Dr. Chee Kiat Seow is an Associate Professor at the University of Glasgow's School of Computing Science. He holds a PhD from Nanyang Technological University (NTU) and an MSc from the National University of Singapore (NUS). His research focuses on cyber-physical security, wireless communication localization, and IoT systems leveraging AI/ML. He has led projects valued in the millions, winning awards like the IEEE Best Student Paper and National Instruments Engineering Impact Awards. Education: PhD (NTU), MSc (NUS) Research: Specializes in UWB positioning, spoofing detection, and IoT integration with 5G/GNSS. Teaching: Courses include Big Data, Software Engineering, and Data Analytics. His recent work addresses NLOS mitigation in indoor localization and cyber-physical security threats. Over 63 publications span journals like IEEE Transactions and conferences such as IPIN and WF-IoT. Supervised 6+ PhD/MSc students on topics like autonomous robotics and AI-driven localization. Grants: Includes $853K for 5G-X Smart Building projects and $797K for GNSS signal authentication. Awards: IEEE PIERS Best Student Paper (2019), NI Engineering Impact Awards (2015-2016). He advises on IoT and cybersecurity for organizations like ARTC and National Instruments. Active in IEEE Signal Processing and Computer Society.
Christos Gatzidis serves as Executive Dean of Bournemouth University's Faculty of Science and Technology since October 2023, overseeing six departments including Computing and Informatics, Creative Technology, and Psychology. Previously Deputy Dean (2021-2023) and Head of Creative Technology Department (2016-2021), he was appointed Professor in Creative Technology in November 2019. The Faculty leads five REF Units of Assessment and secures funding from AHRC, NIHR, and Innovate UK for research spanning digital healthcare, gaming technologies, and cultural heritage applications. His educational qualifications include: PhD in Information Science, City University London (2010) PG Cert in Research Degree Supervision, Bournemouth University (2010) MA in Computer Animation, Teesside University (2003) BSc (Hons) in Computer Studies (Visualisation), University of Derby (2002) Professor Gatzidis specializes in computer graphics with research spanning virtual reality, serious games, and digital healthcare applications. His work bridges technical innovation and practical implementation, particularly in mindfulness prototypes for healthcare and stroke rehabilitation systems. Current projects focus on the multidisciplinary application of gaming technologies in medical contexts, emphasizing user experience and therapeutic outcomes through collaborations with industry partners. His publication record (2014-2025) demonstrates evolving expertise from foundational computer graphics research in terrain generation and deformation to applied work in healthcare, cultural heritage, and music education. Key trends include virtual reality for therapeutic mindfulness, usability studies in mobile gaming, and digital cultural presentation techniques, reflecting a trajectory toward socially impactful technological solutions with strong industry translation. No scientific awards are documented in the provided information. He has supervised PhD students and secured competitive research funding, including two Innovate UK Knowledge Transfer Partnerships. His principal investigator role in a virtual reality mindfulness prototype project exemplifies his approach to translating academic research into practical industry solutions, with current focus on expanding knowledge exchange activities to support the University's civic engagement mission. As Executive Dean, he leads faculty-wide research strategy across six departments, fostering interdisciplinary collaborations particularly in digital healthcare and cultural heritage. His personal research integrates computer graphics expertise with clinical applications through partnerships with healthcare providers and technology companies, driving innovation in therapeutic VR systems and educational gaming platforms.
Changjian Li is an Assistant Professor in the School of Informatics at the University of Edinburgh. He leads the GraphViX Group (Graphics, Vision and X) and is a member of the Institute of Perception, Action and Behaviour (IPAB). His research spans computer graphics, computer vision, and human-computer interaction with a focus on 3D generation and analysis. Education: Bachelor's Degree from Shandong University (2014) Ph.D. from the University of Hong Kong (2019) under Prof. Wenping Wang Postdoc at University College London (UCL) with Prof. Niloy Mitra Starting Researcher position at Inria with Dr. Adrien Bousseau Research Interests: Changjian's research focuses on sketch-based 3D modeling, CAD modeling, point cloud processing, and medical imaging applications. He develops systems that bridge intuitive sketching with precise CAD workflows, enhances 3D animation pipelines, and applies neural methods to sparse medical data reconstruction. Scientific Recognition: Best Paper Honorable Mention Award (MICCAI 2021) CADTalk selected as Highlight (CVPR 2024 top 10%) ACM SIGGRAPH Asia 2018 cover image selection ACM SIGGRAPH Asia 2015 technical paper highlight CVPR 2019 poster highlighted in 'Computer Vision News' Advising & Collaborations: He mentors postdocs and PhD students including Duolikun Danier, Haocheng Yuan, Ankan Bhunia, and Lei Zhong. Former advisees include Salvatore Esposito (now at Edinburgh), Guangshun Wei (Shandong University), and Mingjun Yang (University of Melbourne). Collaborates with Oisin Mac Aodha, Hakan Bilen, and Niloy Mitra. Professional Service: Currently serves as Associate Editor for IEEE TVCG and participates in program committees for SIGGRAPH Asia, SIGGRAPH, EuroGraphics, and Geometry Design and Computing (GDC) conferences.
