جست‌وجوی استاد و پژوهشگر

Chris Mooreمشاهده پروفایل

پژوهشگر ارشد

• Gravitational Wave Physics
• Black Hole Mergers
• General Relativity Testing
• +۵ مورد دیگر

Dr Chris Moore is a Research Fellow in the Faculty of Mathematics at the University of Cambridge, specializing in gravitational wave physics within the Relativity and Gravitation research group. His work focuses on data analysis techniques for gravitational wave detection, particularly related to the groundbreaking LIGO observations including the historic GW150914 event - the first direct detection of gravitational waves from a binary black hole merger. Moore's research interests center on gravitational wave data analysis, parameter estimation techniques, and testing general relativity through gravitational wave observations. His work combines advanced statistical methods with deep theoretical understanding of gravitational physics. A significant portion of his research involves developing and refining Gaussian process regression techniques for gravitational wave parameter estimation, which has proven crucial for extracting maximum information from gravitational wave signals. Analysis of Moore's publication record reveals a strong focus on the first gravitational wave detections by Advanced LIGO, particularly the binary black hole merger events. His work spans multiple aspects including detector characterization, data analysis methodology, parameter estimation, astrophysical interpretation, and tests of general relativity. The recurring themes across his publications demonstrate expertise in both the theoretical framework of gravitational wave generation and the practical challenges of detecting and analyzing these extremely weak signals. Moore is an active member of the international gravitational wave research community, contributing to numerous collaborative papers with the LIGO Scientific Collaboration and Virgo Collaboration. His research has been published in leading journals including Physical Review Letters, Physical Review D, and Classical and Quantum Gravity. Based in Room B2.08 at the University of Cambridge, Moore maintains an active research program in gravitational wave astronomy, contributing to one of the most exciting frontiers in modern physics. His work continues to advance our understanding of black holes, neutron stars, and the fundamental nature of gravity through the new window of gravitational wave astronomy.

Rafi Almhanaمشاهده پروفایل

استادیار بالینی

• Bug Management
• Software Maintenance and Evolution
• Artificial Intelligence for Software Engineering
• +۴ مورد دیگر

Rafi Almhana is an Assistant Clinical Professor in the Masters Program in Computer Science at the University of Chicago. He holds a B.S. in computer science and an M.S. in software engineering from the University of Michigan, followed by a Ph.D. in information systems. His research focuses on applying intelligent search and machine learning to software engineering challenges such as bug localization, triage, prioritization, and maintenance. He has collaborated with industry partners like eBay and Ford to validate his work. Education: B.S. in Computer Science, University of Michigan M.S. in Software Engineering, University of Michigan Ph.D. in Information Systems, University of Michigan Research Interests: Rafi’s work spans bug management, refactoring, software evolution, AI-driven software engineering solutions, mining software repositories, and quality assurance. His methodologies combine machine learning with search-based approaches to enhance software development processes. Publications: His recent work emphasizes automated bug management systems and dependency analysis in bug reports, reflecting a trend toward leveraging AI for practical software engineering challenges. These studies aim to improve developer productivity and software reliability through data-driven techniques. Teaching & Industry Experience: Rafi has taught STEM-focused courses in software engineering and computer science. His industry background includes roles as a software architect and manager, emphasizing business-process integration and technological solution design.

Robert Mullinsمشاهده پروفایل

استاد

• Computer Architecture
• Secure Machine Learning
• Hardware Accelerators
• +۳ مورد دیگر

Robert Mullins is a Professor in Computer Architecture at the University of Cambridge's Department of Computer Science and Technology. He is a Fellow of St. John's College and Director of Studies for Computer Science at St. John's and Peterhouse Colleges. His research focuses on secure machine learning, hardware accelerators, and open-source silicon design through initiatives like the lowRISC Foundation and the Raspberry Pi Foundation. He leads projects in efficient AI hardware, including the OpenTitan project and the ARIA 'Scaling Compute' programme targeting 1000x cost reduction in AI infrastructure. Key research themes include architectural security, FPGA optimization, and ethical AI deployment. Mullins contributes to interdisciplinary initiatives such as the CHIA Centre for Human-inspired AI and the ELIAS Alliance for European AI leadership. His work spans both theoretical advancements and practical applications, including open-source hardware development and educational outreach through the Raspberry Pi Foundation. Recent projects highlight trends in adversarial defense mechanisms, neural architecture search, and hardware-software co-design for energy efficiency. His involvement in global collaborations underscores a commitment to bridging academic research with industry impact.

