Professor Piotr Krysta is a faculty member in the Department of Computer Science, affiliated with the research groups on Algorithms, Complexity Theory and Optimisation, and Economics and Computation. His work spans theoretical and applied domains in algorithmic design and economic systems. University of Liverpool (implied by context, though not explicitly stated) His research interests include: Approximation Algorithms Combinatorial Optimization Algorithmic Game Theory Computational Complexity Optimization in Network and Economic Systems His recent publications focus on blockchain mechanisms, combinatorial constraints in delegation, and optimization techniques in graph theory. Funded by UK and German research councils, his work bridges computational hardness with economic applications. Scientific awards include: Best paper award for Track C of 39th ICALP (2012) Emmy Noether Fellow (DFG, 2004–2008) He has served on program committees for major conferences, collaborated internationally, and contributed to journals like Electronic Commerce Research and Applications . His teaching involves supervising theses on algorithmic challenges and mechanism design.
Xin Fei is a Lecturer in Business Analytics at the University of Edinburgh Business School since 2022. Previously, she held the same role at the University of Bristol and was a fellow at the Bristol Digital Futures Institute . Her academic foundation includes a PhD in Operations Research & Management Science from Warwick Business School , supervised by Professor Juergen Branke and Professor Nalan Gulpinar. Current affiliation: University of Edinburgh Business School Prior affiliations: University of Bristol, Bristol Digital Futures Institute Education: PhD in Operations Research & Management Science (Warwick Business School) Xin Fei's research bridges business analytics , optimization , and decision science , focusing on stochastic programming , simulation optimization , and reinforcement learning . Her work develops computationally efficient methods for complex decision problems under uncertainty, emphasizing scenario generation and information collection procedures . Her recent publications in European Journal of Operational Research (ABS 4), IEEE Transactions on Evolutionary Computation (ABS 4), and INFORMS Transportation Science (ABS 3) highlight applications in transportation systems , industrial engineering , and pharmaceutical portfolio planning . Collaborative research includes air traffic management innovations recognized by the Jane's Innovation Award (2019). Teaching highlights include UG: Business Analytics and Information Systems (BUST08032) (2021-present), PG: Principles of Data Analytics (CMSE11432) (2022), and advanced PG courses in Applied Decision Optimisation (2023-present) and Online Learning and Decision Making (2023-present). Administrative roles include PGR Representative for the Management Science and Business Economics Group (2022-2025). Professional Affiliations: Fellowship of the Higher Education Academy The Operational Research Society The Institute for Operations Research and the Management Sciences (INFORMS)
Professor David Andrews is Professor of Engineering Design in the Department of Mechanical Engineering at University College London (UCL). A globally recognised authority on naval architecture and ship design methodology, he has held continuous academic appointments at UCL since 1980, punctuated by distinguished service in the UK Ministry of Defence where he rose to Director of Frigates and Mine Countermeasures. Since 2000 he has occupied the Chair in Engineering Design at UCL, leading major research initiatives funded by EPSRC, ONR and the EU, and forging strategic industrial partnerships. Education Bachelor of Engineering, UCL (1970) MSc Naval Architecture, UCL (1971) PhD “Synthesis in Ship Design”, UCL (1984) Research Focus Professor Andrews is acknowledged as the world-leading expert in naval ship design methodology, with seminal contributions to early-stage design processes, submarine architecture, trimaran/multi-hull vessels, and distributed ship service systems. His pioneering Design Building Block approach and SURFCON CAD tool have been integrated into industry-standard platforms such as PARAMARINE. Current work addresses energy balance frameworks, computer-aided sketching, and philosophical foundations of engineering design. Across more than 150 publications, a clear trajectory emerges: from fundamental design theory through tool development to practical application in warship, submarine and advanced multi-hull projects. Recent outputs (2021-2024) emphasise automation of early-stage synthesis, network-based modelling of complex distributed systems, and integration of operational availability considerations into concept design. Honours & Awards Fellow of the Royal Academy of Engineering (2000) Fellow of the Royal Institution of Naval Architects (RINA) Fellow of the Society of Naval Architects and Marine Engineers (SNAME) William Froude Medal, RINA (2020) – highest award David W Taylor Medal, SNAME (2021) – lifetime contribution Advising & Grant Leadership Since flexible retirement in 2012 he continues to lecture and supervise MSc projects in Naval Architecture, Marine Engineering and Submarine Design CPD courses. He has led or co-led research grants exceeding £2 million from EPSRC, EU and industry (BAE Systems, Rolls-Royce, BMT, Dstl). These projects have funded numerous CASE studentships and collaborative PhD programmes that bridge UCL and industrial stakeholders. Research Team & Industrial Links Professor Andrews heads the Design Research group at UCL, mentoring successive MoD Professors of Naval Architecture and maintaining active Memoranda of Understanding with BAE Systems and other maritime primes. He chairs the tri-annual International Marine Design Conference’s Design Methodology Panel and has delivered keynote addresses worldwide, uniquely representing non-US expertise at successive US Navy Ship Design Process Workshops.