Julia Camps is a postdoctoral research associate at the University of Oxford, Department of Computer Science. Her work bridges Computational Biology and Health Informatics, focusing on cardiac digital twin development for precision medicine applications. She specializes in combining data-driven and mechanistic approaches for in silico clinical trials, particularly through Purkinje network modeling and ECG-based calibration. Education: Informatics Engineer (2014) and Master's in Artificial Intelligence (2015-2017) from Universitat Politècnica de Catalunya PhD in Computer Science (2017-2021) at Oxford, completed within the Computational Cardiovascular Science research group under Prof Blanca Rodriguez Current role: postdoc in Prof Rodriguez's group since 2021, focusing on post-myocardial infarction disease progression Software development: open-source cardiac digital twin tools available on GitHub Her research interests center on creating patient-specific cardiac digital twins using multimodal clinical data. This work enables virtual therapy evaluation and in silico clinical trials through: Integration of statistical inference and machine learning techniques Development of Purkinje network models from clinical ECG data Electrophysiological and repolarization sequence modeling Gait detection algorithms for Parkinson's disease applications Recent publications (2024-2025) demonstrate trends in: GPU-accelerated cardiac electrophysiology simulations (MonoAlg3D) Topology-informed ECG electrode localization Sex-specific electromechanical cardiac modeling Multi-modal characterisation of diabetic cardiac deterioration Pro-arrhythmic risk assessment for stem cell therapies
Professor David Thomas holds the position of Professor in Computer Engineering at the University of Southampton's Electronics and Computer Science Department. His research focuses on the intersection of software and hardware, particularly leveraging FPGAs for novel digital architectures and event-driven computing. He has a notable academic trajectory, having previously served as a Lecturer and Senior Lecturer at Imperial College London before joining Southampton in 2021. Dr. Thomas is actively involved in supervising PhD students and contributes to interdisciplinary research projects funded by the EPSRC, such as the SONNETS initiative exploring scalable event-triggered systems. Education: BSc in Computer Science (Imperial College London), PhD in Digital Architectures (Imperial College London). Postdoctoral roles included Research Associate and Research Fellow at Imperial's Department of Computing. Research Interests: Event-driven computing, FPGA-based systems, high-level synthesis, and high-performance computing. His work emphasizes practical implementations of theoretical models, such as custom processors and application-specific accelerators. Current projects include optimizing random number generation for FPGAs and exploring meta-programming techniques for hardware design. Advising and Grants: Supervises multiple PhD students in areas like neuromorphic computing and algorithm optimization. Active in securing funding for distributed system architectures and FPGA-based solutions. Labs/Teams: Member of the Cyber Physical Systems research group. Collaborates with interdisciplinary teams on projects like POETS (Partially Ordered Event-Triggered Systems) for large-scale parallel computing.
