جست‌وجوی استاد و پژوهشگر

Justin Pearsonمشاهده پروفایل

دانشیار

• Constraint Programming
• Combinatorial Optimisation
• Artificial Intelligence
• +۷ مورد دیگر

Justin Pearson is an Associate Professor at the Department of Information Technology; Division of Computing Science at Uppsala University . He is a member of the university's optimisation group and coordinates the IT department's mentor programme for new employees . Research Interests include Constraint Programming , Combinatorial Optimisation , Artificial Intelligence , Software Testing , and Complexity Theory . His work focuses on theoretical and practical aspects of constraint satisfaction, local search algorithms, and symmetry breaking in constraint programming. Teaching involves courses such as Algorithms and Data Structures II (1DL231) and Introduction to Machine Learning for Bachelor Students (1DL034), with a PhD-level course on Category Theory offered periodically based on demand. Scientific Contributions span publications in constraint programming for air traffic management, sensor networks, and industrial applications. Recent work includes parameterised treewidth in constraint models, time-series constraints, and symmetry breaking techniques. Students supervised include PhD candidates Frej Knutar Lewander (co-supervised with Pierre Flener), Yi Zhao (co-supervised with Di Yuan), and previously graduated students Gustav Björdal , María Andreína Francisco Rodríguez , and Joseph Scott .

• Structural Engineering
• Civil Engineering
• Smart Infrastructure
• +۸ مورد دیگر

Sam Cocking is a Researcher at the University of Cambridge , affiliated with the Department of Engineering . He works at the Centre for Smart Infrastructure and Construction , focusing on structural monitoring and assessment of ageing railway infrastructure. Research Focus: Structural monitoring, masonry/concrete construction, acoustic emission, fibre-optic sensing, and decarbonisation/climate resilience decision-support tools for transport infrastructure. Projects: UK National Hub for Decarbonised, Adaptable, and Resilient Transport Infrastructures (DARe), monitoring church pinnacles, and structural assessment of a 350-year-old tree. Technologies: Fibre-optic sensing, acoustic emission sensors, videogrammetry, LiDAR, and finite-element modeling. Collaborations: Centre for Smart Infrastructure and Construction (CSIC), DARe Hub. Research Trends: Publications emphasize masonry arch bridges, structural monitoring technologies, seismic analysis, and machine learning applications for form-finding. Studies span 2016-2025, reflecting long-term engagement with infrastructure resilience and historical preservation. Conservation Efforts: Interdisciplinary work includes monitoring church pinnacles and ancient trees, bridging civil engineering with cultural and environmental conservation.

• Stochastic Optimization
• Risk-Averse Decision-Making
• Mathematical Programming
• +۷ مورد دیگر

Darinka Dentcheva is a Professor in the Department of Mathematical Sciences at Stevens Institute of Technology, affiliated with the Charles V. Schaefer, Jr. School of Engineering and Science. She holds a PhD in Mathematics from Humboldt University (2006) and an earlier PhD in Mathematics (1989) and MS in Mathematics and Computer Science (1981), also from Humboldt University. Her research focuses on stochastic optimization, risk-averse decision-making, and their applications in machine learning, finance, healthcare, and energy systems. Dr. Dentcheva’s work emphasizes developing mathematical frameworks for managing risk under uncertainty, including stochastic dominance constraints and risk-averse control of Markov systems. She has authored influential books such as *Risk-Averse Optimization and Control: Theory and Methods* (2024) and co-edited volumes on stochastic optimization theory. Her research has been supported by grants from the National Science Foundation (NSF), Office of Naval Research, and Air Force Office of Scientific Research, totaling over $3 million in funding. Her honors include the Davis Memorial Research Award (2007), recognition from the Stevens Board of Trustees for research excellence, and awards from the Bulgarian Ministry of Education. She has held leadership roles, including Chair of the Department of Mathematical Sciences (2018–2021) and co-director of the CRAFT Center (Center for Research toward Advancing Financial Technologies). Her teaching spans courses in nonlinear optimization, stochastic control, and data science. Dr. Dentcheva’s contributions to stochastic optimization theory and applications have been published in over 100 peer-reviewed articles and book chapters. Her recent work explores risk-averse machine learning models, dynamic resource allocation, and bias reduction in sample-based optimization. She actively collaborates with institutions like Rutgers University and serves on editorial boards for journals such as *SIAM Review* and *ESAIM: Control, Optimisation and Calculus of Variations*.

