy-climate integration (2018), and cloud infrastructure for environmental science (2014/2016). Earlier contributions focused on ocean data systems (2009-2012) and grid computing for climate modeling (2006-2009). Awards & Grants: No specific awards listed, but his sustained contributions to major projects like GODAE and MELODIES reflect institutional recognition. Active in grant-funded initiatives related to environmental data infrastructure. Labs/Teams: Collaborates with teams at the National Oceanography Centre, NASA, and European climate initiatives. Core contributor to projects managed by organizations like ESA and the UK's Natural Environment Research Council (NERC).

Omduth Cocealمشاهده پروفایل

پژوهشگر ارشد

• Turbulence and Dispersion
• Boundary-Layer Meteorology
• Urban Meteorology
• +۱ مورد دیگر

Dr. Omduth Coceal is a Research Fellow in the Department of Meteorology at the University of Reading. His research focuses on turbulence and dispersion processes, boundary-layer meteorology, urban meteorology, and air quality. He leads projects like Next Generation Cities (NGC) and HighResCity, addressing urban climate challenges. Current research includes DIPLOS (dispersion in street networks) and GREYBLS (boundary layer modeling). Key research interests involve atmospheric dispersion modeling in urban environments, pollutant transport mechanisms, and the impact of urban structures on airflow. His work combines numerical simulations and field observations to improve understanding of environmental and health risks in cities. Recent publications emphasize urban street canyon dynamics, airborne disease transmission, and convective boundary layer processes. Coceal collaborates widely, contributing to international efforts like the ClearfLo project on London's air quality and health linkages. He advises PhD student George Gunn and maintains active roles in meteorological communities.

• Machine Learning
• Biomedical Engineering
• Medical Imaging
• +۵ مورد دیگر

Professor Anil Bharath holds the role of Professor of Biologically-Inspired Computation & Inference in the Department of Bioengineering at Imperial College London. He serves as Academic Director of Imperial Global: Singapore and co-leads the IN-CYPHER research program on AI-driven healthcare security. His research focuses on machine learning, deep networks, and biomedical applications. He earned his BEng from UCL and PhD from Imperial College, followed by roles including President of the City and Guilds College Association (2022-2024). Research Interests: Machine learning, neural networks, medical imaging, and biologically-inspired computation. Notable contributions include 2D steerable filters for shape detection (1998), Bayesian marginalisation in early computer vision, and deep learning for cardiac MRI analysis. He co-founded Cortexica Vision Systems (acquired by Zebra Technologies in 2019), applying biological neuron models to visual search technology. Labs & Affiliations: Director of the BICI Lab, affiliated with the Data Science Institute, Centre for Neurotechnology, and multiple healthcare networks. His work spans interdisciplinary projects in AI for healthcare, cardiovascular engineering, and medical device innovation. Publications: Recent work emphasizes AI in cardiology (e.g., MRI analysis for mitral regurgitation, aortic stenosis detection) and synthetic data privacy. His research bridges computational models with clinical interpretability, addressing challenges in medical imaging efficiency and diagnostic accuracy.

Alessandro De Rosisمشاهده پروفایل

مدرس ارشد

• Multiphysics Modelling
• Lattice Boltzmann Method
• Fluid-Structure Interaction
• +۳ مورد دیگر