Neil Bramleyمشاهده پروفایل

مدرس ارشد

• Computational Cognitive Science
• Causal Cognition
• Active Learning
• +۳ مورد دیگر

Neil Bramley is a Senior Lecturer in Psychology at the University of Edinburgh, affiliated with the School of Philosophy, Psychology and Language Sciences within the College of Arts, Humanities & Social Sciences. Currently serving as Director of Data and Open Research (2023–2026), he previously held roles such as Marketing Officer for the Psychology Department (2019–2022). His research focuses on computational cognitive science, exploring algorithms underlying human intelligence through computational modeling and behavioral experiments. He teaches courses in causal cognition and cognitive modeling, and actively supervises MSc and PhD students in cognitive science topics. Education: PhD in Experimental Psychology MRes in Computer Science MSc in Cognitive & Decision Sciences MA (Hons) in Philosophy Research Interests: Causal cognition, active learning, hypothesis generation, decision-making, resource rationality, and philosophy of mind. His work bridges computational models with human behavior, emphasizing how people learn and control complex systems through interaction. Grants: EPSRC New Investigator Grant (2021–2024) for 'Computational Constructivism: The Algorithmic Basis of Discovery.' Labs/Teams: Leads the Bramley Computational Cognitive Science Lab, investigating causal learning, temporal dynamics, and human-like generalization in AI.

• Eating Disorders
• Cognitive Flexibility
• Behavioral Flexibility
• +۳ مورد دیگر

Kelly Dann serves as a casual academic in the School of Psychology at The University of Sydney and as a Research Officer at the InsideOut Institute for Eating Disorders, focusing on cognitive and behavioral mechanisms in eating disorder pathology. Her research program centers on: Cognitive and behavioral flexibility in anorexia nervosa Strengths-based approaches to treatment and recovery Measurement validity in cognitive assessment for eating disorders Exploration of cognitive strengths in clinical populations Analysis of her 2021-2025 publications reveals evolving methodological sophistication—from systematic reviews to eye-tracking paradigms—with consistent emphasis on translating cognitive findings to real-world functioning and clinical outcomes. Her work increasingly integrates positive psychology frameworks while addressing persistent measurement challenges in the field. Dr. Dann's primary research affiliation is with the InsideOut Institute, Australia's national center for eating disorder research and treatment innovation.

Yong Zhi Fooمشاهده پروفایل

پژوهشگر ارشد

• Human sexual selection
• Person perception
• Life-history trade-offs
• +۵ مورد دیگر

Dr. Yong Zhi Foo is a Research Fellow in the School of Biological Sciences at The University of Western Australia. He holds a PhD in Psychology and Biological Sciences (2017) from UWA, under Prof. Gillian Rhodes and Prof. Leigh W. Simmons, and completed postdoctoral fellowships at UWA and UNSW with Prof. Shinichi Nakagawa. His research bridges evolutionary biology and psychology, focusing on person perception, life-history trade-offs, and sexual selection. He is actively involved in ARC-funded projects exploring nutrition's impact on male life history traits. Key research areas include human sexual selection mechanisms, facial perception accuracy, and the biological basis of attractiveness. His work employs meta-analyses, cohort studies, and experimental methods. He has published 24 peer-reviewed articles, with recent contributions on wildlife management, social intelligence hypotheses, and immune-reproductive trade-offs. Current grants include a DECRA 2023 project (2023–2026) investigating nutrition's role in male health and reproduction. Dr. Foo collaborates internationally on datasets involving human and cross-species comparative studies, with a focus on ecological immunology and behavioral ecology. His research contributes to UN Sustainable Development Goals related to health and well-being, and sustainable cities.