Paul H J Kellyمشاهده پروفایل

استاد

• Compiler Technology
• Parallel Computing
• High-Performance Computing (HPC)
• +۹ مورد دیگر

Paul H J Kelly is a Professor of Software Technology at Imperial College London, leading the Software Performance Optimisation research group. He serves as co-Director of the Centre for Computational Methods in Science and Engineering and Director of Industrial Liaison for the HiPEDS Centre for Doctoral Training in High-Performance Embedded and Distributed Systems. Research Interests His research focuses on: Compiler technology for computational science Performance portability across heterogeneous architectures Domain-specific languages (DSL) for scientific computing Optimization of finite element methods and PDE solvers Data locality and parallelism trade-offs Computer vision algorithms and SLAM systems He actively collaborates with hardware vendors and application developers in computational science, robotics, and quantum chemistry. Article Trends Recent publications emphasize: Temporal and spatial tiling for PDEs and stencil computations Quantum circuit simulation optimization Distributed SLAM systems Performance portability frameworks (e.g., Firedrake, Devito) Compiler techniques for GPUs and custom accelerators Memory hierarchy optimization Scientific Awards Senior Member of the ACM (2021) Imperial College Engineering Faculty Teaching Excellence Award (2013) Best Robotics Paper at 18th Conference on Robots and Vision (2021) Student Mentoring He has mentored numerous PhD and postdoctoral researchers now in academic positions including: Luigi Nardi - Assistant Professor at Lund University Sajad Saeedi - Assistant Professor at Ryerson University Lawrence Mitchell - Assistant Professor at University of Durham Current students include Renato Salas-Moreno , David Ham , and Miklos Homolya .

• Molecular Diagnostics
• Antimicrobial Resistance
• Point-of-Care Technologies
• +۶ مورد دیگر

Jesus Rodriguez Manzano is an Associate Professor in the Department of Infectious Disease at Imperial College London's Faculty of Medicine. He leads research in molecular diagnostics, antimicrobial resistance (AMR), and point-of-care technologies. His work focuses on developing innovative diagnostic devices and leveraging machine learning to enhance diagnostic accuracy and throughput. Dr. Rodriguez-Manzano is Deputy Director of the Centre for Antimicrobial Optimisation (CAMO) and co-founder/CSO of ProtonDx, a diagnostics company. Education: BSc in Biological Sciences, MSc in Advanced Microbiology, and PhD in Microbiology and Biotechnology (University of Barcelona). Postdoctoral research at Caltech (USA) and Imperial College London (UK). Research Interests: Point-of-care diagnostic platforms (e.g., SmartLid, Dragonfly) Machine learning-enhanced PCR multiplexing Host-response biomarker translation Single-molecule PCR mechanism analysis AMR surveillance and outbreak response Affiliations include the NIHR Health Protection Research Unit in HCAI and AMR, CAMO-Net Network, and the Digital Diagnostics for Africa Network. His work addresses global health challenges in resource-limited settings and pandemic preparedness. Grants/Advisory Roles: UK Expert Advisor to the Science and Technology Committee, WHO R&D Blueprint panelist, and NIHR HPRU lead. Over 100 peer-reviewed publications and 15 patent applications demonstrate his impact in diagnostic innovation. Labs/Teams: CAMO’s multidisciplinary team combines microbiology, bioengineering, and data science. Facilities include molecular labs, mass spectrometry, and sensor fabrication units.