Alessandro De Rosis is a Senior Lecturer in Virtual Engineering at the University of Manchester’s Mechanical and Aerospace Engineering department. His research focuses on multiphysics modeling using the lattice Boltzmann method (LBM), with applications in fluid-structure interaction, magnetohydrodynamics, and biomedical engineering. He holds a PhD in Structural and Hydraulic Engineering from the University of Bologna and a Master’s in Civil Engineering from the University of Calabria. His postdoctoral work included a PRESTIGE grant-funded period at the Laboratoire de Mécanique des Fluides et Acoustique, developing LBM algorithms for high-Reynolds magnetohydrodynamic flows. Key research areas include computational fluid dynamics (CFD) modeling of cardiovascular devices, such as LVAD outflow graft positioning to reduce aortic regurgitation, and coupled finite-volume/LBM methods for internal flows. He has contributed to over 60 peer-reviewed publications, with recent work spanning biomedical engineering, plasma physics, and environmental fluid dynamics. Collaborations include the Fluids Research Group at the University of Manchester and institutions like the Technion-Israel Institute of Technology. Education: PhD in Structural and Hydraulic Engineering (2013), University of Bologna Master of Engineering in Civil Engineering (2009), University of Calabria His research bridges theoretical physics and engineering applications, emphasizing multiphase flows, CFD-driven surgical optimization, and high-performance numerical simulations. Current projects address challenges in mechanical circulatory support devices, fluid-structure interaction in biomedical systems, and magnetohydrodynamic turbulence modeling.

Timothy Drysdaleمشاهده پروفایل

استاد

• Remote Laboratories
• Engineering Education
• Electromagnetics
• +۲ مورد دیگر

Timothy Drysdale is Professor and Chair in Technology Enhanced Science Education at the University of Edinburgh, where he directs the Remote Laboratories group and serves as Director of Strategic Digital Education. His practable.io platform revolutionizes laboratory education through aesthetically-designed remote experiments installed in campus foyers, saving physical space while enhancing accessibility. Research develops novel remote labs based on experiments likened to "science museum exhibits," integrating real-time equipment access via web interfaces. Additional work explores orbital angular momentum in radio communications. His £3M openEngineering Laboratory project received multiple honors including the Queen's Anniversary Prize and THE Digital Innovation Award. Global Online Laboratories Consortium Award (2024, 2018) Queen's Anniversary Prize (2024) Jisc Digital Transformation Award (2023) Guardian Teaching Excellence Award (2018) Teaches across undergraduate engineering programs and supervises doctoral projects in digital education innovation. Advocates for assessment transformation and generative AI integration in education.

• Tidal Energy
• Hydrodynamics
• Renewable Energy Systems

Brian Sellar is a Reader at the University of Edinburgh's School of Engineering, focusing on tidal energy, hydrodynamics, and turbine performance. He holds a PhD and accepts PhD students. His research includes validating tidal turbine models, multi-scale coastal ocean modeling, and turbulence analysis for renewable energy sites. He received the MDPI Energies Editor’s Choice Award in 2021. His work contributes to optimizing tidal energy systems and advancing ocean engineering methodologies.

Michael Templetonمشاهده پروفایل

استاد

• Environmental Engineering
• Infectious Diseases
• Public Health Engineering
• +۶ مورد دیگر

Professor Michael Templeton is a leading academic in Public Health Engineering at Imperial College London , affiliated with the Faculty of Engineering and the Department of Civil and Environmental Engineering . He also holds the Royal Academy of Engineering Research Chair in Global Sanitation Technology , working closely with organizations like Oxfam , Water For People , and the International Worm-Based Sanitation Association . His work addresses critical issues in water supply , sanitation , and public health , particularly in regions affected by schistosomiasis and water scarcity . Professor Templeton earned a Bachelor's degree with honours in Engineering Science and a PhD in Civil-Environmental Engineering , both from the University of Toronto . He is a chartered civil engineer , Fellow of the Institution of Civil Engineers , and elected Fellow of the African Academy of Sciences . His professional experience includes advisory roles for the World Health Organization , Ethiopian Federal Ministry of Health , and various research councils. Environmental Engineering : Water treatment Infectious Diseases : Schistosomiasis control Global Health : Sanitation in low-income settings Climate Resilience : Cold region sanitation Waste Valorization : Biochar from faecal sludge Diagnostic Innovation : Biosensors for pathogens His most recent research explores stormwater odorants , UV disinfection , and smartphone-based water quality monitoring . He has also advanced tiger worm toilets and citizen science approaches in data-scarce regions. His work spans 15 countries including Ghana , Sierra Leone , India , and Ethiopia . Scientific awards and honors include: Fellow of the Institution of Civil Engineers Elected Fellow of the African Academy of Sciences Royal Academy of Engineering Research Chair Professor Templeton has no listed students in the provided data but has contributed extensively to sanitation innovation , waterborne disease prevention , and capacity-building in developing nations. He has led field projects and published on vermifiltration systems , biochar production , and disinfection byproducts .

