جست‌وجوی استاد و پژوهشگر

Stephen Langdonمشاهده پروفایل

استاد

• Numerical Analysis
• Numerical Solution of Partial Differential Equations
• Boundary Integral Equation Methods
• +۶ مورد دیگر

Professor Stephen Langdon is a faculty member at Brunel University London , holding the position of Professor of Mathematics and serving as Associate PVC for Academic Planning & Strategic Projects . His academic career includes over 15 years at the University of Reading , where he was Head of the Department of Mathematics and Statistics for five years. He also served as Interim Executive Dean of the College of Engineering, Design and Physical Sciences at Brunel from 2022 to 2024. Education: PhD in Numerical Analysis, University of Bath (1999) BA in Mathematics, Oxford University (1994) Postgraduate Certificate of Academic Practice, University of Reading (2009) Research Interests: Professor Langdon's research is centered in Numerical Analysis , with a strong focus on the development, analysis, and implementation of numerical methods for partial differential equations . His work encompasses: Boundary integral and finite element methods High-frequency scattering problems in acoustics and electromagnetics Fluid flow in porous media Computational modeling of tumor growth Machine learning applications in numerical methods Publications Overview: His recent work includes modeling helicopter rotor-induced particle-fluid interactions , developing frequency-independent numerical methods for far-field scattering , and advancing high-frequency boundary element methods . These publications span journals such as AIAA Journal , Journal of Fluid Mechanics , SIAM Journal on Scientific Computing , and IMA Journal of Numerical Analysis . Teaching and Supervision: He teaches MA2690 - Professional Development and Project Work and actively supervises PhD students in areas aligned with his research interests. He welcomes prospective PhD applicants in numerical analysis, PDEs, and related computational fields. Contact: Email: stephen.langdon@brunel.ac.uk Phone: +44 (0)1895 266554 Office: Tower A 030, Brunel University London

Arthi Manoharمشاهده پروفایل

مدرس ارشد

• Human–Computer Interaction
• Inclusive Design
• Participatory & Co-design
• +۵ مورد دیگر

Dr Arthi Manohar is a Senior Lecturer in Design at Brunel University London and serves as Programme Director for the BSc Product Design degree within Brunel Design School, College of Engineering, Design and Physical Sciences. Since joining Brunel in 2018 she has led multiple undergraduate and master-level modules, championed Equality, Diversity & Inclusion, and secured significant EPSRC research funding. Education PhD Digital Product Design, University of Dundee (2017) MA Architecture and Digital Media, University of Westminster (2009) BArch Architecture, National Institute of Technology, India (2007) FHEA (Fellow of the Higher Education Academy), 2021 Research Interests Arthi’s research lies at the intersection of social design and emerging technology . She investigates participatory, inclusive and co-design approaches to Human–Computer Interaction, privacy and trust in the Internet of Things, and the application of AI to accessibility and health technologies. Her work emphasises human values, cross-cultural perspectives and ethical considerations in technology design. Recent funded projects include Trust in Home: Rethinking Interface Design in IoT (EPSRC HDI Network Plus) and From Understanding Privacy and Trust to Re-visualising TAPESTRY (EPSRC Sandpit). She collaborates across disciplines with partners such as the University of Nottingham, University of Kent, Royal Holloway and industry partners like LoomiAssist Ltd. Publications & Scholarly Service Arthi has published extensively in top-tier venues such as DRS, DIS, British HCI, Multimedia Tools & Applications, IEEE Transactions on Services Computing and CHI Workshops. Since 2020 she has served as Equality, Diversity & Inclusion Champion for the Department of Design and has held programme-committee roles for British HCI 2021, DIS 2019 and IndiaHCI 2019. PhD Supervision & Teaching She currently supervises four doctoral researchers exploring antimicrobial resistance design, stigma in assistive technology, virtual production and user engagement. At undergraduate and masters levels she leads modules on Interaction & UX Design, Digital Design Prototyping, Professional Practice and Design Communication, and has mentored over a dozen master dissertations on inclusive design, AI/AR retail experiences and speculative futures.

