Professor Ferrante Neri is a faculty member at the University of Surrey, holding the positions of Professor of Machine Learning and Artificial Intelligence and Associate Dean (International) for the Faculty of Engineering and Physical Sciences (FEPS). He is affiliated with the Nature Inspired Computing and Engineering Research Group, Surrey Institute for People-Centred AI (PAI), and the Computer Science Research Centre within the School of Computer Science and Electronic Engineering. His research focuses on optimization, explainable AI, and machine learning, with contributions to memetic computing and differential evolution. Since 2010, he has chaired the IEEE Task Force on Memetic Computing. He advises PhD students in topics like dynamic multi-objective optimization and AI-driven applications. His teaching expertise includes mathematical foundations for computer science. He has supervised students such as Aisha E S E Saeid and Pengjin Wu. Notable research areas include evolutionary algorithms, neural architecture search, and applications in robotics and environmental monitoring. Labs and teams include the Nature Inspired Computing group, which explores AI-driven solutions for complex problems. His work bridges theoretical advancements and practical applications in fields like autonomous systems and deep learning.
Lee Nissim is a Lecturer in the Department of Mechanical Engineering at the University of Bath, affiliated with the Centre for Bioengineering & Biomedical Technologies (CBio). He holds a PhD in Aeronautical Engineering from Imperial College London (2021), an MRes in Fluid Dynamics (2016), and a Master of Engineering from the University of Cambridge (2015). His research focuses on biomedical engineering, particularly in hemocompatibility, computational fluid dynamics (CFD), and magnetic levitation systems for medical devices like ventricular assist devices (NeoVAD). He also explores tribology in prosthetic joints and pediatric cardiovascular support systems. Key projects include the KTP collaboration with Modini Limited, advancing NeoVAD design through CFD and machine learning. His work integrates CFD simulations, experimental validation, and machine learning to optimize biomedical device performance. Recent articles highlight innovations in blood-contacting bearing design, energy-efficient rotary pumps, and pediatric LVAD prototypes. His contributions span over 15 peer-reviewed publications, emphasizing design optimization, hemodynamic analysis, and wear-resistant prosthetics. Nissim is actively supervising doctoral students and advancing interdisciplinary solutions in bioengineering and mechanical systems.
Antonio Pellegrino is a Lecturer in the Department of Mechanical Engineering at the University of Bath. His research focuses on high strain rate mechanics of materials, including lightweight polymers, titanium alloys, and biological materials. He develops novel experimental apparatus like the combined tension-torsion Hopkinson Bar. Key areas include AI in materials modelling, failure stress loci of syntactic foams, and dynamic fracture analysis. He holds a PhD in Mechanical Engineering from the University of Catania (2012). Recent projects include an EPSRC-funded study on syntactic foams using in-situ microscale tomography and X-ray scattering. Collaborations span institutions globally, with emphasis on advanced materials testing and data-driven modelling. Awards include election to the Governing Board of DYMAT (2024). He supervises doctoral students and serves as a peer reviewer for journals like International Journal of Mechanical Sciences and Engineering Fracture Mechanics . Research highlights include: development of a tension-torsion Hopkinson Bar; studies on strain rate-dependent behavior of composites and metals; biomechanical investigations of eye lens mechanics. His work contributes to UN SDGs through sustainable materials research and education initiatives. Education: PhD Mechanical Engineering (University of Catania, 2012) Key Skills: High-strain rate testing, data-driven modelling, experimental apparatus design Recent Activities: 16 peer review and committee roles (2023-2025)
James Roscow is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, affiliated with the Centre for Integrated Materials, Processes & Structures (IMPS), IAAPS, and the Institute of Sustainability and Climate Change. His research focuses on developing ferroelectric composites for energy harvesting, sensing, and energy storage, with expertise in material fabrication, property tuning, and numerical modeling. He holds a PhD in Mechanical Engineering from the University of Bath and a BSc in Materials Science from the University of Manchester. Research interests include porous ferroelectric ceramics, piezoelectric and pyroelectric materials, and their applications in renewable energy and sensors. He has led or contributed to 12 projects funded by organizations like EPSRC and Innovate UK, exploring topics such as low-cost transducers, nanofluid cooling for solar panels, and phase transformations in ceramics. Key publications (2021–2025) address piezoelectric energy harvesting, porous material design, and advanced manufacturing techniques. His work aligns with UN SDGs, particularly sustainable energy and innovation. Roscow supervises PhD students in functional ceramics, energy storage, and sensor technologies. Notable collaborations include projects on hydraulic energy harvesters, SONAR transducers, and self-healing materials. He has contributed datasets on piezoelectric composites and energy storage systems, emphasizing reproducibility and applied research.