• Artificial Intelligence
• Image Processing
• Medical Imaging
• +۳ مورد دیگر

Dr Ahmed Fetit is a Senior Lecturer and Senior Teaching Fellow at Imperial College London's Department of Computing (Faculty of Engineering), specializing in AI for Healthcare through the UKRI Centre for Doctoral Training. His research focuses on applying machine/deep learning to medical imaging, particularly in collaboration with NHS Trusts. He holds a PhD from the University of Warwick (2015) and degrees from the University of Birmingham (MSc, BEng). He is a Fellow of the Higher Education Academy (FHEA). Education: PhD: University of Warwick (2015), applications of machine learning to tumor diagnosis/prognosis via MRI MSc: University of Birmingham BEng (Hons): University of Birmingham Research Interests: Ahmed's work bridges AI and healthcare, emphasizing medical imaging applications such as MRI segmentation, adversarial robustness, fetal brain connectivity analysis, and retinal biomarker discovery. His projects often involve NHS collaborations to translate AI innovations into clinical practice. Recent Article Trends: Recent publications highlight advancements in CNN robustness (e.g., k-space artifact simulation), fetal/neonatal brain segmentation, and XAI explanations in healthcare imaging. His work also explores cross-modal MRI inference and cardiovascular risk stratification using retinal features. Awards: Fellow of the Higher Education Academy (FHEA) Advising & Grants: While specific grant details are not listed, his NHS collaborations imply involvement in funded healthcare AI projects. No advisees are explicitly mentioned. Labs/Teams: Active in the UKRI CDT in AI for Healthcare and the Department of Computing's Neuroimaging research groups.

Joseph Robsonمشاهده پروفایل

استاد

• Physical Metallurgy
• Alloys for Extreme Environments
• Microstructural Modeling
• +۸ مورد دیگر

Prof. Joseph Robson holds the RAEng-DSTL Chair in Alloys for Extreme Environments and is a Professor of Physical Metallurgy at the University of Manchester. His research focuses on microstructural evolution in industrial alloys, particularly aluminum, magnesium, and zirconium, using advanced modeling techniques like Calphad-based thermodynamic and kinetic models. He leads the Light Alloy Processing group and collaborates with institutions like the Henry Royce Institute. Key projects include optimizing microstructures for aerospace, automotive, and nuclear applications through processes like friction stir welding and thermomechanical treatment. Education: BSc in Natural Sciences (Cambridge, 1993), PhD in Metallurgy (Cambridge, 1996). Professional memberships include the Institute of Materials, Minerals and Mining (Fellow, Light Metals Division board member). Research interests span dynamic precipitation behavior, irradiation effects on zirconium alloys, and magnesium alloy strengthening. He has pioneered studies on discontinuous precipitation and its impact on material properties. Awards include the Hume Rothery Award (2015), Grunfeld Medal (2011), and Champion H. Matthewson Award (2017). Advising and grants: Leads major projects like LightForm (EPSRC) and NEWAM (innovative manufacturing). His work addresses challenges in alloy design for extreme environments, with a focus on sustainable materials and advanced processing techniques. Labs/Teams: Active in the Materials Performance Centre and collaborates with industry partners such as Magnesium Elektron and Westinghouse on nuclear materials research.