Veselin Rakocevicمشاهده پروفایل

مدرس ارشد

• Multihop Wireless Networks
• Vehicular Networks
• Ad-hoc Networking
• +۵ مورد دیگر

Dr. Veselin Rakocevic is a Senior Lecturer in Electronic Engineering at City, University of London (post-merger with St George's). He holds a PhD in Telecommunications from Queen Mary, University of London (2002) and a Dipl-Ing in Electrical & Electronic Engineering from the University of Belgrade (1998). At City, he has served as Head of Department (2015-2018) and Associate Dean for Portfolio Development (since 2023). PhD: Telecommunications, Queen Mary, University of London (2002) Dipl-Ing: Electrical & Electronic Engineering, University of Belgrade (1998) His research focuses on multihop wireless networks , including optimal scheduling , dynamic clustering , cooperation mechanisms , and network self-organisation . Applications span vehicular networks , heterogeneous cellular networks , and energy network optimisation . Over 15 years, his publications demonstrate expertise in 5G/LTE-A protocols , VANET security , and transport-layer multipath tunneling . Recent article trends highlight 5G congestion control , machine learning for traffic identification , and game theory applications in rural wireless networks . He has supervised 12 PhD students with topics covering network optimization , QoS management , and mobile security . Major projects include REACH (EU-India rural broadband) and Wireless Networks for Moving Objects (EU COST Action).

Andrew Kennedyمشاهده پروفایل

استاد

• Materials Science
• Additive Manufacturing
• Porous Materials
• +۷ مورد دیگر

Professor Andrew Kennedy is the Chair in Advanced Manufacturing and Head of the Department of Engineering at Lancaster University . A graduate of Imperial College and Cambridge University, he previously held academic positions at Nottingham University. His research focuses on novel manufacturing methods for advanced materials, particularly multi-phase materials like metal matrix composites, metal foams, and porous materials, using techniques such as additive manufacturing, powder processing, and gel casting. Research Interests: Development of lightweight and energy-absorbing structures, novel batteries and energy storage systems, thermal/fluid flow management, and medical devices. Collaborations: Leads the TWI-Lancaster Joining 4.0 Centre and works with experts in AI, robotics, and machine learning to enhance manufacturing processes. Scientific Achievements: Published over 140 peer-reviewed papers, holds 2 patents, supervised 40+ PhD students, and led 65+ research projects including EU initiatives with 10+ industrial/academic partners. International Collaborations: Partnerships with institutions in Spain, Germany, Finland, Romania, Greece, Italy, Switzerland, China, Thailand, India, Malaysia, Mexico, Chile, Australia, and Canada.

• Machine Learning
• Ensemble Learning
• Dempster-Shafer Theory of Evidence
• +۹ مورد دیگر

Yaxin Bi is a Professor in the School of Computing at Ulster University and a core member of the Artificial Intelligence Research Centre, with over thirty years of research experience in AI applications. His work bridges theoretical advances in machine learning with real-world problem-solving across diverse domains. His educational background includes a BSc (Hons) in Computing Science, an MSc by research in Computing Application, and a PhD in Text Categorization with ensemble learning approaches. These qualifications established the foundation for his pioneering work in evidence theory and classifier systems. Professor Bi's research centers on machine learning and ensemble learning integrated with Dempster-Shafer theory of evidence, focusing on developing robust data analytics methods for decision-making under uncertainty. Key application areas include satellite data anomaly detection, manufacturing process optimization, energy systems analysis, agricultural monitoring through crop classification and disease detection, digital twin development, sentiment analysis, and multi-sensor activity recognition. His methodology emphasizes practical implementation of theoretical frameworks to address complex real-world challenges. Analysis of recent publications (2024-2025) reveals a strategic focus on high-impact applications of AI in critical infrastructure and environmental monitoring. Key trends include the convergence of deep learning (LSTM, GAN) with evidence theory for seismic prediction, optimization of industrial manufacturing processes, and advancement of information retrieval systems. These works consistently address uncertainty quantification and demonstrate cross-domain applicability from semiconductor fabrication to disaster response. His scientific recognition includes: Senior Fellow of the Higher Education Academy, UK Professor Bi has secured over £5 million in competitive research funding from major international bodies including the European Space Agency, EU Frameworks and Horizon 2020 programs, Knowledge Transfer Partnership, Invest NI, and the Royal Society. He actively shapes the academic community through editorial roles as Associate Editor for the International Journal of Intelligent Systems and editorial board membership for Real-World Data Science (Royal Statistical Society), alongside steering committee positions for KSEM and SAI conferences. His consultancy projects demonstrate direct industry translation of research. As a core member of Ulster University's Artificial Intelligence Research Centre, he leads initiatives in satellite data analytics, digital twin development, and AI-driven solutions for sustainable development goals, directing current projects including Electromagnetism Anomaly Detection and Seismic Deformation Monitoring through generative AI approaches.