Maximilian Kasyمشاهده پروفایل

استاد

• Machine learning theory
• Social impact of algorithmic decision making
• Publication bias
• +۸ مورد دیگر

Maximilian Kasy serves as Professor of Economics at the University of Oxford's Department of Economics, actively contributing to research and teaching within econometrics and applied microeconomics frameworks. His research spans machine learning theory, algorithmic decision-making social impacts, publication bias mechanisms, adaptive experimental design, statistical decision theory, empirical Bayes methods, causal identification, and economic inequality with optimal taxation applications. This interdisciplinary work bridges economics, statistics, and machine learning to address methodological challenges in empirical research and policy evaluation, emphasizing social accountability in algorithmic systems and research transparency. Recent publications demonstrate expertise in adaptive experimental frameworks for policy optimization and novel methodologies for detecting and correcting publication bias, reflecting his commitment to improving empirical rigor and social relevance in economic research. Scientific recognition includes: Sloan Foundation grant (2022) Professor Kasy mentors students through Oxford's Summer School courses and coordinates the interdisciplinary Machine Learning and Economics Group, fostering collaboration across methodological domains. His research groups specifically focus on Econometrics and Applied Microeconomics, with significant engagement in UK and European contexts addressing Labour, Technology, and Inequality challenges.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Dr. Mubashir Ahmad is a researcher at the School of Physics, Engineering & Computer Science, University of Hertfordshire. His work focuses on applying computational methods to solve real-world challenges in healthcare, infrastructure, and environmental sustainability. Research Focus Dr. Ahmad's expertise spans: Core AI/ML Techniques : Deep learning, machine learning algorithms, computer vision systems Application Domains : Medical imaging diagnostics, pollution modeling, infrastructure inspection automation, and climate impact analysis Emerging Areas : Robotic systems integration and big data fusion for industrial applications Project Engagement Deep Learning-powered Apple Disease Detection System (ADDS) (2024-2025): Serving as Co-Investigator to develop AI tools for agricultural disease identification in collaboration with UK farmers. Publication Trends His recent publications demonstrate consistent focus on operationalizing deep learning across diverse sectors. Dominant themes include automated infrastructure inspection (sewer systems), medical image analysis (chest radiographs), and environmental forecasting (air quality/pollution). This reflects a cross-disciplinary approach bridging computer science with civil engineering, healthcare, and environmental science.

• Computer Security
• Network Security
• Internet of Things (IoT) Security
• +۳ مورد دیگر

Dr. Abdelrahman Abuarqoub is a Senior Lecturer in Computer Security at the Cardiff School of Technologies , Cardiff Metropolitan University . He holds a PhD in Computer Science (2014) from Manchester Metropolitan University and an MSc (Distinction) in Data Telecommunications and Networks (2011) from the University of Salford . Research focuses on Computer Security , IoT Networks , and Lightweight Encryption Active member of IEEE TSUSC , MTAP-Springer , and other technical program committees Published extensively in IEEE , Springer , and ACM venues

• Software Engineering
• Internet of Things (IoT)
• Cryptography
• +۴ مورد دیگر

Dr. Bassam Al-Shargabi serves as a Senior Lecturer in Software Engineering at Cardiff School of Technologies, Cardiff Metropolitan University. His academic credentials include a PhD in Computer Information Systems (2009) and an MSc in Computer Information Systems from AABFS (2004). His research focuses on critical intersections of technology and security: Lightweight encryption methods for resource-constrained IoT healthcare devices Innovative DNA-based cryptographic techniques Blockchain technology applications in auditing systems E-learning platform adoption in educational contexts Dr. Al-Shargabi's scholarly contributions demonstrate a consistent trajectory in developing secure, efficient solutions for emerging technological challenges, particularly in healthcare environments. His work bridges theoretical computer science with practical implementations to address real-world security concerns in increasingly connected systems. He actively participates in the academic community as a guest editor and technical program committee member for international conferences and leading journals. His publications appear in prestigious venues from major publishers including Elsevier, IEEE, Springer, and ACM, reflecting the quality and relevance of his research contributions.

