جست‌وجوی استاد و پژوهشگر

Michael O'Boyleمشاهده پروفایل

استاد

• Heterogeneous Code discovery and Optimisation
• Neural Machine Translation and Neural Synthesis
• Deep Neural Network system stack
• +۷ مورد دیگر

Michael O'Boyle is a Professor at the University of Edinburgh's School of Informatics, where he serves as Director of the ARM Research Centre of Excellence and the EPSRC Centre for Doctoral Training in Pervasive Parallelism. Holding an EPSRC Established Career Research Fellowship, he leads pioneering work in compiler technology for heterogeneous architectures, bridging theoretical advances with practical high-performance computing applications. Professor O'Boyle's research spans multiple cutting-edge areas including heterogeneous code discovery and optimization, neural machine translation for program synthesis, deep neural network system stack optimization, software-defined hardware, and compiler/architecture co-design. His approach integrates constraint analysis, program synthesis, and machine learning to address complex challenges in high-performance computing across diverse hardware platforms. His recent publications reveal a strong trend toward integrating machine learning with traditional compiler techniques, particularly in neural program synthesis, tensor optimization, and architecture-aware compilation. This work represents a paradigm shift in compiler design, moving from rule-based systems to learning-based approaches that can automatically adapt to diverse hardware targets. IEEE/ACM CGO 2025 Distinguished Paper Award for 'Tensorize: Fast Synthesis of Tensor Programs from Legacy Code' IEEE/ACM CGO 2024 Test of Time Award ACM GPCE 2023 Best Paper Award for 'C2TACO: Lifting Tensor Code to TACOM' ACM ASPLOS 2021 Distinguished Paper Award IEEE HPCA 2021 Best Paper Award for 'Prodigy: Improving the Memory Latency of Data-Indirect Irregular Workloads' Professor O'Boyle has successfully mentored numerous PhD students who have secured prominent positions in academia (including at Cambridge, Edinburgh, Leeds, and McGill) and industry (including Meta, NVIDIA, Qualcomm, Huawei, and Microsoft). His research is supported by significant funding from EPSRC, ARM, and European projects including Bonseyes and Transmuter, demonstrating strong international recognition and industry impact. He leads the influential Compiler and Architecture Design (CArD) Group at the University of Edinburgh and is a founder of the HiPEAC Network of Excellence, which has grown into a major European initiative connecting researchers and practitioners in high-performance and embedded computing.

Rogério de Lemosمشاهده پروفایل

مدرس ارشد

• Resilient AI
• Self-adaptive software systems
• Authorisation infrastructures
• +۷ مورد دیگر

Rogério de Lemos is a Senior Lecturer in Computing Science and Director of Postgraduate Research (PGR) at the School of Computing, University of Kent. He previously served as an invited assistant professor at the University of Coimbra, Portugal, and as a Senior Research Associate at the Centre for Software Reliability (CSR) at the University of Newcastle upon Tyne, UK. Dr. de Lemos' research focuses on architecting resilient systems, particularly in resilient AI, self-adaptive software systems, and authorization infrastructures. He belongs to both the Programming Languages and Systems Group and the Cyber Security Group at the University of Kent. His specific research interests include: Software engineering for self-adaptive systems assurances and resilience evaluation Dynamic generation of processes Handling insider threats using self-adaptive authorization Architectural abstractions for fault tolerance Verification and validation of dependable software architectures Software development for safety-critical systems Dependability and bioinspired computing His publication trends show increasing emphasis on practical applications of self-adaptive systems in cyber security contexts, with recent work spanning network traffic analysis, cryptographic function detection, and cloud-edge security architectures. His research bridges theoretical foundations with practical implementations, particularly in cyber security and resilient systems architecture. Dr. de Lemos currently leads the "Collaborative and Confidential Information Sharing and Analysis for Cyber Protection" project funded by the European Union's Horizon 2020 Programme. His past projects include "ADAAS: Assuring Dependability in Architecture-based Adaptive Systems" and multiple collaborations with NCR on sensor fusion and fault tolerance. As Director of Postgraduate Research, he oversees the School of Computing's research degree programs and likely supervises PhD students in resilient systems and cyber security, though specific student names are not listed in the available information.

