جست‌وجوی استاد و پژوهشگر

Yuyan Zhengمشاهده پروفایل

مدرس ارشد

• Leadership
• Employee Performance
• Wellbeing
• +۲ مورد دیگر

Dr. Yuyan Zheng is a Senior Lecturer in Organisation Psychology/Organisation Studies at Surrey Business School, University of Surrey. She holds a PhD in Management from Durham University and previously held academic positions at the University of Sheffield (as Lecturer in Leadership), Durham University (as Post-Doctoral Research Associate), and the London School of Economics (as Teaching Fellow in Organizational Behaviour). Her work bridges organizational psychology and management studies. Her research explores: Leadership dynamics across ethical, authoritarian, servant, and paradoxical paradigms Employee wellbeing in contexts of work-nonwork spillover and stress Identity formation through professional roles and values internalization Behavioral outcomes including ethical voice, performance, and newcomer adjustment Methodological innovation using explainable machine learning and meta-analytic techniques Her 15 most recent publications (2021-2025) demonstrate strong methodological diversity, including meta-analyses, machine learning applications, and multi-wave surveys. Key themes examine leadership during crises (e.g., COVID-19), ethical decision-making mechanisms, and cross-cultural management. Articles consistently feature moderated mediation models analyzing psychological processes. Teaching responsibilities include Quantitative Research Methods (MAND028) and Leadership (MAN3119) courses. No awards, grants, or supervised students are documented in available sources.

• Computer Vision
• Artificial Intelligence (AI)
• Distributed Ledger Technology (DLT)
• +۵ مورد دیگر

John Collomosse is a Professor of Computer Vision and AI at the University of Surrey, leading DECaDE (UKRI/EPSRC Centre for the Decentralised Digital Economy) and the Centre for Vision, Speech and Signal Processing (CVSSP). He also serves as a Principal Scientist at Adobe Research, managing the Cross-Modal Representation Learning (XRL) group. His research focuses on AI, Distributed Ledger Technology (DLT), media provenance, and blockchain applications to combat misinformation and enhance data integrity. Collaborations include the Content Authenticity Initiative (CAI) and the ARCHANGEL project, which pioneered AI and blockchain for tamper-proof archives. He holds a PhD, is a Fellow of the IET, and has advised UK/EU bodies on digital economy policies. His work bridges academia and industry, with contributions to generative AI, watermarking, and decentralized systems. Publications span content authenticity, style transfer, and generative models. Awards include a 2024 prestigious fellowship. His labs include Surrey Institute for People-Centred AI (PAI) and DECaDE, fostering interdisciplinary research in AI ethics, provenance, and digital economy frameworks.

Jean-Yves Guillemautمشاهده پروفایل

مدرس ارشد

• 3D Computer Vision
• 3D Reconstruction
• Computational Photography
• +۴ مورد دیگر

Dr. Jean-Yves Guillemaut is a Senior Lecturer in 3D Computer Vision and Postgraduate Research Director at the Centre for Vision, Speech and Signal Processing (CVSSP) within the School of Computer Science and Electronic Engineering at the University of Surrey. His research focuses on 3D reconstruction of complex dynamic scenes, particularly addressing challenges with glossy materials and uncontrolled outdoor environments. He collaborates with industry to apply his work in AR/VR, immersive content production, and free-viewpoint video. Education: He holds an MEng (hons), PhD, and is a member of professional bodies including MIEEE, MBMVA, and FHEA. His technical expertise spans computational photography, lightfield imaging, and artificial intelligence. Current PhD students: Matthew Bailey, Yue Zhang, Gianmarco Addari Laboratory affiliations: CVSSP Research interests include scene modeling from multi-view video, dynamic scene reconstruction, and applications in creative industries. Recent projects involve developing algorithms for illumination estimation, pedestrian tracking, and neural rendering. Grants and collaborations are centered on industry partnerships enhancing creative technology sectors. Future work aims to expand outdoor scene modeling and AI-driven medical imaging applications.