• Web Security
• Identity Management
• System Security
• +۳ مورد دیگر

Dr. Wanpeng Li is a Lecturer in Cyber Security within the Department of Computer Science at the University of Liverpool. Prior to this role, he held lecturer positions at the University of Aberdeen and Manchester Metropolitan University, and worked as a postdoctoral researcher at City, University of London. His research focuses on critical areas in cyber security including web security, identity management, authentication mechanisms, and malware detection using machine learning. Research Trends: His recent publications span both cyber security and mathematical modeling domains. Key security themes include automated vulnerability detection, federated learning attacks, and privacy-preserving protocols for vehicular networks and IIoT systems. Parallel studies in grey system models explore energy consumption forecasting and environmental impact analysis using fractional calculus and neural network integrations. Advising: Dr. Li actively accepts PhD students in cyber security-related fields.

• Supply Chain Analytics
• Logistics Management
• Operations Research
• +۵ مورد دیگر

Professor Ying Xie is a leading academic at Cranfield University's School of Management, holding the position of Professor of Supply Chain Analytics. Her work bridges engineering, data science, and business management across diverse sectors including maritime logistics, healthcare, and disaster response. Her educational background includes a BEng, MSc, and PhD in Management Science from Coventry University. Key research interests focus on supply chain digitalization and decarbonization , renewable energy supply chain configuration , and AI applications in operational resilience . Her work consistently integrates machine learning with real-world business challenges, particularly in port management and sustainability. Recent publications reveal strong trends in maritime decarbonization (25%), AI-driven supply chain optimization (30%), and healthcare systems resilience (20%). Her research increasingly addresses climate adaptation through circular economy models and clean energy transitions. Principal Fellow of the Higher Education Academy (HEA) Expert reviewer for UKRI MRC, British Academy, and EU Horizon Professor Xie has supervised numerous PhD completions and secured two dedicated scholarships for port management and digital twin research. Her £20m+ grant portfolio includes major projects with EPSRC (£7.6m Net Zero Aviation CDT), Innovate UK (£174k Sustainability Platform), and EU Horizon (£5m MEDiate disaster management). She actively collaborates with the Port of Dover, Ocado Technology, and NHS England. She leads the Co-Innovation Group in the UK National Clean Maritime Research Hub and directs academic activities for the EPSRC Centre for Doctoral Training in Net Zero Aviation, shaping national maritime strategy through the Department for Transport's 'UK Ports the Future' report.

• Robotics
• Evolutionary Robotics
• Artificial Evolution
• +۶ مورد دیگر

Leni Le Goff is a Lecturer at the School of Computing, Engineering and the Built Environment , Edinburgh Napier University. Her research bridges robotics , evolutionary computation , and environmental sustainability . Key research interests include: Evolutionary design of robot morphologies and controllers Integration of individual and cultural learning in artificial evolution Application of autonomous systems for terrestrial biodiversity monitoring Optimization frameworks for robotic policy search Manufacturability constraints in morpho-evolution Transdisciplinary collaboration between ecologists and roboticists Recent publications highlight her work on: Developing generalized early stopping criteria for policy search Mapping fitness landscapes in morpho-evolution Assessing robotic solutions for ecological surveying Overcoming hierarchical optimization challenges in coevolution Creating biodegradable and deployable robotic systems Evaluating manufacturability trade-offs in evolved robot designs Active in the Autonomous Robot Evolution (ARE) project, she collaborates with leading researchers like Prof Emma Hart and Prof Karen Diele. Her work receives funding from EPSRC and the Carnegie Trust , focusing on real-world deployment challenges and computational efficiency improvements.

• Edge-Cloud Computing
• Resource Optimization
• Applied Machine Learning
• +۵ مورد دیگر