• Electrical and Electronic Engineering
• Computer Hardware
• Computer Software
• +۷ مورد دیگر

Professor Peter Y. K. Cheung is a Professor of Digital Systems at Imperial College London, holding dual affiliations within the Department of Electrical and Electronic Engineering and the Dyson School of Design Engineering. His work focuses on reconfigurable systems, FPGA architectures, and high-level synthesis tools. He co-founded one of the UK's leading FPGA research groups with Professor Wayne Luk, addressing challenges in variability mitigation, reliability, and application-specific FPGA deployments. His research spans Field-Programmable Gate Arrays (FPGAs) Reconfigurable computing Neural network acceleration Cryptographic protocols Embedded systems He has pioneered techniques such as logic shrinkage for FPGA-based neural networks and developed frameworks like LUTNet for efficient inference. His contributions also include fault-tolerant FPGA designs and methodologies for distributed computation protocols. Key collaborations include work with the Department of Computing on FPGA-based AI acceleration and cybersecurity applications. His recent work explores edge computing, secure decentralized systems, and pandemic modeling using adaptive control strategies. Notable projects include the DSCS protocol for secure distributed computation, acceleration of gravitational wave detection algorithms, and energy-efficient CNN implementations. His research bridges hardware-software co-design with real-world applications in healthcare, finance, and aerospace.

• Software Engineering
• Graph Transformation Systems
• Model-Based Development
• +۵ مورد دیگر

Reiko Heckel is a Professor of Software Engineering at the University of Leicester, serving as Director of Postgraduate Teaching for Computing degrees and Data Analytics Lead at the Leicester Innovation Hub. She previously held academic roles at the Technical Universities of Dresden and Berlin before joining Leicester in 2004. Her research focuses on graph transformation systems, model-based development, stochastic modeling, and formal methods in software engineering. She earned her PhD (Dr.-Ing.) in Computer Science from TU Berlin in 1998. Her research interests span software engineering pedagogy, formal specification techniques, and applications of graph grammars in system modeling. Recent work explores stochastic graph transformations for social networks, transparency engineering in AI systems, and blockchain-based smart contract frameworks. Her contributions bridge theoretical foundations with practical applications in cybersecurity, data integration, and human-centric systems design. Key contributions include advancements in automated test case generation via graph transformations, visual contracts for software reverse engineering, and formal methods for complex system analysis. Her work frequently intersects with industry through collaborations via the Leicester Innovation Hub, emphasizing data analytics and technology transfer. Education: MSc Computer Science, Technical University of Dresden PhD (Dr.-Ing.), Computer Science, TU Berlin (1998) Leadership Roles: Head of Department (2014-2018) Director of Postgraduate Teaching (Ongoing) Research Themes: Model-Based Development Stochastic Systems Analysis Graph Neural Networks Trustworthy AI Her publications reflect a focus on formal methods, with recent trends in applying graph transformation techniques to social network modeling, blockchain smart contracts, and educational pedagogy.

Philip Kirbyمشاهده پروفایل

مدرس ارشد

• History of Education
• Education Policy
• Disability Studies
• +۳ مورد دیگر

Dr. Philip Kirby is a Senior Lecturer in the History of Education at King’s College London’s School of Education, Communication & Society. He joined in 2020 after roles at the University of Oxford, the Sutton Trust, and the University of Exeter. His research focuses on the historical and social dimensions of specific learning difficulties like dyslexia and dyspraxia, alongside children’s culture and education policy. His notable work includes Dyslexia: A History (2022, co-authored with Prof. Margaret J. Snowling) and entries in encyclopedias like Palgrave Encyclopedia of Disability . He also explores geopolitical themes in media, including film scores and video games. Recent projects include Delphi studies on dyslexia assessment and policy reform. His research spans education policy, private tuition dynamics, and the intersection of popular culture with disability ethics. He actively contributes to interdisciplinary initiatives like the Centre for Public Policy Research, addressing social justice in education and policy.