Dr. Yunxiao Chen is an Associate Professor in the Department of Statistics at the London School of Economics and Political Science (LSE), where he co-leads a psychometric lab with Professor Irini Moustaki. Previously, he was an Assistant Professor at Emory University (2016–2018) and earned his PhD in Statistics from Columbia University (2016). His research focuses on developing statistical and computational methods for social data science, addressing challenges in high-dimensional data analysis, latent variable models, and educational assessment. Education: PhD in Statistics, Columbia University, 2016 Research Interests: High-dimensional factor models (matrices, tensors, counting processes) Dynamic behavioral data analysis Sequential decision theory in personalized learning Statistical inference for large-scale item response data Applications in education, psychology, and marketing Publications: Recent work includes advancements in factor analysis, change-point detection, and DIF statistical inference Key journals: Journal of the American Statistical Association , Psychometrika , Journal of Machine Learning Research Awards: 2024 Psychometrics Society Best Reviewer Award 2022 Early Career Award 2018 NCME Loyd Dissertation Award Advising & Grants: Accepts PhD students in statistical methodology Funded by National Academy of Education/Spencer Fellowship (2018–2020) and IEA R&D grants (2022–2023) Labs & Teams: Runs LSE’s psychometric lab focused on educational measurement Collaborates with interdisciplinary teams on machine learning applications
Dr. Tania Mendo is a Lecturer at the University of St Andrews, School of Geography and Sustainable Development. She specializes in interdisciplinary approaches to small-scale coastal fisheries management, focusing on policy-informed research, socio-economic indicators, and marine spatial planning. Her work emphasizes equitable representation of fishers in the blue economy and employs statistical methods paired with user-friendly data visualization tools for stakeholder engagement. Current research interests include machine learning applications for decision-making, blue justice frameworks, climate change adaptation in hyper-arid regions, and El Niño impacts on food systems. Dr. Mendo leads projects such as the Digital Transition of Catch Monitoring in European Fisheries and Conserving Atlantic Biodiversity through Co-management. She collaborates internationally with organizations like Cefas and engages with communities in Peru and Scotland. Her research integrates quantitative methods with participatory approaches to address fisheries governance challenges and environmental sustainability. Grants include funding from UKRI, BBSRC, and EPSRC for initiatives like improving stock assessment technologies and assessing fishing communities' resilience during crises. Her publications highlight innovations in vessel tracking analysis, spatial distribution modeling, and socio-economic frameworks for fisheries. She advises PhD students Miguel Delos Santos and Tamsin Rigold. Mendo is affiliated with the Bell-Edwards Geographic Data Institute and contributes to UN SDGs related to life below water and sustainable communities.
Professor Daniele Condorelli is a faculty member in the Department of Economics at the University of Warwick. His research focuses on Microeconomic Theory, Networks and Platforms, and Mechanism Design. He holds a Professor title and is affiliated with the Department of Economics. His work explores topics such as consumer hold-up in ecosystems, data-driven envelopment, and surplus bounds in Cournot competition. His research interests span strategic models of intermediation networks, auction design, and information economics. Notable publications include studies on vertical mergers in digital ecosystems, privacy-policy impacts on data monetization, and optimal mechanism design for market efficiency. Recent articles highlight his contributions to understanding platform competition, resale networks, and algorithmic game theory. His work often intersects with antitrust policy, digital market governance, and incentive design in networked environments. Professor Condorelli advises students in economics and is involved in academic administration, offering office hours by appointment.
Dr. Jonathan E. Booth is an Associate Professor in the Department of Management at the London School of Economics and Political Science (LSE). He specializes in Organisational Behaviour and Human Resource Management, focusing on workplace stigma, prosocial behavior, leadership, and LGBTQI+ inclusion. He teaches courses such as The Dark Side of the Organisation to MSc, PhD, and executive education students. His research explores topics like employee volunteering, client-instigated victimization, and the impact of technology on work. Dr. Booth holds a PhD in Human Resources and Industrial Relations from the University of Minnesota (Carlson School of Management) and a B.S. in Business Administration from Georgetown University. He has been recognized with awards including the John T. Dunlop Outstanding Scholar Award (2020) and multiple LSE Excellence in Education Awards. He serves as an Associate Editor for the British Journal of Industrial Relations and has held leadership roles in academic programs at LSE. His research interests span technology and the future of work, prosocial behavior (e.g., corporate volunteering), workplace mistreatment, and union dynamics. He has published extensively in journals like the Academy of Management Journal and Journal of Applied Psychology. His work often addresses global challenges, such as LGBTQI+ inclusion and pandemic-related workplace adaptations. Dr. Booth has supervised several PhD students, including Ceren Erdem, Ephrat Livne, Rashpal Dhensa-Kahlon, and Fan Gu. He actively participates in academic service roles, including editorial boards and conference organization. His teaching portfolio includes courses on negotiation, human resource management strategies, and organizational behavior.