Rebecca Stenbergمشاهده پروفایل

دانشیار

• Emergency Management
• Crisis Response
• Rescue Operations
• +۷ مورد دیگر

Rebecca Stenberg is an Associate Professor in Business Administration at Linköping University's Department of Management and Engineering. She holds a Ph.D. in Psychology and is a board member of the Center for Advanced Research in Emergency Response (CARER). Her work focuses on optimizing rescue operations through improved organizing, leadership, and collaboration, with special emphasis on marine rescue, outdoor safety, and crisis management involving new actors in safety systems. Current research includes the multidisciplinary 'Efficient Rescue in the Incident Site of Tomorrow' program. Education: Ph.D. in Psychology. Affiliations: CARER (funded by Linköping University and Swedish Contingencies Agency), Department of Management and Engineering (IEI), Business Administration (FEK). Research Interests: Interorganizational collaboration in crisis response, missing persons search strategies, dementia-related emergency preparedness, volunteer coordination in rescue operations, and digitalization's role in emergency response systems. Her work bridges social sciences with practical crisis management challenges. Publications focus on collaborative frameworks in rescue missions, digital co-production systems, and geographical analysis of volunteer networks. Key projects include the 'Terrängpejlen' fieldwork series and dementia-related preparative collaboration studies. Labs/Teams: Active in CARER's multidisciplinary research initiatives, collaborating with Swedish authorities, NGOs, and volunteer organizations. Current projects emphasize scenario-based crisis training and resource allocation optimization in complex environments.

Stephane Willocqمشاهده پروفایل

استاد

• Experimental Particle Physics
• High Energy Physics
• ATLAS Experiment
• +۵ مورد دیگر

Professor Stephane Willocq is a faculty member in the Department of Physics at the University of Massachusetts Amherst. He holds a Ph.D. from Tufts University (1992) and specializes in Experimental Particle Physics, focusing on high-energy collider experiments, particularly with the ATLAS detector at CERN's LHC. His research interests include searches for new physics beyond the Standard Model, Higgs boson studies, supersymmetry, and dark matter candidates. Willocq is deeply involved in the ATLAS collaboration, contributing to analyses of LHC data from Run 2 and beyond. His work encompasses precision measurements of top quark properties, W/Z boson physics, and novel signatures of exotic particles. He has pioneered studies on photonuclear processes in ultra-peripheral collisions and developed advanced data analysis techniques using machine learning. His recent publications (2024–2025) highlight searches for new scalar particles, vector-like leptons, and long-lived neutral particles, alongside constraints on Higgs boson properties and off-shell behavior. Willocq also contributes to ATLAS computing infrastructure, including cloud resource evaluation and detector calibration improvements.

Marin Kobilarovمشاهده پروفایل

دانشیار

• Intelligent Robotics
• Autonomous Systems
• Mechanical Control Systems
• +۳ مورد دیگر

Marin Kobilarov is an Associate Professor in the Department of Mechanical Engineering at Johns Hopkins University’s Whiting School of Engineering. He leads the Laboratory for Autonomous Systems, Control, and Optimization, a subset of the Laboratory for Computational Sensing and Robotics. His research focuses on intelligent robotic vehicles capable of autonomous navigation and task execution in complex environments, with applications in aerial vehicles, medical robotics, and space systems. Dr. Kobilarov holds a BS in Computer Science and Applied Mathematics from Trinity College (2003) and a PhD in Computer Science from the University of Southern California (2008). Before joining Johns Hopkins in 2012, he completed postdoctoral fellowships at the California Institute of Technology and the United Technologies Research Center, specializing in control systems and dynamical systems. His research interests span robotics, autonomous systems, and medical applications, including surgical robotics for ophthalmology and microsurgery. Notable projects include developing perception-aware navigation frameworks, UAV pick-and-place systems, and autonomous retinal surgery tools using imitation learning and real-time imaging. His publications emphasize trajectory optimization, multi-agent coordination, and safety-critical control, with recent work addressing challenges in occluded environment navigation and uncertainty-aware planning for heterogeneous robot teams. Awards include prestigious postdoctoral fellowships from the Keck Institute for Space Studies and United Technologies Research Center. Dr. Kobilarov’s lab collaborates across disciplines to advance robotics in dynamic environments, with ongoing work on surgical automation, autonomous aerial systems, and robust control algorithms. His research bridges theoretical control methods with practical engineering solutions for real-world robotic applications.