Cecilia Mascoloمشاهده پروفایل

استاد

• Mobile Systems
• Wearable Computing
• Machine Learning
• +۵ مورد دیگر

Cecilia Mascolo is a Professor of Mobile Systems at the University of Cambridge , specifically in the Department of Computer Science and Technology . She co-directs the Centre for Mobile, Wearable System and Augmented Intelligence and is a Fellow of Jesus College, Cambridge . Her research focuses on mobile systems , machine learning for mobile health , and earable technology . She has been awarded prestigious grants such as the ERC Advanced Research Grant (2019-2025) and the EPSRC Open Research Fellowship (2025-2030). Currently on sabbatical at Harvard University , her work bridges systems and machine learning for health applications. Education: PhD in Computer Science from the University of Bologna, Italy. Previous Affiliation: Faculty at University College London before 2008. Her research spans mobile and wearable systems for health and behavior monitoring, focusing on on-device machine learning , uncertainty-aware models , and audio-based diagnostics . Key areas include federated learning , edge computing , and respiratory disease progression analysis via wearables. She explores earable technology for physiological monitoring, gait analysis, and even toothbrushing tracking using in-ear sensors. Her recent publications highlight advancements in earable-based health monitoring , including heart rate estimation , respiratory rate detection , and ECG analysis using machine learning. She emphasizes longitudinal health data from consumer devices, advocating for scalable diagnostics beyond traditional clinical standards. Scientific Awards: ERC Advanced Research Grant EPSRC Open Research Fellowship Best Paper Award - IEEE Percom 10-Year Impact Award - ACM Ubicomp Computer Laboratory Ring Hall of Fame Best Paper Award Student: Andrea Ferlini - ACM SIGMOBILE Doctoral Dissertation Runner-up She leads the Mobile Systems Research Laboratory , mentoring a team of 15 researchers (postdocs and PhD students), and has graduated over 25 PhD students. Her teaching includes Mobile Health courses at the University of Cambridge, and she serves as Director of Studies for Computer Science at Jesus College.

Xin Zhouمشاهده پروفایل

پژوهشگر ارشد

• Computational Biology
• Health Informatics
• Cardiovascular Disease Modeling
• +۳ مورد دیگر

Dr. Xin Zhou is an Oxford-Bristol Myers Squibb Fellow at the Department of Computer Science, University of Oxford. Her research integrates computational modeling, clinical data, and experimental findings to investigate cardiac disease mechanisms and develop human-based simulations for drug evaluation. BSc and MSc in Life Sciences, Beijing Normal University DPhil in Computational Biology, University of Oxford Her work focuses on multi-scale cardiac modeling , particularly in ischemic heart disease and heart failure, exploring ionic currents, tissue conduction, and organ-level dynamics. She develops electromechanical simulations to study cardiac alternans and arrhythmic risks, translating these into clinical applications for patient stratification and pharmaceutical testing. Recent publications emphasize in silico clinical trials , sex-specific cardiometabolic analysis, and Purkinje network modeling. Collaborative efforts with clinicians and pharmaceutical partners highlight her translational approach to regulatory science. Model of the Year 2024, BioModels EPSRC Impact Acceleration Account Microsoft Research Project Award Recognition Award, University of Oxford She supervises PhD and MSc students in computational cardiology, while serving on the editorial board of Frontiers in Physiology . Her current projects involve digital twinning and predictive cardiac safety models to reduce animal testing reliance.