• Building Information Modelling (BIM)
• ICT in the built environment
• Child-friendly outdoor environments
• +۴ مورد دیگر

Professor Lamine Mahdjoubi is Professor of the Built Environment at the University of the West of England (UWE Bristol), Faculty of Environment and Technology, Department of Architecture and the Built Environment. An architect and urban designer by training, he has gained international recognition for integrating advanced ICT solutions into the design, management, and visualisation of the built environment. Education & Qualifications: Qualified in Architecture and Urban Design (specific institutions and dates not provided in the text). Research Interests: Professor Mahdjoubi’s research focuses on the intersection of digital technologies and sustainable urban environments. He develops innovative methodologies and tools for analysing human–environment interactions, with particular emphasis on: Building Information Modelling (BIM) for design, construction, and operations; Virtual and immersive environments for collaborative design and stakeholder engagement; Child-friendly outdoor environments, linking urban design to public health outcomes; Heritage Building Information Modelling (HBIM) for retrofitting and conservation; Blockchain and machine-learning applications for decentralised energy management; Decision-support systems for brownfield redevelopment and risk assessment. Publication Trends: Across >100 peer-reviewed outputs, recent work (2020–2025) demonstrates a clear pivot toward AI and data-driven approaches in the built environment. A dominant strand couples BIM with machine-learning and VR/AR technologies to enhance design coordination, safety, and sustainability. Energy research increasingly integrates blockchain and large-language-model systems for smart grids. A second major strand addresses socio-environmental equity, producing evidence-based guidelines for healthy outdoor spaces for children and refugee communities. Scientific Awards & Recognition: While specific named awards are not listed, Professor Mahdjoubi’s international recognition is evidenced by: Membership of the Advisory Board, International Making Cities Livable (USA); Invited keynote speaker at numerous national and international conferences; Chief/External Examiner roles for universities in the UK and overseas; Founding Director of the pioneering Virtual Reality Enterprise Centre (VREC) at UWE Bristol. Research Funding & Teams: He has secured and directed major projects funded by: UK Engineering & Physical Sciences Research Council (EPSRC); British Academy; European Union Framework Programmes; Qatar National Research Fund (QNRF); Industry partners and local authorities. These initiatives have supported multidisciplinary teams spanning architecture, computer science, public health, and social policy. Laboratories & Centres: Professor Mahdjoubi founded and directed the Virtual Reality Enterprise Centre (VREC) , the first UK centre dedicated to knowledge exchange in visualisation and analysis of the built environment. The centre provides state-of-the-art VR/AR facilities for teaching, research, and industry collaboration.