Joan Espasa Arxerمشاهده پروفایل

مدرس

• Automated Planning
• Artificial Intelligence
• Constraint Programming
• +۵ مورد دیگر

Dr Joan Espasa Arxer is a Lecturer in the School of Computer Science at the University of St Andrews, specializing in the AI group. His research focuses on Automated Planning, Constraint Programming, and applications of logic in computer science. He holds a position in the Department of Computer Science and teaches courses such as CS4402 - Constraint Programming and CS4303 - Videogames, while supervising projects across various academic levels. Research interests include Classical and Numeric AI Planning, Boolean Satisfiability (SAT), Satisfiability Modulo Theories (SMT), Planning as Satisfiability, Constraint Programming, and Automated reformulation of models. His work addresses challenges in planning domain modeling, benchmark instance generation, and cross-paradigm problem solving. Recent publications explore lifted planning with constraints, international planning competitions, and modeling pipelines in AI. He collaborates on tools like the 2023 International Planning Competition dataset and frameworks for generating benchmark instances. Advises PhD students Mustafa Abdelwahed and Carla Davesa Sureda. Engages in community outreach through events like 'Doors Open @ Computer Science' and contributes to open-source tools for planning and constraint satisfaction.

• Artificial Intelligence
• Constraint Programming
• Combinatorial Optimization
• +۳ مورد دیگر

Prof Ian Miguel is a Professor and Head of the School of Computer Science at the University of St Andrews, a position he has held since 2004. His primary research focuses on Artificial Intelligence, particularly in combinatorial optimization and constraint programming. He leads efforts to automate the constraint modelling process through frameworks like the Constraint Modelling Pipeline, which translates high-level problem descriptions into efficient solver inputs. His work emphasizes improving solver performance through automated reformulation techniques and explores applications in planning, scheduling, and routing. He teaches courses on Constraint Programming (CS4402) and Video Games (CS4303). Research interests include automated constraint model generation, solver optimization, and cross-paradigm modelling. His contributions span academic publications, conference presentations, and collaborations on projects like Athanor (local search for abstract constraints) and TabID (subproblem identification in models). Notable achievements include developing Savile Row and Conjure tools for automated constraint modelling. His PhD advisees include Carla Davesa Sureda, Adamu Habu, and Erdem Kus. Publications focus on advancing constraint satisfaction and optimization techniques, with recent work addressing multi-task learning, graph-based reformulation, and algorithm selection. He actively contributes to conferences such as LION, ICGT, and CP, and his research has implications for automated planning, cloud computing optimization, and solver benchmarking.

Rosa Filgueiraمشاهده پروفایل

مدرس

• Distributed Systems
• Data-Streaming Optimizations
• Serverless Computing
• +۱۱ مورد دیگر

Rosa Filgueira is a Lecturer at the School of Computer Science, University of St Andrews, and Group Leader of the Systems Research Group (SRG). She holds an Honorary Research Fellow title and is a member of the UK Young Academy. Her career includes roles as Assistant Professor at Heriot-Watt University, Vice President Applied Researcher at JPMorgan Chase, and Senior Data Scientist at the British Geological Survey. She earned her BSc and MSc from the University of Deusto (Spain) and a PhD from University Carlos III Madrid (Spain). Her research focuses on advanced information processing technologies to accelerate scientific discovery, emphasizing distributed systems, data-streaming optimizations, and reproducible frameworks. Key areas include serverless computing, adaptive communication techniques, and AI-driven software analysis. She teaches CS3031 Databases (undergraduate) and CS5020 Principles of Computer Communication Systems (postgraduate), supervising multiple student projects. Rosa’s work addresses challenges in health, earth sciences, and digital humanities. Notable projects include cultural analytics frameworks for the creative industries and AI tools for historical text mining. She leads initiatives like the Laminar serverless framework and the frances NLP tool for heritage texts. Her awards include the UK Young Academy membership and National Librarian's Research Fellowship. Current grants include the British Academy-funded Decoding Democracy project. She actively collaborates internationally, contributing to IEEE eScience conferences and open-source projects like dispel4py and Inspect4py. Labs/Teams: Systems Research Group (SRG), leading interdisciplinary collaborations in HPC and data science. Her work bridges computer science with domain-specific applications, emphasizing real-world impact through reproducible software solutions.