• Computational Biology
• Health Informatics
• Machine Learning
• +۳ مورد دیگر

Julia Camps is a postdoctoral research associate at the University of Oxford, Department of Computer Science. Her work bridges Computational Biology and Health Informatics, focusing on cardiac digital twin development for precision medicine applications. She specializes in combining data-driven and mechanistic approaches for in silico clinical trials, particularly through Purkinje network modeling and ECG-based calibration. Education: Informatics Engineer (2014) and Master's in Artificial Intelligence (2015-2017) from Universitat Politècnica de Catalunya PhD in Computer Science (2017-2021) at Oxford, completed within the Computational Cardiovascular Science research group under Prof Blanca Rodriguez Current role: postdoc in Prof Rodriguez's group since 2021, focusing on post-myocardial infarction disease progression Software development: open-source cardiac digital twin tools available on GitHub Her research interests center on creating patient-specific cardiac digital twins using multimodal clinical data. This work enables virtual therapy evaluation and in silico clinical trials through: Integration of statistical inference and machine learning techniques Development of Purkinje network models from clinical ECG data Electrophysiological and repolarization sequence modeling Gait detection algorithms for Parkinson's disease applications Recent publications (2024-2025) demonstrate trends in: GPU-accelerated cardiac electrophysiology simulations (MonoAlg3D) Topology-informed ECG electrode localization Sex-specific electromechanical cardiac modeling Multi-modal characterisation of diabetic cardiac deterioration Pro-arrhythmic risk assessment for stem cell therapies

Stephanie Archerمشاهده پروفایل

دانشیار

• Cancer Risk Prediction
• Digital Health Interventions
• Patient Experience Research
• +۲ مورد دیگر

Dr. Stephanie Archer is an Associate Professor and Senior Research Associate at the University of Cambridge, jointly affiliated with the Department of Psychology and the Department of Public Health and Primary Care. Her work bridges psychological science with clinical applications, particularly in cancer risk assessment and digital health interventions. Dr. Archer holds a BSc, MSc, and PhD, though specific institutions are not mentioned in available sources. Her educational background has prepared her for interdisciplinary research at the intersection of psychology, public health, and clinical medicine. Her research focuses on three primary areas: designing multifactorial cancer risk prediction tools for clinical settings; exploring patient and staff experiences of health and social care; and developing/testing digital health interventions. She employs qualitative methods extensively while also engaging with quantitative approaches for comprehensive health services research. Her work demonstrates strong translational focus, moving from theoretical frameworks to practical clinical applications. Analysis of Dr. Archer's recent publications reveals a consistent trajectory in cancer risk prediction tools (particularly CanRisk), patient experience research across multiple conditions, and implementation science for digital health interventions. Her work spans breast, ovarian, prostate, and other cancers while also addressing mental health in autistic populations and patient safety in surgical settings. The interdisciplinary nature of her research connects psychology with oncology, primary care, and public health. Dr. Archer actively contributes to clinical guidelines development, as evidenced by her involvement in the Joint ABS-UKCGG-CanGene-CanVar consensus regarding CanRisk implementation. Her research methodology combines qualitative depth with mixed-methods approaches to address complex healthcare challenges. As a Senior Research Associate and Associate Professor, Dr. Archer likely supervises PhD students and early-career researchers, though specific advisees are not documented in available sources. Her teaching interests include health psychology, health services research, qualitative methods, and intervention development. Dr. Archer collaborates across multiple research units at Cambridge, including the Primary Care Unit and likely the Centre for Cancer Genetic Epidemiology, reflecting her interdisciplinary approach to improving cancer risk assessment and patient care pathways.

Dimitris Kolovosمشاهده پروفایل

استاد

• Automated and Model-Based Software Engineering
• Model-Driven Software Engineering
• GenAI for Software Engineering
• +۴ مورد دیگر

Roles and Affiliations : Dimitris Kolovos is a Professor of Software Engineering at the University of York's Department of Computer Science. He leads the Automated Software Engineering (ASE) research group and is an Eclipse Foundation committer, leading development of the Epsilon open-source platform. His roles include research leadership, teaching, and academic service. Education : PhD in Software Engineering - University of York MSc in Software Engineering with Distinction - University of York First Class Honours Degree in Informatics - Athens University of Economics and Business Research Interests : Kolovos focuses on advancing Model-Driven Engineering (MDE), GenAI integration in software development, low-code platforms, and data analytics. His work emphasizes scalable modeling tools, education technology (e.g., MDENet platform), and industry collaboration with organizations like NASA, BAE Systems, and Siemens. Labs and Projects : He leads the Epsilon project under the Eclipse Modelling initiative, developing tools for model transformation, validation, and code generation. His research group also explores AI-driven model transformations and hybrid graphical-textual editors.