Christina Silverمشاهده پروفایل

دانشیار

• Qualitative Methodology
• Computer-Assisted Qualitative Data Analysis (CAQDAS)
• Technology in Research
• +۳ مورد دیگر

Dr. Christina Silver is an Associate Professor (Teaching) in Sociology at the University of Surrey and Director of the CAQDAS Networking Project. She holds a PhD from the University of Surrey (2002), an MSc in Social Research Methods (Surrey, 2000), and a BA (Hons) in Politics and Sociology (Essex, 1997). Her work focuses on qualitative methodology, particularly the integration of technology like CAQDAS software into research and pedagogy. As Director of the CAQDAS Networking Project since 1998, she oversees training programs, advisory services, and course development for researchers globally. Her research explores how software tools like NVivo, ATLAS.ti, and MAXQDA enhance qualitative analysis, with a focus on pedagogical frameworks such as the Five-Level QDA method. She has pioneered online teaching strategies for CAQDAS during the pandemic, emphasizing synchronous learning and digital adaptability. Key contributions include co-developing the Five-Level QDA method, which structures learning through objectives, plans, and software tool utilization. Her recent work addresses AI’s role in qualitative analysis, balancing innovation with critical reflection. She has collaborated with institutions like Southampton and Birmingham Universities on projects such as the Mass Observation longitudinal study. Publications span over two decades, covering CAQDAS software comparisons, methodological debates, and educational innovations. Her work bridges technical proficiency with methodological rigor, influencing both researchers and educators worldwide.

• Quantum Information
• Quantum Cryptography
• Post-Quantum Cryptography
• +۷ مورد دیگر

Carlo Ottaviani is a Senior Lecturer in the Department of Computer Science at the University of York and a member of the York Centre for Quantum Technologies. His academic qualifications include a PhD in Physics & Computer Science, and Fellowships from the Advance HE (HEA) in 2023 and 2013. He has held roles such as Senior Research Fellow and Research Associate within the department, contributing to quantum information, post-quantum cryptography, and quantum networks. Education: PhD in Physics & Computer Science PGCAP & Fellow of Advance HE (2023) YLTA & Associate Fellow of Advance HE (2013) Research Interests: Quantum Information and Quantum Technologies Quantum Cryptography (QKD), Post-Quantum Cryptography Quantum Optics and Quantum Atom-Optics Security, Continuous-Variable Quantum Systems Dr. Ottaviani has contributed to major projects, including the UK Quantum Technology Hub for Quantum Communications Technologies. His work focuses on developing secure quantum communication protocols and advancing theoretical frameworks for quantum systems. He actively participates in academic collaborations and has authored over 45 publications in peer-reviewed journals and conferences. Grants and Projects: Principal Investigator for projects on Coherent Control of Quantum Optical Systems and Quantum Non-Linear Optics Contributor to the EPSRC-funded UK Quantum Communications Hub Labs/Teams: York Centre for Quantum Technologies (YCQT) Quantum Information and Cyber Security & Privacy Research Groups

• Computer Vision
• Machine Learning
• Cognitive Robotics
• +۳ مورد دیگر

Dr. Kasim Terzic is a Lecturer at the School of Computer Science, University of St Andrews. He is affiliated with the Centre for Research into Ecological & Environmental Modelling and the Coastal Resources Management Group. His research focuses on computer vision, machine learning, cognitive robotics, and their applications in ecology and conservation. He also promotes open-source software solutions. Terzic holds a PhD in Computer Science from the University of Hamburg and has taught modules such as Computer Graphics and Machine Learning. He currently supervises four PhD students and serves as an External Examiner at Robert Gordon University. Education Background: PhD in Computer Science, University of Hamburg MSc in Information and Communication Systems, Hamburg University of Technology MSc in Global Technology Management, Hamburg University of Technology BEng (Hons) in Electronic Engineering, University of East Anglia Research Interests: Terzic’s work bridges computer vision with ecological conservation, developing algorithms for image analysis, robotic manipulation of deformable objects, and active vision systems. He emphasizes interdisciplinary approaches, combining AI with ecological monitoring and open-source technologies to enhance accessibility. His projects include fish scale circuli detection, robotic towel manipulation, and individual re-identification in wildlife populations. Advising & Grants: Supervises four PhD students and actively contributes to academic activities, including organizing public events like Doors Open @ Computer Science. His research has been published in venues like Sensors, Biology Methods and Protocols, and IEEE conferences. Labs/Teams: Collaborates with the Centre for Research into Ecological & Environmental Modelling and Coastal Resources Management Group, focusing on applying AI to environmental challenges.