Jia Hu is an Associate Professor in Computer Science at the University of Exeter. He holds a PhD in Computer Science from the University of Bradford (2010), and M.Eng/B.Eng degrees in Electronic Engineering from Huazhong University of Science and Technology. His research specializes in edge-cloud computing, federated learning, and AI-driven optimization for networks and IoT systems. Research Interests: Hu's work spans resource optimization, applied machine learning (particularly in distributed settings), network security, blockchain integration, and intelligent systems for electric vehicles and Industry 4.0. His recent projects focus on federated edge AI, 6G-enabled industrial IoT, and real-time federated learning via hardware-algorithm co-design. Publications: His 150+ papers emphasize federated learning, edge computing, and reinforcement learning applications. Recent works (2020–2025) show a strong trend toward optimizing AI at the network edge, with themes like digital twins, blockchain security, and EV-integrated systems dominating. Awards & Recognition: Best Paper Awards: IEEE SOSE'16, IUCC'14 Outstanding Service & Leadership Awards for IEEE conferences Top 4% contributor to EPSRC Peer Review Fellow of the Higher Education Academy (HEA) Grants & Projects: Secured €4.7M+ funding from EU Horizon, EPSRC, and Royal Society for projects including: SAILING (Secure AI for Smart Internet-of-Energy, €3.6M) REFINE (Real-time Air Quality Monitoring with UAVs, €897K) SustainAIRA6G (Energy-Efficient AI for 6G Networks, £118K) Advising: Supervised 12 PhD students to completion; currently mentoring 7 students in federated learning, edge computing, and AIoT.

Tomoko Tamariمشاهده پروفایل

دانشیار

• Japanese culture & society
• Consumer culture
• Visual culture
• +۸ مورد دیگر

Tomoko Tamari is Reader in Sociology at Goldsmiths, University of London, affiliated with the Institute for Creative and Cultural Entrepreneurship (ICCE). She joined Goldsmiths in 2013 after serving as a research fellow at Nottingham Trent University. Her academic background spans sociology, mass communication studies, and women's studies, with current interests intersecting sociology, cultural studies, and body studies. She serves as Managing Editor of Body & Society (Sage Publications) and coordinates the Theory Culture & Society 'New Encyclopaedia Project'. Tamari's research interests encompass Japanese culture and society, consumer culture, visual culture, and technology's relationship with the body. Her current working areas include animation and human perception (particularly affect in digital aesthetics and hand-drawing moving images), technology and modern architectural design (exploring Japanese Metabolism movement), food culture and lifestyles in 20th century Japan, the body and medicine (focusing on probiotics industry), body image and prosthetic aesthetics in Paralympic culture, techno-animism, and human-machine integration. Her work consistently examines how technology reshapes bodily experience and cultural practices. Her recent publications demonstrate a clear trajectory toward examining the intersections of digital technologies, human perception, and embodiment. The majority of her work from 2023-2025 focuses on AI, digital aesthetics, animation, and the materiality of the body in technological contexts. This represents an evolution from her earlier work on Japanese consumer culture and department stores toward contemporary digital and technological questions while maintaining her core interest in embodiment and cultural practices. Tamari has been actively involved in academic leadership through her editorial roles, including co-editing special journal issues on the Tokyo Olympics and post-university scholarly apparatus. Her conference presentations reflect engagement with cutting-edge discussions about AI, embodiment, and the future of knowledge production in digital society. While specific grant information isn't detailed in the provided texts, her extensive publication record and editorial positions indicate significant research activity and scholarly recognition.

• Digital Twin
• Augmented Reality
• Virtual Reality
• +۶ مورد دیگر

Dr. Jiaxin Ling serves as a Research Fellow in Digital Twin and AR/VR for Heritage Buildings at The Bartlett School of Sustainable Construction, University College London. His work bridges digital innovation with sustainable construction practices, focusing on heritage preservation in complex urban environments. Academic background includes: PhD in Civil Engineering, Tongji University (2018-2024), recognized as an Outstanding Graduate of Shanghai Bachelor's in Civil Engineering, Wuhan University (2014-2018) His research spans Digital Twin for tunnels/buildings, Building Information Modeling (BIM) , and AI/ML applications in construction engineering. He pioneers AR/VR solutions for fire safety, tunnel lighting optimization, and intelligent infrastructure, directly supporting UN Sustainable Development Goals 11 (Sustainable Cities) and 9 (Industry Innovation). Analysis of recent publications reveals a cohesive trajectory in applying digital twin technology to solve critical challenges in tunnel safety, energy efficiency, and real-time construction monitoring through hybrid knowledge-data approaches. Key recognition: Outstanding Graduate of Shanghai (top doctoral honor) Dr. Ling contributes to major research initiatives funded by the European Union Horizon Programme and National Natural Science Foundation of China (NSFC) , collaborating across international teams to advance sustainable construction methodologies. His work operates within UCL's interdisciplinary research ecosystem, focusing on heritage building preservation through cutting-edge digital workflows and sensor-integrated monitoring systems.