Michael O'Dea is a Senior Lecturer in the Department of Computer Science at the University of York, United Kingdom. He has held previous academic positions at York St John University, Beijing University of Technology, University of Hull, and Waikato Institute of Technology, bringing extensive international experience in computer science education. He is actively engaged in pedagogical scholarship and leadership in higher education innovation. Senior Lecturer, Department of Computer Science, University of York Senior Lecturer in Computer Science, York St John University Lecturer in Software Engineering, Beijing University of Technology, China Lecturer in Computer Science, University of Hull Lecturer in Information Technology, Waikato Institute of Technology, NZ Dr. O'Dea earned his Ed.D. in Computer Based Learning from the University of Leeds. His research centers on the integration of artificial intelligence into educational practices, with a strong emphasis on AI literacy, the effectiveness of generative AI in teaching and learning, and the evolving landscape of technology acceptance in higher education. He investigates how AI tools can enhance student learning, faculty development, and institutional policy. His recent publications span topics such as AI literacy assessment, the future of online and blended learning, the application of machine learning in earthquake prediction, and international study abroad effectiveness. These works reflect a broad interdisciplinary approach, combining computer science, educational theory, and policy analysis. His scholarship is increasingly focused on the transformative potential of generative AI in academic settings, as evidenced by his leadership in special journal issues and funded research projects. Dr. O'Dea holds significant editorial responsibilities as Associate Editor and Lead Guest Editor for the Journal of University Teaching and Learning Practice and as Guest Editor for a special issue in Education Sciences on generative-AI-enhanced learning. He is also an Invited External Academic Affiliate at the King's Institute for Artificial Intelligence, King's College London. Associate Editor - Special Issues, Journal of University Teaching and Learning Practice Lead Guest Editor, Special Issue on Technology Acceptance Models, JUTLP (2024) Guest Editor, Special Issue on Generative-AI-Enhanced Learning, Education Sciences Principal Investigator, QAA Collaborative Enhancement Project on Graduate Attributes in the Era of GenAI (2025) He has delivered numerous invited talks and workshops at institutions such as the University of York, Queen Mary University of London, and international conferences including the Academy of Management and the International Conference on Artificial Intelligence in Education. His work bridges research, practice, and policy in higher education, with a strong commitment to inclusive and innovative teaching methodologies.
Dr. Martin Kleppmann is an Associate Professor at the University of Cambridge, specializing in local-first software and security protocols . He leads research in distributed systems, focusing on decentralized architectures, collaborative editing tools, and cryptographic methods. As a key contributor to the Automerge open-source project, he bridges academic innovation with real-world applications. Formerly a research fellow at TU Munich (2022–2023) and Cambridge (2015–2022), he has also worked as a software engineer and startup founder, including LinkedIn (acquired 2012). Research Interests span Distributed Systems Security , Conflict-Free Replicated Data Types (CRDTs) , Collaborative Software , and Cryptography . His work addresses challenges in decentralized social networks, privacy-preserving protocols, and efficient data synchronization. Recent projects include Kintsugi (end-to-end encrypted key recovery) and Pudding (private user discovery for anonymity networks). Publications emphasize Collaborative text editing (2025: Eg-walker, 2023: The Art of the Fugue) CRDTs for JSON and trees (2021, 2017) Privacy in decentralized systems (2024: Pudding, 2025: Emission Impossible) Scientific Awards include Gilles Muller Best Artifact Award (EuroSys 2025) Distinguished Paper & Artifact Awards (OOPSLA 2017) Best Presentation Awards (Security Protocols Workshop 2018, PaPoC 2025)
Prof. David Ham is a Professor of Computational Mathematics at the Department of Mathematics, Faculty of Natural Sciences, Imperial College London. His research focuses on high-level abstractions for scientific computation, particularly in geophysical fluids and numerical software. He leads the Firedrake project and co-developed the dolfin-adjoint framework, which received the 2015 Wilkinson Prize for Numerical Software. Ham holds a BSc (Mathematics) and LLB from The Australian National University, and a PhD from TU Delft. His career includes roles as a NERC Independent Research Fellow and Grantham Research Fellow at Imperial College. He is affiliated with the Grantham Institute, Mathematics of Planet Earth, and Software Performance Optimisation groups. His research spans computational science, including finite element methods, adjoint-based inversion, and parallel computing. Recent work emphasizes differentiable programming integration with machine learning and geophysical modeling. Ham has contributed to numerous grants and projects, including EPSRC and NERC-funded initiatives. He leads development of software tools like Firedrake and Thetis, advancing computational methods for oceanography and geodynamics.
Professor Barry Porter is a faculty member at Lancaster University in the School of Computing and Communications . His research focuses on emergent software platforms that address software complexity through component models , meta-software platforms , and machine learning . Key areas include distributed systems, cloud integration with sensor nodes, green computing, and real-time visualization. Research Interests : Runtime adaptation in complex systems Self-assembling software architectures Machine learning for code optimization Distributed emergent systems at scale Green computing for multi-core environments Edge-cloud continuum integration Recent Publication Trends : His 2025 work explores genetic improvement for software using speciation algorithms , program geometry projection , and multi-agent decision frameworks . Earlier studies (2022-2024) investigate edge-cloud systems , neural transfer learning , and ecosystem curation in emergent software. Supervision & Projects : He supervises PhD student Ben Craine and leads projects like B-EGI (Bio-Enhanced Genetic Improvement) and BBC Prosperity Partnership for media delivery. Collaborations span environmental IoT, multi-agent learning, and fog computing. Labs & Groups : Affiliated with the Lancaster Intelligent, Robotic and Autonomous Systems Centre , Centre of Excellence in Environmental Data Science , and the Distributed Systems group.