• Subsurface Physics
• Carbon Capture and Storage (CCS)
• Reservoir Engineering
• +۵ مورد دیگر

Professor Ann Muggeridge holds the Proconsul & Chair in Subsurface Physics at Imperial College London's Department of Earth Science & Engineering (Faculty of Engineering). Her research focuses on subsurface fluid flow dynamics, particularly CO2 storage security and reservoir physics. She has held prestigious roles including Chair of the Norwegian IOR Centre's Scientific Advisory Committee (2016-2021) and Technical Committee member for SPE Reservoir Simulation Conferences. Education: D.Phil. in Atmospheric Physics from University of Oxford (1983-1986), B.Sc. (Hons) in Physics from Imperial College London (1980-1983). Professional milestones include BP Technology Fellow (2006-2008) and keynote addresses at major geoscience conferences. Research interests span CO2 geological storage, reservoir heterogeneity effects, and enhanced oil recovery (EOR). Key contributions include dynamic risk mapping for CO2 sites and pore-scale observations of low salinity flooding. Her work integrates computational modeling with field-scale studies to address energy transition challenges. Awards: EAGE IOR Symposium Chair (2013-2019), SPE Technical Committee Member, BP Technology Fellow Labs & Teams: NORMS (Novel Reservoir Modelling & Simulation), Energy Futures Lab Affiliate Grants & Advising: Leads Imperial's Subsurface Physics research group; no listed advisees but mentors through collaborative projects Active in academia as Imperial's Faculty of Engineering Ambassador for Women and Departmental Athena SWAN coordinator, advancing gender equity in STEM.

Aliah Hawariمشاهده پروفایل

پژوهشگر

• Cancer Genomics
• Computational Biology
• Metabolic Modeling
• +۳ مورد دیگر

Aliah Hawari is a Researcher in the Division of Cancer Sciences at the University of Manchester, affiliated with the Manchester Cancer Research Centre. She holds a PhD in Metabolic Modelling of Tomato Fruit Ripening from Oxford University (2010-2014), an MSc in Metabolic Modelling of Terpenoid Biosynthetic Pathways from Universiti Kebangsaan Malaysia (2007-2009), and a BSc in Bioinformatics (2003-2006). Her research focuses on computational biology, cancer genomics, and systems biology, with emphasis on early cancer detection in BRCA1/2 carriers through molecular profiling. Key areas include kinetic modeling, metabolic pathways, and ensemble modeling techniques. She actively supervises PhD students exploring topics like contralateral breast tissue analysis in genetic cancer predisposition. Recent work includes groundbreaking genomic analyses of colorectal cancers and advanced in silico models of biochemical pathways. Her contributions to defining informative priors for ensemble modeling have been widely adopted in systems biology research. Affiliated with the Manchester Cancer Research Centre and Healthier Futures initiative, her work aligns with global health goals in precision oncology and molecular diagnostics.

Moulay Larbi Chalalمشاهده پروفایل

مدرس ارشد

• Urban Energy Planning
• Building Information Modeling (BIM)
• Sustainable Design
• +۳ مورد دیگر

Dr. Moulay Larbi Chalal is a Senior Lecturer in Architectural Technology at Nottingham Trent University’s School of Architecture Design and the Built Environment. He holds a PhD in Architecture from NTU (2018) and a Master’s with Distinction in Digital Architectural Design from Salford University. His academic responsibilities include curriculum design, studio instruction, and research supervision in architectural technology modules. Chalal’s research integrates computational design with sustainability, focusing on: Urban energy planning using GIS and BIM Generative algorithms for architectural optimization Eco-feedback systems for behavioral change Smart city infrastructure and autonomous vehicles His publications demonstrate a consistent focus on energy pattern analysis, sustainable urban development, and digital innovation in construction. Recent work explores AI applications in education and energy visualization frameworks. Awards & Recognition: Emerald Award for Best Master’s Dissertation (Salford University, 2013) NTU Vice Chancellor’s Scholarship for PhD research (2014) He advises doctoral candidates (e.g., F. Mekheimar’s work on digital archaeology) and collaborates with industry partners including Nottingham Energy Partnership and SETART Group. Chalal leads projects in NTU’s Creative and Virtual Technologies Research Lab, developing tools for sustainable urban planning.