John Wickersonمشاهده پروفایل

دانشیار

• Computer Hardware
• Electrical and Electronic Engineering
• Computer Software
• +۷ مورد دیگر

Dr. John Wickerson is an Associate Professor in the Circuits and Systems group at the Department of Electrical and Electronic Engineering, Imperial College London. His research focuses on improving the reliability of high-performance computing through formal methods, with contributions to high-level synthesis, memory models, and concurrency verification. He holds leadership roles including Course Director for the Electrical and Information Engineering degree and Deputy Tutor for PhD students. Research Interests: Formal Verification of Hardware/Software Systems High-Level Synthesis (HLS) and FPGA Compilation Weak Memory Models and Concurrency Semantics Fuzz Testing for Hardware Tools Compiler Optimization and Correctness Digit Elision and Arbitrary-Precision Arithmetic Notable Achievements: Best Paper Award at EuroSys 2024 (database isolation validation) Pioneered formal methods for HLS tools (e.g., QuteFuzz, C4) Co-developed the C4 C compiler concurrency checker Published over 60 peer-reviewed papers across top venues (ASPLOS, PLDI, FPGA) Lab/Team: Part of the Circuits and Systems group at Imperial College, collaborating with industry partners like Kaihong Yann and ARM.

• Artificial Intelligence
• Cybersecurity
• AI Safety
• +۷ مورد دیگر

Dr. Isabel Straw is an Assistant Professor in Healthcare Artificial Intelligence & Cybersecurity at the Faculty of Population Health Sciences, University College London. She leads the CRASH Team (Cybersecurity Resiliency & AI Safety in Healthcare) and collaborates with the Centre for Healthcare Cybersecurity at the University of California San Diego. As an Emergency Doctor at Homerton Hospital NHS Trust, her research bridges clinical practice, AI development, and cybersecurity. PhD in Artificial Intelligence Contributed to UNESCO's Recommendation on the Ethics of AI Developed CIPHER: tool for modeling patient harms from cyberattacks Co-led international workshops on healthcare cybersecurity Featured in 15+ international media outlets Her research examines technology-facilitated abuse, algorithmic bias in healthcare, and risks from interconnected medical technologies. She has delivered over 70 invited talks, including DEF CON and May Contain Hackers events. Recent publications include: 2025: Cybersecurity in family medicine clinics 2024: Sex-based disparities in cardiac ML algorithms 2023: Biotechnological syndromes and digital pathologies 2022: Ethical model calibration in medical AI 2020: AI biases in mental health She leads UCL postgraduate modules on Healthcare AI and Cybersecurity, and mentors MSc students on topics including AI fairness in oncology and cardiology. Her work has informed WHO policy, UK parliamentary frameworks, and UN AI governance reports.

• Experimental and Behavioral Economics
• Neuroeconomics
• Trust Behavior
• +۳ مورد دیگر

Professor Michael Naef is the Head of the Department of Economics and a Professor at Durham University's Business School. His research focuses on Experimental and Behavioral Economics and Neuroeconomics , exploring topics such as trust dynamics, cultural influences on cooperation, and neurochemical effects on decision-making. He leads the Department of Economics within a triple-accredited business school, emphasizing academic excellence and global connections. Key research interests include investigating how dopamine receptors modulate trust behavior, the origins of cooperative behavior in rice-farming cultures, and the role of testosterone in social interactions. His work combines experimental economics with neuroscience and psychology, often employing pharmacological interventions and neuroimaging techniques. Publications highlight contributions to understanding volatility in trust beliefs (2023), the neurobiological basis of social learning (2019), and testosterone's influence on competitiveness (2017). He advises PhD students Angel Li and Zekun Lin, focusing on advancing behavioral economic theory and applications. Prof. Naef's research has implications for understanding cultural economic differences, mental health impacts on decision-making, and the biological underpinnings of social preferences. His work bridges disciplines, fostering interdisciplinary collaborations in economics, neuroscience, and endocrinology.