Dr. Zhibao Mian is a Lecturer in the School of Computer Science at the University of Hull, UK, and previously held an Associate Professor position at Northwest Normal University. He specializes in trustworthy AI, machine learning, and intelligent maintenance systems. His research integrates AI with IoT, blockchain, and digital twins in Industry 4.0/5.0 contexts. He leads projects on predictive maintenance for offshore wind turbines and AI-driven sustainable energy solutions. Dr. Mian holds a PhD from the University of Hull and an MSc from the University of Nottingham. Research interests include AI ethics, model-based safety analysis, and RCM. He has secured grants such as the CPHC-funded study on AI in software education and oversees multiple PhD scholarships. Notable roles include Editorial Board member of the American Journal of Artificial Intelligence and Reviewer for high-impact journals/conferences like JSS and IEEE. He is a Senior Fellow of the Higher Education Academy and received the Royal Academy of Engineering's 2024 Exceptional Talent designation. Recent publications (2023-2025) focus on ordinal networks, outlier detection, Belt and Road trade analysis, and carbon emissions modeling. He actively advises PhD students on topics like UAV-based anomaly detection and predictive maintenance frameworks.
Professor Andrew Ireland is a faculty member in the School of Mathematical & Computer Sciences at Heriot-Watt University, specializing in Computer Science. His research focuses on formal methods, autonomous systems, and the intersection of AI with legal frameworks. He has authored over 39 publications since 1996, with recent work emphasizing safety-critical systems, hazard analysis, and legal implications of autonomous vehicle design. Recent collaborations span international teams addressing transnational legal challenges in AI and autonomous systems. His contributions include developing formal modeling techniques for accident anticipation and ontology-based legal support systems. Ireland has served as an editor for academic journals and conferences, such as the AVoCS 2015 special issue. His work bridges technical innovation with regulatory compliance, ensuring safe implementation of emerging technologies.
Roles and Affiliations : Dimitris Kolovos is a Professor of Software Engineering at the University of York's Department of Computer Science. He leads the Automated Software Engineering (ASE) research group and is an Eclipse Foundation committer, leading development of the Epsilon open-source platform. His roles include research leadership, teaching, and academic service. Education : PhD in Software Engineering - University of York MSc in Software Engineering with Distinction - University of York First Class Honours Degree in Informatics - Athens University of Economics and Business Research Interests : Kolovos focuses on advancing Model-Driven Engineering (MDE), GenAI integration in software development, low-code platforms, and data analytics. His work emphasizes scalable modeling tools, education technology (e.g., MDENet platform), and industry collaboration with organizations like NASA, BAE Systems, and Siemens. Labs and Projects : He leads the Epsilon project under the Eclipse Modelling initiative, developing tools for model transformation, validation, and code generation. His research group also explores AI-driven model transformations and hybrid graphical-textual editors.
Amy Zavatsky is a Reader in Engineering Science at the University of Oxford and Tutorial Fellow at St Edmund Hall, with faculty service since 1996. Her work bridges mechanical engineering and clinical orthopaedics, focusing on lower extremity biomechanics and gait analysis within the Department of Engineering Science. Education: BSc in Bioengineering, University of Pennsylvania DPhil in Engineering Science, University of Oxford (Thouron Award recipient) Research Focus: Prof. Zavatsky pioneers orthopaedic biomechanics research with emphasis on foot/ankle kinematics, knee osteoarthritis mechanisms, and gait compensations. Her work integrates theoretical modeling with in vitro experimentation to develop clinical applications for cerebral palsy, flatfoot, and running injuries. Current projects advance multi-segment foot modeling and cognitive-efficient data visualization for clinical gait analysis. Publication Trends: 2021-2025 works reveal three converging themes: (1) Open-source foot modeling ( OpenOFM ), (2) Data visualization for clinical decision-making, and (3) Sensor optimization using statistical methods. These publications consistently bridge engineering innovation with orthopaedic clinical practice through collaborations with the Oxford Gait Laboratory. Scientific Recognition: Philip Leverhulme Prize (2003) for outstanding early-career scholarship University Teaching Award (2008) for biomechanics instruction and MSc Biomedical Engineering development Departmental Teaching Awards: Silver (2021), Bronze (2022) Institution of Mechanical Engineers Thomas Stephen Prize (1993) Academic Leadership: Prof. Zavatsky directs undergraduate engineering tutorials at St Edmund Hall while teaching mechanical/civil/biomedical engineering courses. She previously served as Director of Graduate Studies (2016-17), Acting MSc Biomedical Engineering Director (2006-07), and Junior Proctor (2012-13). Her DPhil supervision targets lower-limb biomechanics projects requiring strong engineering fundamentals. Research Infrastructure: Based at the Institute of Biomedical Engineering (Nuffield Orthopaedic Centre), she collaborates extensively with the Oxford Gait Laboratory. Her biomechanics research group utilizes motion capture systems and multi-segment modeling to translate engineering principles into clinical rehabilitation protocols.