Bill Martinمشاهده پروفایل

استاد

• Applied Optics
• Spectropolarimetry
• High Resolution Spectrographs
• +۴ مورد دیگر

Professor Bill Martin is a faculty member in the Department of Physics, Astronomy and Mathematics at the University of Hertfordshire's School of Physics, Engineering & Computer Science. Holding a PhD from UC San Diego (1974), he directs research in the Centre for Astrophysics Research and Centre for Atmospheric and Climate Physics Research. His research focuses on Applied Optics , Spectropolarimetry , and High-Resolution Spectrograph development for exoplanet detection. Key areas include fibre optic systems, laser physics interactions, and chlorophyll optical signatures. Recent work demonstrates expertise in atmospheric dust polarization analysis and optical instrumentation for space applications. Analysis of his 59 research outputs (1972-2025) reveals consistent contributions to astronomical instrumentation and atmospheric physics, with significant emphasis on optical engineering solutions for exoplanet characterization and Earth observation systems. His fingerprint analysis shows strong concentration in high-resolution spectrographs (83%), exoplanets (54%), and linear polarization (53%). Professor Martin leads or collaborates on major research projects including: Blinded by the Light (2023-2026): Exoplanet systems research EXOhSPEC (2018-2020): High-resolution spectrograph development OIC: Optical Insect Counting (2017): Rothamsted Insect Survey instrumentation Lens Optimisation (2017-2019): Rapid prototyping for optical systems His collaborative network spans atmospheric physics, astronomy, and optical engineering disciplines, with significant contributions to sensor development for environmental monitoring and space applications.

Massimiliano Vasileمشاهده پروفایل

استاد

• Computational Optimisation
• Astrodynamics and Mission Analysis
• Space Debris and Asteroid Manipulation
• +۵ مورد دیگر

Massimiliano Vasile is a Professor in the Department of Mechanical and Aerospace Engineering at the University of Strathclyde. His expertise lies in computational optimisation, astrodynamics, and autonomous space systems. He leads major networks such as Stardust (asteroids/space debris), UTOPIAE (uncertainty treatment), and the EPSRC ENCORE network (resilience in engineering systems). Vasile has pioneered methods like Evidence Based Robust Optimisation and developed algorithms for debris removal, asteroid navigation, and multi-objective control. Research focuses include: Optimisation under uncertainty Space debris mitigation and active removal Autonomous spacecraft navigation AI-driven sensor fusion Space sustainability metrics Key achievements include: Innovative trajectory design for binary asteroids Development of CubeSat-based debris removal systems Advances in hyperspectral imaging for space object analysis He has received prestigious awards including Royal Astronomical Society Fellowship, AIAA Associate Fellowship, and IEEE Senior Membership. Current projects address space traffic coordination, solar power satellite engineering, and ethical use of spatial data in human rights contexts.

Hai Huyen Heidi Damمشاهده پروفایل

مدرس ارشد

• Digital Signal Processing
• Wireless Communications
• Channel Equalisation
• +۴ مورد دیگر

Dr. Hai Huyen Heidi Dam is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computer, and Mathematical Sciences (EECMS), under the Faculty of Science and Engineering. Her research focuses on digital signal processing, wireless communications, channel equalization, and digital filter design and optimization. She holds a BSc (Hons) and PhD (Curtin) in related fields. Her work spans theoretical and applied signal processing, including speech enhancement, blind signal separation, and robust beamforming. Key contributions include optimized filter design, multiuser MIMO systems, and adaptive feedback control in hearing aids. Dr. Dam has published extensively in journals like IEEE Transactions on Signal Processing and Circuits Systems and Signal Processing. Her research trends emphasize optimization algorithms, real-time signal processing, and practical implementations in acoustics and communications. Collaborations with industry and academia highlight her contributions to noise reduction, microphone array systems, and sensor technologies. Active in academic service, she contributes to the Office of the Provost at Curtin's Perth campus. Her lab and team focus on advancing signal processing solutions for real-world challenges in audio, communications, and control systems.