Mahroo Eftekhariمشاهده پروفایل

استاد

• Building Energy Management Systems
• HVAC Systems Optimization
• Thermal Comfort Modeling
• +۵ مورد دیگر

Professor Mahroo Eftekhari is a Professor in Building Services Engineering at Loughborough University, leading the Low Energy Building Services Engineering MSc programme. Her research focuses on energy-efficient building systems, thermal comfort, HVAC optimization, and renewable integration. She has pioneered control systems for airports and buildings, including MPC-based strategies to reduce energy use while enhancing occupant well-being. Notable contributions include the development of BISPA (Building & Industrial Services Pipework Academy), a national center for BIM and pipework training. Education: Holds qualifications including CEng (Chartered Engineer), DPhil (Doctor of Philosophy), FCIBSE (Fellow of Chartered Institution of Building Services Engineers), and SFHEA (Senior Fellow of the Higher Education Academy). Her academic career is marked by collaborations with Tata Steel, Mitsubishi R&D, and Vexo, yielding applied research in sustainable building technologies. Research Interests: Indoor Air Quality, Thermal Comfort Modeling, Zero Energy Buildings, Digital Twins, and Advanced Control Systems. She has developed innovative solutions like AI-driven thermal management for Building Energy Management Systems (BEMS) and interfaces to synchronize airport operations with energy systems. Awards & Grants: Secured funding from diverse bodies for projects such as adaptive thermal comfort models, BISPA infrastructure, and energy-efficient HVAC strategies. Her work emphasizes practical applications, including reducing CO₂ emissions via airport terminal optimization and improving renewable energy use in buildings. Lab & Teams: Leads the Building Energy Research Group, managing projects in closed-loop heating systems, IEQ monitoring, and hydronic system efficiency. The Civil Engineering labs house interactive BIM rigs launched with institutional and industry support.

Martin Pickupمشاهده پروفایل

دانشیار

• Philosophy of Religion
• Metaphysics
• Early Modern Philosophy
• +۱ مورد دیگر

Martin Pickup serves as Associate Professor in Philosophy and Director of the Birmingham Centre for Philosophy of Religion at the University of Birmingham, having joined in 2021 after a decade of Oxford-based academic roles including the Turpin Junior Research Fellowship at Oriel College. His career spans teaching, research leadership, and international collaboration such as an Visiting Professorship at the University of Navarra. His educational foundation includes: DPhil in Philosophy (University of Oxford, 2012) BPhil in Philosophy (University of Oxford, 2009) MA in Philosophy (King’s College London, 2006) BA in Philosophy and Theology (University of Oxford, 2005) Pickup’s research integrates Philosophy of Religion, Metaphysics, and Early Modern Philosophy with distinctive methodology: he applies analytic metaphysics to test religious claims’ coherence without advocating theological positions, develops 'situationalism' to explain metaphysical indeterminacy in change and identity, and critically engages Leibniz’s framework for necessity/contingency. His work consistently bridges abstract theory and concrete religious practices, particularly focusing on Eucharistic metaphysics and petitionary prayer. Analysis of his 14 publications (2014-2025) reveals three evolving strands: early Leibniz scholarship (2014-2016), foundational situationalism papers resolving identity puzzles (2016), and mature work connecting indeterminacy frameworks to theology (2021-2025). Recent outputs demonstrate increasing synthesis between metaphysical tools and religious ritual analysis, exemplified by 2025 publications on Eucharistic presence and teleology. His professional recognition includes: Finalist in 'I’m a Researcher Get Me out of Here' (2017) Pickup actively supervises PhD candidates across his research domains and teaches from first-year 'Problems of Philosophy' to Masters-level 'Analytic Theology', though specific grants remain unmentioned in source materials. His leadership as Centre Director involves curating interdisciplinary dialogue through workshops and public engagements like the Institute of Art and Ideas fellowship (2016-17). As Director of the Birmingham Centre for Philosophy of Religion, he cultivates a collaborative hub for advancing philosophical theology through conferences, publications, and cross-departmental initiatives, positioning the Centre as a nexus for rigorous examination of religion’s conceptual foundations.