Dr. Radu Jianu is a Lecturer in the Department of Computer Science at City, University of London , where he has been a faculty member since 2016. He is affiliated with the giCentre , a leading research group in information visualization. He earned his PhD and MSc in Computer Science from Brown University, USA, and a Diploma in Engineering from the Polytechnic University of Timisoara, Romania. His academic career includes a previous role as Assistant Professor at Florida International University (2012–2016). His research focuses on Data Visualisation, Visual Analytics, and Human-Computer Interaction . He conducts interdisciplinary collaborations with domains such as biology, food policy, and energy decarbonisation, aiming to develop interactive visual tools that enhance data understanding and decision-making. His methodological approach includes user studies, eye-tracking, and the design of novel visualization techniques. Dr. Jianu teaches Programming in Java and Cognition and Technologies , and he coordinates the Programming Bootcamp. He also holds administrative responsibilities as the Progression and Support Director in the Computer Science Department and is a member of its Executive Committee (ExCo). His recent publications reflect a growing interest in LLM-assisted visual analytics, gaze-aware systems, and collaborative human-AI analytical frameworks . He has published in top venues such as IEEE TVCG, CHI, EuroVis, and Nature Immunology, with several best paper awards. His work on the RAMPVIS project highlights his contributions to visualization in public health emergencies. Scientific Awards: Best Paper Award, Symposium on Graph Drawing (2018) Best Short Paper Award, EuroVis (2020) Advising and Grants: Dr. Jianu supervises multiple PhD and MSc students, including Dany Laksono (Energy Decarbonisation) and Maeve Hutchinson (NLP-mediated Visualization). His students have co-authored high-impact, award-winning papers. He has been involved in funded research initiatives such as RAMPVIS, which received support from UKRI/EPSRC for developing visual analytics infrastructure during the COVID-19 pandemic. Labs and Teams: He is an active member of the giCentre at City, University of London, a hub for visualization research. He also collaborates with interdisciplinary teams in epidemiology, immunology, and computer science, contributing to large-scale projects like the Immunological Genome Project and RAMPVIS.
Mark Batty is a Professor in the School of Computing at the University of Kent, specializing in formal methods for concurrent systems. His work bridges hardware-software interfaces, focusing on memory models for C/C++, OpenCL, and architectures including x86, ARM, POWER, and GPUs. As a member of the Programming Languages and Systems Research Group, he develops mathematical specifications and verification tools for real-world concurrency challenges. His research centers on empirical testing of hardware/compiler behavior, formal modeling of system components, and verification of fine-grained concurrent algorithms. Key contributions address relaxed memory semantics, transactional memory, and compositional reasoning for concurrent data structures. His work combines theoretical rigor with practical tool development to ensure correctness in complex concurrent environments. Analysis of his 2015-2025 publications reveals consistent focus on memory consistency models, formal verification of weak memory concurrency, and compiler optimizations. Dominant themes include C/C++11 standards, GPU concurrency semantics, and mechanized verification techniques. His research demonstrates strong industry relevance through collaborations with hardware vendors and contributions to language standards. Mark Batty has received significant recognition: John C. Reynolds Doctoral Dissertation Award (2015) from ACM SIGPLAN CPHC and BCS Distinguished Dissertation Award (2015) Lloyds Register Foundation and Royal Academy of Engineering Research Fellowship (2016) He actively leads major research initiatives and mentors next-generation researchers: Current Funding: EPSRC Standard Grant 'Verifiably Correct transactional memory' (2018), VeTTS Grant 'Specification and verification of C++ data structure libraries' (2018), EPSRC First Grant 'Compositional, dependency-aware C++ concurrency' (2018) PhD Recruitment: Actively seeking candidates for UKRI-funded studentship in Verified Trustworthy Software Systems Batty drives community engagement through Kent Concurrency Workshop (2016) and South of England Programming Language Seminars, fostering national collaboration in programming languages research. His leadership in organizing Royal Society discussions underscores his influence in trustworthy systems verification.