Dr. Viknesh Andiappan serves as Associate Professor in Chemical Engineering and Associate Director of the School of Research at Swinburne University of Technology, Sarawak Campus, within the Faculty of Engineering, Computing and Science. His academic foundation includes a PhD and MEng (Hons.) in Chemical Engineering from The University of Nottingham. PhD in Engineering (The University of Nottingham) MEng (Hons.) in Chemical Engineering (The University of Nottingham) His research pioneers net-zero energy systems through mathematical optimization, focusing on supply chain decarbonization, industrial symbiosis, and sustainable agriculture planning. Recent work integrates carbon accounting with palm oil value chains and biomass-to-energy systems, emphasizing practical implementation in Southeast Asian contexts. Analysis of his 15 most recent publications (2020-2022) reveals a dominant focus on decarbonization strategies (47%), biomass supply chains (27%), and process optimization (26%), with growing emphasis on circular economy applications and multi-stakeholder resource allocation frameworks. Key recognitions include: IBAE Young Researcher of the Year Award IChemE Young Researcher Malaysia Award Finalist (2018, 2019) Heriot-Watt University PRIME Award Finalist (2021) He actively supervises research students in net-zero energy systems while leading industry-relevant projects like the Ministry of Plantation Industries white paper on palm oil recovery strategies. His scholarly service includes editorial roles for Process Integration and Optimization for Sustainability and Frontiers in Sustainability. Though no dedicated lab is specified, his research group operates through Swinburne's School of Research, leveraging institutional facilities for computational optimization and sustainability analysis.
Corinne LUCET-VASSEUR is a University Professor at Université de Picardie Jules Verne (UPJV), leading Research Unit UR 4290 (OCIA - Optimisation Combinatoire, Images et Applications). Her office (Room 302, Tel: 5900) serves as the hub for her research group focused on combinatorial optimization and artificial intelligence applications. Her research spans: Combinatorial Optimization : Developing metaheuristics for NP-hard problems Healthcare Logistics : Patient flow optimization, facility location, simulation training Logistics Engineering : Parcel distribution, vehicle routing with time windows Algorithm Design : Ant Colony Optimization, Adaptive Large Neighborhood Search, portfolio methods She applies these methodologies to solve complex real-world problems, particularly in healthcare systems where resource constraints and scheduling complexity demand innovative optimization approaches. Her work bridges theoretical advances with practical implementation through industrial partnerships. Current research projects include: SMILE PICK UP (CIFRE industrial partnership) Simusanté (healthcare simulation) LORH (logistics optimization) These projects secure ongoing funding and provide doctoral training opportunities through industry collaboration. Her publication record demonstrates consistent methodological innovation applied to healthcare and logistics challenges across multiple European conferences and journals. Professor Lucet-Vasseur actively mentors junior researchers through co-authorship on conference papers and journal articles. Her supervision style emphasizes practical problem-solving with industry relevance, preparing students for both academic and industrial careers in optimization. The OCIA research unit provides a collaborative environment for tackling complex combinatorial problems with real-world impact. The OCIA laboratory serves as UPJV's center for combinatorial optimization research, specializing in metaheuristic development for healthcare and logistics applications. The lab maintains strong industry connections through CIFRE contracts and applied projects, ensuring research relevance while providing students with exposure to real business challenges. Current focus areas include adaptive algorithm selection using reinforcement learning and fitness landscape analysis for optimization problems.
Professor John McCall is a distinguished academic and researcher at Robert Gordon University's School of Computing, Engineering & Technology, where he previously served as Head of School. He currently serves as Director of the National Subsea Centre, leading initiatives to accelerate energy transition through smart technologies applied to industrial and environmental challenges in subsea and related marine sectors. With over 25 years of research experience in nature-inspired computing and artificial intelligence, Professor McCall has established himself as a leading expert in optimization algorithms and explainable AI. Professor McCall's research interests span data science, artificial intelligence, nature-inspired computing, and optimization, with significant applications in energy transition and subsea technologies. His work bridges theoretical foundations with practical implementations, having founded two spinout companies that deliver real-world optimization solutions to industry. He leads both the Complex Optimisation Research Group and the Computational Intelligence Research Group, where his team explores cutting-edge approaches to solving complex computational problems. Analysis of Professor McCall's recent publication record (2023-2025) reveals a strong focus on explainable AI, particularly in the context of evolutionary computation and metaheuristics. His research demonstrates an increasing emphasis on practical applications in energy systems, transportation, and subsea technologies, reflecting his commitment to addressing real-world challenges related to climate change and industrial transformation. The interdisciplinary nature of his work is evident in publications spanning computer science, operations research, renewable energy, and transportation planning. Lead of the Computational Intelligence Research Group ResearcherID: G-1423-2011 Scopus Author ID: 36797474900 ORCID: https://orcid.org/0000-0003-1738-7056 Professor McCall is actively involved in mentoring the next generation of researchers, currently supervising multiple PhD students across diverse topics including explainability of non-deterministic solvers, optimization of electrical machines, and computational intelligence applications in hydrocarbon systems. His research is supported by numerous grants from industry and government sources, with projects totaling millions of pounds focused on solving challenges in energy transition and smart technologies. At the National Subsea Centre, Professor McCall leads a multidisciplinary team working on digital twin technologies, subsea AI applications, and data-driven solutions for the energy sector. His work emphasizes collaboration between academia and industry to develop transformative solutions that address both current challenges and future opportunities in the subsea domain.