Yulu Piمشاهده پروفایل

پژوهشگر

• Machine learning
• XAI
• Policy making
• +۳ مورد دیگر

Yulu Pi is a Researcher at the Centre for Interdisciplinary Methodologies, University of Warwick. Her work focuses on developing interactive algorithmic systems to enhance AI adoption in the public sector, bridging machine learning and policy-making processes. She holds a background in data science and economics, with prior experience in governmental and international organizations. Research Interests: Machine learning, Explainable AI (XAI), policy-making methodologies, and algorithmic decision-making frameworks for public institutions. Her work emphasizes data-driven policy predictions and cost-efficient policy trials through advanced ADM systems. Publications include a 2021 paper in JeDEM - EJournal of EDemocracy and Open Government , exploring machine learning applications in government contexts. She received the Chancellor’s International Scholarship (2021-22) through the Centre for Interdisciplinary Methodologies. Her PhD research, titled 'Interactive Algorithmic Decision-Making For Public Policy,' addresses the challenges of predicting policy outcomes through computational models. No formal student advisement roles are currently listed.

• 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.

• Terahertz Engineering
• Biomedical Engineering
• Medical Imaging
• +۳ مورد دیگر

Dr. Robert Donnan is a Reader in Terahertz Engineering at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on Terahertz Engineering, biomedical applications of electromagnetic systems, and advanced imaging technologies. He holds prestigious fellowships including Fellow of the Institute of Physics (FInstP) and Fellow of the Institution of Engineering and Technology (FIET). His work bridges disciplines such as medical imaging, nanotechnology, and materials science. Recent studies include developing AI-driven denoising techniques for Optical Coherence Tomography (OCT), designing THz antennas for biomedical applications, and exploring electromagnetic triggering for drug delivery systems. His research also extends to material characterization using sub-THz spectroscopy and microfluidic systems. Dr. Donnan's publications span innovations in terahertz engineering and biomedical instrumentation, with a strong emphasis on translating theoretical advancements into practical clinical and engineering solutions. His awards reflect recognition of his contributions to interdisciplinary research at the intersection of physics, engineering, and healthcare.

Ekaterina Ivanovaمشاهده پروفایل

مدرس

• Human-Robot Interaction
• Haptic Communication
• User-Centred Robotics
• +۳ مورد دیگر

Dr. Ekaterina Ivanova is a Lecturer (Assistant Professor) in Human-Machine Interaction at Queen Mary University of London's School of Electronic Engineering and Computer Science. She is affiliated with the Centre for Human-Centred Computing, focusing on multimodal human-robot interaction, haptic communication, and user-centred robotics for medical applications. Her research integrates robotics, data science, neuroscience, and clinical expertise to develop assistive technologies. Teaching: She teaches modules such as ECS7029P Research Methods and ECS733P Interactive System Design, emphasizing interdisciplinary and hands-on approaches. Research Interests: Her work spans haptic communication, neurorehabilitation, and robot-assisted motor learning. Recent studies explore human-robot collaboration in training, sensory augmentation, and motor performance optimization. Grants: Improving motor learning via haptic human-human and human-robot interaction (Royal Society, £12,000) Multimodal human-human Interaction in Negotiation Tasks (Royal Society, £12,000) UKRI CDT in Artificial Intelligence and Music (EPSRC, £6.5M) Labs/Teams: Active contributor to the Centre for Human-Centred Computing, collaborating on projects like supernumerary limb systems and haptic social interaction.

• Engineering Education
• Telecommunications
• Control Systems
• +۱ مورد دیگر

Dr. Tijana Timotijevic is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. She specializes in control systems, telecommunications, and engineering education innovation. Her teaching spans undergraduate and postgraduate courses in control systems, electric/magnetic fields, and electronic devices. She holds a PhD in Telecommunications and an MSc in Biomedical Engineering. Current research focuses on enhancing engineering education outcomes, alongside prior work in telecommunications and network performance. Education qualifications include BEng (Hons), PhD (Telecommunications, 1999), and MSc (Biomedical Engineering, 2007). Her publications (2000–2013) address sensor networks, motion capture, QoS in packet networks, and satellite communication systems. She advises on improving student learning methodologies and contributes to curriculum development. Office hours are Tuesday 09:00-10:30 in Eng E302.