• Systems Modelling
• Optimisation
• Biomedical Engineering
• +۴ مورد دیگر

Jill Stewart is a Professor in Systems Modelling and Optimisation at the University of Derby's College of Health, Psychology and Social Care. Her research focuses on biomedical engineering, particularly in intradialytic blood pressure monitoring and haemodialysis optimization, alongside contributions to aerospace engineering and thermal management systems. Stewart has collaborated extensively with colleagues such as Paul Stewart and Maarten W. Taal, producing impactful work in journals like Nephrology Dialysis Transplantation and the Journal of Heat Transfer . Her research interests span systems optimisation, biomedical technology development, and aerospace systems design. Key areas include real-time blood pressure monitoring during dialysis, constructal design principles, and thermal management solutions for electric motors. She also explores neural mass modeling and flight control systems, demonstrating interdisciplinary expertise. Recent articles emphasize advancements in non-invasive medical monitoring and systems modeling, with a focus on optimizing dialysis treatments. Earlier contributions include studies on aircraft propulsion and thermal management in engineering systems. No scientific awards or fellowships were mentioned in the provided information. No formal advisees or grant information were detailed in the text. Her work spans collaborations across biomedical and mechanical engineering fields, with no specific lab or team affiliations explicitly noted.

Bugra Alkanمشاهده پروفایل

مدرس ارشد

• Smart Manufacturing Systems
• Collaborative Robotics
• Industrial Artificial Intelligence
• +۷ مورد دیگر

Dr Bugra Alkan is a Senior Lecturer in Artificial Intelligence and Robotics at the School of Computer Science and Digital Technologies , London South Bank University . With a PhD in Engineering from University of Warwick (2019), he has held postdoctoral positions at University of Bristol and University of Warwick . Academic Rank: Senior Lecturer Institutional Roles: Module Leader for Industrial Cyber-Physical Systems, Artificial Intelligence, Systems Cybersecurity Editorial Roles: Associate Editor for Industrial Robot and Heliyon , Editorial Board Member for MDPI Sensors and Frontier of Industrial Engineering Research focuses on smart manufacturing , collaborative robotics , and industrial AI with emphasis on cyber-physical production systems , digital twins , and Industry 5.0 . Key projects include: Data-driven Configuration Optimisation of CPPS AI-Enabled Digital Life-cycle Management Deep Learning-based Inline Quality Inspection Human-centric Collaborative Assembly 5.0 Scientific contributions include: Best Paper Awards at CIRP CATS 2016 and IATS’13 Over 40 peer-reviewed publications with h-index 16 Editorial leadership in Q1/Q2 journals Teaching responsibilities span artificial intelligence , cyber-physical systems , and statistical modeling at both undergraduate and postgraduate levels. Current research involves EU-funded TWIN-IT-ROMANS project (€1.76M) addressing robotics manufacturing systems.

Kevin Michael Smithمشاهده پروفایل

دانشیار

• Energy Engineering
• Building Performance Simulation
• HVAC Systems
• +۷ مورد دیگر

Kevin Michael Smith is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), where he conducts research in energy-efficient building systems, district heating, and sustainable building retrofits. He is based at the Energy and Services research group in Kgs. Lyngby, Denmark. His research focuses on natural ventilation in retrofitted apartment buildings , data-driven optimization of heating systems , and integration of BIM with dynamic simulations . Key areas include improving indoor air quality, reducing energy consumption, and enhancing the performance of district heating networks through smart control strategies. Recent publications reveal a strong trend toward AI-based methods , virtual sensing , and grey-box modeling for building energy services, particularly in residential contexts. His work bridges practical implementation with advanced simulation techniques. He actively supervises multiple PhD students and leads interdisciplinary research projects involving cyber-physical systems and smart building technologies. Data-Enabled Heating Optimisation in Apartment Buildings Intelligent building energy services through data-driven cyber-physical models HeatCheck: AI-driven optimal heating of apartment buildings His scientific contributions support UN Sustainable Development Goals related to affordable and clean energy, sustainable cities, and climate action. While no formal awards are listed, his leadership in cutting-edge energy research underscores significant impact in the field of building performance engineering.