Professor Stephen Hicks is a Professor in Civil Engineering and Leader of the Civil and Environmental Engineering Discipline Stream at the School of Engineering, University of Warwick. He has held senior roles in research institutes like the Heavy Engineering Research Association (HERA) and the Steel Construction Institute (SCI), contributing to national and international standards development. Education: PhD (University of Cambridge, 1998), BEng (University of London, 1993) Research focuses on composite steel-concrete structures, structural reliability, and vibration serviceability. He leads teaching modules including ES3E1 Design Project and ES2C2 Civil Engineering Design. Key projects include Eurocode 4 revisions and steel-concrete composite systems development. Grants include leadership on Steel-CLT composite design (WSP UK) and EU-funded Eurocode 4 standardization projects. He chairs CEN Subcommittee SC4 for Eurocode 4 and contributed to Australasian standards like AS/NZS 2327. Engaged in governance roles with organizations such as EPD Australasia and Steel Construction New Zealand.
Andrei Kirilenko is Professor of Finance and Founding Director of the Cambridge Centre for Finance, Technology and Regulation (CCFTR) at the University of Cambridge's Judge Business School. His roles include leading research at CCFTR and contributing to the school's focus on institutional financial decision-making. He holds a PhD from the University of Pennsylvania. Previous roles: Chief Economist of US CFTC (2010-2012), 12-year tenure at IMF addressing global financial crises Adjunct appointments: None explicitly stated Research focuses on the intersection of finance, technology, and regulation with emphasis on fintech innovations, digital market design, and regulatory frameworks for automated systems. Current projects include rebuilding Ukraine's financial sector through executive education programs and developing crypto asset recommendation systems. Media engagements highlight his commentary on Ukraine's economic situation and fintech advancements. No specific grants or awards listed in the text. Labs/teams: Leads the CCFTR initiative integrating finance, tech, and regulatory strategies.
Nitisha Jain is a Postdoctoral Researcher at King's College London's Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences. She holds a PhD in Knowledge Graphs from the Hasso Plattner Institute (University of Potsdam) and a Master's in Research from the Indian Institute of Science (IISc). Her research focuses on neuro-symbolic AI, ethical AI standards, multimodal knowledge graphs, and knowledge engineering using large language models. Her work includes contributions to the Croissant metadata standard for machine-readable datasets and the development of interpretable embeddings aligned with semantic aspects. She has published extensively in venues like NeurIPS, ACL, and ISWC, and serves on program committees for conferences such as ESWC and DEEM. Key achievements include a spotlight paper at NeurIPS 2024 and a best paper award at DEEM 2024. She supervises students in areas like knowledge graph embeddings and neuro-symbolic methods, and has taught courses on network data analysis and knowledge engineering at both bachelor’s and master’s levels.
Dr. Wenjuan Song is a Lecturer in Electrically Powered Aircraft, Propulsion, Electrification & Superconductivity Group at the James Watt School of Engineering, University of Glasgow. She holds a PhD in Electrical Engineering from Beijing Jiaotong University (2019) and has held postdoctoral positions at Victoria University of Wellington (2016–2018) and the University of Bath (2019–2021). Her research focuses on accelerating net-zero transitions in transport sectors through superconductivity and AI-driven solutions. Research Interests: Net-zero aviation, renewable energy systems, superconducting fault current limiters, cryogenic systems, and AI applications in electrification. Awards: Global Talent (UK Royal Academy of Engineering, 2021), featured in IEEE PES Women in Power, and COST Action publications. Teaching: Course coordinator for Simulation of Engineering Systems, Simulation of Aerospace Systems, and Power Engineering 3. Professional Activities: Organizing Committee member (UK Fluids Conference 2023), guest editor (Superconductor Science and Technology), and session chair at international conferences. Her work integrates superconductivity and AI to address challenges in electric aircraft, high-speed rail, and marine electrification. Key contributions include fault detection systems for HTS components and predictive modeling of superconducting materials.
Christian Egwim is a Researcher in the Department of Computer Science at the University of Bath. With a PhD in Applied Artificial Intelligence from the University of Hertfordshire and a BSc in Computer Science from the University of Ibadan, he specializes in Artificial Intelligence, Big Data Analytics, Machine Learning, Software Engineering, Digital Technology Innovation, Environmental Monitoring, and Circular Economy. Education: PhD in Applied Artificial Intelligence, University of Hertfordshire BSc in Computer Science, University of Ibadan His research focuses on applying AI and IoT technologies to address environmental challenges, including air quality monitoring, pollution prediction, and sustainable building design. Current projects include the D-BuD initiative, which uses big data and machine learning to optimize pollution dispersion in architectural designs. His scholarly work spans topics like feature selection, ensemble modeling, and agentic AI. Collaborations include partnerships with institutions in the UK and Nigeria, contributing to advancements in environmental and construction-related AI applications.