Wenwu Wangمشاهده پروفایل

استاد

• Signal Processing
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Wenwu Wang is a Professor of Signal Processing and Machine Learning at the University of Surrey's School of Computer Science and Electronic Engineering, and serves as Associate Head (External Engagement). He is Co-Director of the Machine Audition Lab within CVSSP and an AI Fellow at Surrey's Institute for People Centred Artificial Intelligence. Education: Holds a BSc, MSc, and PhD (specific disciplines not specified). Research focuses on unsupervised learning techniques , computational auditory scene analysis , and multimodal machine learning . Notable projects include audio captioning systems, text-to-audio generation (e.g., AudioLDM), and anomalous sound detection frameworks. Grants: £30M+ total portfolio (as PI: £2.2M; as CI: £14M+). Funders include EPSRC, MoD, EU, and industry partners like BBC/Huawei. Key Projects: AudioTurbo (fast text-to-audio), SemantiCodec (ultra-low bitrate audio), DCASE Challenge contributions. Lab Leadership: Machine Audition Lab explores intersections of audio perception and AI. Recent work emphasizes large audio models , cross-modal generation, and real-world applications in aquaculture monitoring and urban soundscapes.

Pei Xiaoمشاهده پروفایل

استاد

• Wireless Communications
• 5G/6G Networks
• Signal Processing
• +۶ مورد دیگر

Professor Pei Xiao is a leading academic in wireless communications at the University of Surrey’s Institute for Communication Systems (5GIC), part of the School of Computer Science and Electronic Engineering. He holds a BEng from Huazhong University of Science & Technology, MSc from Tampere University of Technology, and PhD from Chalmers University of Technology. As technical manager of 5GIC, he oversees major 5G/6G research projects, coordinating activities across academia and industry. His research focuses on cutting-edge areas including 5G/6G network design, satellite communications, reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), and machine learning-driven optimization. Key projects include EPSRC-funded initiatives on massive machine communications and industrial IoT systems. Professor Xiao’s recent publications emphasize innovations in beamforming, non-orthogonal multiple access (NOMA), and hybrid AI-hardware solutions for next-generation networks. He actively contributes to standards development through collaborations with Nokia Networks and global telecom partners. His work bridges theoretical advancements with practical implementations, addressing challenges in latency, energy efficiency, and network scalability.

Kamalan Jeevaratnamمشاهده پروفایل

استاد

• Veterinary Medicine
• Clinical Physiology
• Cardiovascular Research
• +۴ مورد دیگر

Professor Kamalan Jeevaratnam holds dual roles as the Head of School of Veterinary Medicine and Professor of Clinical Physiology at the University of Surrey. His academic work spans veterinary medicine, clinical physiology, and interdisciplinary research in cardiovascular and neurological disorders. He leads a team advancing electrophysiological studies in animal models and human diseases. Research interests include cardiac electrophysiology (focusing on arrhythmias and aging effects), Parkinson's disease pathophysiology, and veterinary education methodologies. He has pioneered studies on feline blood donation safety and AI applications in equine healthcare. His work integrates machine learning for diagnostic tool development and explores molecular mechanisms in genetic cardiac conditions. Notable contributions include collaborative projects on diabetes-related cardiovascular risks and global mentorship initiatives to enhance research equity. He maintains strong ties with international institutions, evidenced by Hong Kong-based cohort studies and Saudi Arabia educational partnership efforts. Publications emphasize translational research bridging veterinary and human medicine, with a focus on clinical practice improvements and novel diagnostic approaches. His interdisciplinary approach addresses challenges in both animal and human healthcare systems.

Bernardo Castro Dominguezمشاهده پروفایل

مدرس ارشد

• Digital Process Engineering
• Machine Learning for Materials Discovery
• Continuous Manufacturing
• +۳ مورد دیگر

Bernardo Castro Dominguez is a Senior Lecturer in Chemical Engineering at the University of Bath, leading the Smart Process Engineering Lab. His research integrates engineering, chemistry, robotics, and computer science to develop sustainable materials and processes for pharmaceuticals, sensing, and waste recycling. He holds a Ph.D. in Chemical Engineering from the University of Tokyo and M.S./B.S. degrees from the University of Utah. Dominguez's work focuses on digital process engineering, machine learning for materials discovery, and sustainable manufacturing. His lab develops innovative methods like electrospinning for membrane fabrication and AI-guided material design, emphasizing environmental sustainability. He collaborates on projects including hydrochar production, CO2 conversion, and biomedical manufacturing. Publications show strong emphasis on membrane technology, additive manufacturing, and computational modeling for industrial applications.