• Control Systems
• Robotics
• Mathematical Modelling
• +۸ مورد دیگر

Claudio Gaz is a Senior Lecturer in Mechatronics, Control, and Autonomous Systems at the Department of Mechanical Engineering, Faculty of Engineering, Computing and the Environment, Kingston University London. He holds a PhD in Automation and Operational Research (2016) and a Master's in Control Engineering with top marks (2011) from Sapienza Università di Roma, and was awarded the French national qualification as maître de conférences (class 61) in 2019. His research spans control systems, robotics, and mathematical modeling, with a focus on industrial manipulators (e.g., KUKA LWR, Universal Robots UR10) and biological processes like glucose homeostasis. Recent work involves dynamic parameter identification for collaborative robots and sensorless force feedback in medical robotics. He has collaborated with institutions such as Sapienza Università di Roma, CNR-IASI (Italian National Research Council), and Airbus Group. His scientific awards include: Fellowship of the Higher Education Academy (FHEA) . Gaz has contributed to journals and conferences in robotics, control theory, and biomedical modeling, with a strong emphasis on real-time adaptive algorithms and safety in physical human-robot interaction.

• Human Factors
• Cognitive Science
• Cyberpsychology
• +۷ مورد دیگر

Professor Phillip Morgan is a leading academic in Human Factors and Cognitive Science at Cardiff University's School of Psychology, holding a Personal Chair since 2020. He directs the Human Factors Excellence (HuFEx) Research Group and serves as Director of Research for the Centre for Artificial Intelligence, Robotics & Human-Machine Systems (IROHMS) . Since March 2019, he has been seconded part-time to Airbus as Director of their Centre of Excellence in Human-Centric Cyber Security . BSc (Hons) Psychology, Cardiff University (2001) PGDip Research Methods, Cardiff University (2002, Distinction) PhD in Cognitive Psychology, Cardiff University (2005) PGCHE, University of Wales (2012, Distinction) His research merges Human Factors with Cognitive Science to address real-world challenges in: Human-machine interaction in autonomous systems Cyberpsychology and security behavior Transport human factors (connected/autonomous vehicles) Interruption/distraction effects on cognition Trust and blame dynamics in AI systems Industry 5.0 human-centric manufacturing Recent publications show AI and cybersecurity as dominant themes, with specific focus on autonomous vehicle interfaces, human fatigue analysis, and trust calibration in human-machine systems. His work integrates behavioral experiments, driving simulators, and human-state monitoring. Scientific Recognition: Associate Fellow of the British Psychological Society Best Paper Award at AHFE 2021 Member of Experimental Psychology Society Keynote speaker at multiple international conferences As supervisor, he leads projects on cybersecurity frameworks, fatigue detection, and human-AI interaction. His grants portfolio exceeds £37m from sources including EPSRC, ESRC, Airbus, and Wellcome Trust. Current supervisees include Victoria Marcinkiewicz, George Raywood-Burke, and Nicola Turner.

Hongyu Zhangمشاهده پروفایل

مدرس

• Stochastic programming
• Energy systems optimisation
• Machine learning and AI
• +۳ مورد دیگر

Dr Hongyu Zhang is a Lecturer in Optimization for Machine Learning and AI at the School of Mathematical Sciences, University of Southampton. His expertise spans operational research and energy systems optimization, with a focus on stochastic programming and quantum computing applications. PhD Operational Research, NTNU MSc Operational Research with Data Science, University of Edinburgh BSc Mathematics and Applied Mathematics, Huaqiao University His research develops optimization models and algorithms for large-scale energy system planning, integrating machine learning, artificial intelligence, and quantum computing tools to address complexities in energy transition and policy-making. Key areas include multi-timescale uncertainty analysis, decomposition methods, and offshore energy hub modelling. Recent publications show strong trends in energy systems optimization (7 papers), algorithm development for stochastic programming (4 papers), and quantum computing applications (2 papers). His work addresses European energy security, hydrogen infrastructure development, and carbon capture technologies. Currently accepting PhD applications, Dr Zhang contributes to academic supervision and teaches optimization methods at the university. He is affiliated with the Operational Research group and CORMSIS center.