Mohammad Kamrul Hasan is an Associate Professor and Head of the Network and Communication Technology Research Lab at the Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM). He holds a Ph.D. in Electrical and Communication Engineering from the International Islamic University Malaysia (IIUM) and has over a decade of prior industry experience in communication systems and network design. He has held academic positions at Universiti Malaysia Sarawak and IIUM, and is currently active in research and leadership at UKM. Ph.D. in Engineering (Electrical and Computer Engineering), International Islamic University Malaysia, 2016 M.Sc. in Communication Engineering, International Islamic University Malaysia, 2012 His research focuses on cutting-edge areas in network and communication technologies. Key interests include Wireless Communication and Network Security , Industrial Internet of Things (IIoT) , Cyber-Physical Systems , 5G and Beyond (6G) Networks , Smart Grids , and AI-driven security . He explores machine learning, federated learning, blockchain, and optimization algorithms to enhance network resilience, privacy, and efficiency in critical infrastructure and consumer electronics. His recent publications (2023–2025) demonstrate a strong trend toward intelligent and secure next-generation networks. Topics include intrusion detection in IIoT, passwordless authentication, federated learning for healthcare IoT, 6G security, and digital twins for SCADA systems. His work is frequently published in high-impact IEEE and Springer journals, reflecting a consistent and influential research output. Gold Medal for research excellence Young Scientist Award Fulbright Scholarship (Ministry of Higher Education Malaysia) Senior Member, IEEE (since 2013) Member, Institution of Engineering and Technology (IET) Member, Internet Society Dr. Hasan has served as an editorial member for prestigious journals including IEEE, IET, and Elsevier. He has led funded research projects such as the design of a two-way wireless communication system for medium-voltage electrical networks at Universiti Malaysia Sarawak. He has mentored students and collaborated widely, with co-authors from Malaysia and international institutions. He has also contributed to professional service as Chairperson of the IEEE IIUM Student Branch and as a peer reviewer for over 13 journals including Computer Networks , Internet of Things , and Soft Computing . He leads the Network and Communication Technology Research Lab at UKM, focusing on secure, intelligent, and scalable communication systems for smart cities, industry, and healthcare. His team works on AI-powered intrusion detection, blockchain for critical infrastructure, and privacy-preserving data fusion in IoT environments.
Dr. Ehsan Mohseni is a Senior Lecturer in the Department of Electronics and Electrical Engineering at the University of Strathclyde, Faculty of Engineering. He is a key member of the Centre of Ultrasound Engineering (CUE) research group and supports the Royal Academy of Engineering and Spirit AeroSystems research chair led by Professor Gareth Pierce. His work focuses on advancing robotic and intelligent Non-Destructive Evaluation (NDE) systems for industrial applications. B.Sc. in Materials Science and Metallurgical Engineering, University of Tehran, 2006 M.Sc. in Metal Forming Processes, University of Tehran Ph.D. in Automated Defect Detection using Electromagnetic NDE, École de Technologie Supérieure (ETS), Montreal, Canada Dr. Mohseni’s research is centered on NDE 4.0, integrating advanced sensing, multi-physics modeling, and machine learning. His expertise spans ultrasonic and eddy current testing, multi-sensor data fusion, and probability of detection studies. He focuses on applications in additive manufacturing, welding, composites, and metal processing, aiming to overcome current technological barriers in industrial inspection. The recent publications highlight a strong trend toward intelligent, automated, and robotic NDE systems. Key themes include self-supervised learning for ultrasonic segmentation, human-machine collaboration in data analysis, and advanced signal processing for weld and composite inspection. The integration of AI, flexible sensor arrays, and embedded navigation systems reflects a shift toward smart, adaptive inspection platforms aligned with Industry 4.0. Scientific Awards: The BINDT Annual Conference Award (2019) Dr. Mohseni is actively involved in research funding and knowledge transfer. He serves as Principal Investigator on KTP projects with ETHER NDE LIMITED and NATIONAL OILWELL VARCO UK LIMITED, focusing on in-process inspection for additive manufacturing and field calibration for ultrasonic testing. He contributes to large-scale collaborative projects funded by Innovate UK and industry partners, emphasizing practical deployment of NDE solutions. He also supervises research staff and collaborates with global aerospace firms including Pratt & Whitney Canada, Safran, and Bell Helicopter. He is a core member of the Centre of Ultrasound Engineering (CUE), a dynamic research group developing next-generation ultrasound technologies. The team works on advanced robotic sensing hubs, flexible transducer arrays, and AI-driven data interpretation tools, often in collaboration with the Royal Academy of Engineering research chair and industrial partners.