• Software Engineering
• Cloud Computing
• Service Oriented Architecture
• +۳ مورد دیگر

Dr. Mustafa Bozkurt is a Senior Lecturer in Software Engineering at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science. His research focuses on applying multi-objective optimization and machine learning to address challenges in software engineering, including automated testing, software design, requirements analysis, and maintenance. He actively contributes to areas such as service-oriented architecture, cloud computing, and search-based software engineering. Teaching responsibilities include undergraduate and postgraduate courses such as Database Systems, Introduction to Object-Oriented Programming, and Software Engineering. He also oversees the Software Engineering Project module, emphasizing collaborative problem-solving and practical application of engineering principles. Research interests span service-oriented architecture, software testing methodologies, cloud computing, and requirements engineering. Tools like Visual Paradigm are utilized for UML and BPMN modeling in academic projects. His publications emphasize optimization techniques in testing, cost-aware strategies for service-centric systems, and realistic test input generation. Dr. Bozkurt’s work bridges theoretical advancements with practical software development challenges, aiming to enhance software quality and efficiency through innovative methodologies.

• Information Retrieval
• Structured Document Retrieval (SDR)
• Human-Computer Interaction (HCI)
• +۵ مورد دیگر

Jane Reid - Senior Lecturer & Director of Development Ms. Jane Reid is a Senior Lecturer and Director of Development in the Department of Computer Science at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science. She holds dual membership in the Information Retrieval Group and the Interaction, Media and Communication Research Group. Her work bridges computer science with interdisciplinary fields like information science and educational theory. Research Focus Her research centers on user-centered aspects of information retrieval (IR), particularly structured document retrieval (SDR) and interface design. Key areas include information seeking behavior in structured documents, relevance concepts in IR systems, and evaluation methodologies. She also explores distance learning applications, focusing on virtual learning environments (VLEs), cross-cultural factors in online education, and multimedia IR techniques. Teaching Graphical User Interfaces (Postgraduate/Undergraduate) Project Management for Big Data Analysis (Work-based) Information Retrieval for Interactive Computing Research Methods (MSc) Database Systems Administration & Activities She coordinates the Research Methods module for the MSc in Advanced Methods in Computer Science and serves on the Taught Courses committee. Professional activities include membership in the London Knowledge Management Network and past roles as Secretary of the BCS Information Retrieval Specialist Group. Projects & Supervision Current PhD supervision includes Sandra Tury’s work on distance learning frameworks. She leads projects like FOCUS (focussed structured document retrieval) and GRIS (information-seeking behaviors). Her work has been supported through initiatives like INEX (XML retrieval evaluation).

Valentin Rothbergمشاهده پروفایل

پژوهشگر

• Operating Systems
• Software Configuration Management
• Systems Software
• +۳ مورد دیگر

Valentin Rothberg is a Researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg. His work focuses on operating systems, software configuration management, and compiler optimization. He is a core contributor to projects like CADOS (Configurability Aware Development of Operating Systems) and VAMOS (Variability Management in Operating Systems). Research interests include Linux kernel customization, dynamic variability in software systems, and compiler-based redundancy detection. He has authored notable publications on AST hashing for build optimization and impact analysis of Linux feature changes. Rothberg has advised multiple theses on topics like kernel configuration analysis and static analysis tools. His open-source contributions include the vgrep tool for enhanced text search and collaboration on container technologies like Podman . He maintains active involvement in FAU's distributed systems research and has presented at conferences such as USENIX and VaMoS.