Dr. Joan Alza Santos is an early-career Research Fellow at the School of Computing, Engineering, and Technology within Robert Gordon University (RGU). She is affiliated with the Complex Optimisation Research Group and contributes to RGU's research themes in "Environment, Energy & Sustainability" and "Living in a Digital World." Her work bridges academic research in dynamic optimization with practical applications in sustainable logistics and other real-world domains. Dr. Alza Santos completed her educational journey with: BSc (Hons) in Computer Engineering from Universidad del País Vasco (University of the Basque Country), 2013-2017 Postgraduate Certificate from Robert Gordon University, 2018-2021 PhD in Computing from Robert Gordon University, completed in January 2025 with no corrections required - a rare distinction Her research focuses on addressing fundamental challenges in dynamic optimization. Dr. Alza Santos has made significant contributions to the field through three key innovations: developing a fitness landscape rotation framework for dynamic benchmarking, introducing the concept of "elusivity" to quantify algorithmic adaptability over complete restart, and creating methods for generating realistic synthetic instances from real-world logistic data. Her work aims to bridge the gap between academic research and practical applications, particularly in sustainable logistics where optimization under uncertainty is critical. Dr. Alza Santos's publication record shows a consistent focus on dynamic optimization problems, particularly in combinatorial spaces. Her research trajectory demonstrates progression from theoretical foundations of dynamic permutation problems to increasingly practical applications, culminating in methods for generating realistic benchmarks from real-world data. A notable trend in her work is the development of metrics like "elusivity" that provide quantitative ways to evaluate the true adaptive challenge in dynamic optimization problems, moving beyond simplistic representations of dynamism. Her scientific recognition includes: Membership in the International Graduate Student Research Cohort (2024) Presentation at the Arctic Circle Assembly (2024) PhD defense with no corrections required (2025) - noted as a rare distinction As an early-career researcher, Dr. Alza Santos actively supervises research projects and serves as a Demonstrator for "Applied Data Science" and "Data Visualisation" modules. Her industrial collaborations span multiple sectors including energy, transportation, and environmental sustainability. She has worked on projects evaluating offshore wind farm impacts, developing visualization tools for fleet management, simulating transportation demand, optimizing cargo transportation, creating VR flooding simulations, reviewing childhood obesity data, and developing predictive maintenance platforms for the oil and gas industry. Dr. Alza Santos leads research within the Complex Optimisation Research Group at RGU, where she continues to develop innovative approaches to dynamic optimization problems. Her current work focuses on applying simulation-optimization techniques to address real-world challenges, particularly in sustainable logistics. She is actively seeking new collaboration opportunities with both academic researchers and industry partners to expand the impact of her work on society and the economy.
Dr. Lee Christie is a Research Fellow at Robert Gordon University's School of Computing, Engineering & Technology, where he conducts research in optimization and artificial intelligence. He is affiliated with the Complex Optimisation Research Group and maintains connections with the National Subsea Centre through his research on net-zero operations. His educational background includes: BSc (Hons) in Computer Science from Robert Gordon University (2003-2007) MSc in Information Engineering (Distinction) from Robert Gordon University (2009-2011, part-time) PhD in Computational Intelligence from Robert Gordon University (2011-2016) Dr. Christie's research primarily focuses on combinatorial optimization, structure learning, and blockchain technologies. He investigates how to make non-deterministic solvers more transparent through trajectory mining and feature extraction. His work bridges theoretical optimization techniques with practical applications in transportation systems (particularly connected autonomous vehicles), renewable energy (wind farm optimization), and supply chain management. He has published extensively on explainable metaheuristics, with a growing emphasis on making optimization algorithms interpretable for end-users while maintaining effectiveness. His recent publications (2021-2025) demonstrate a clear research trajectory toward explainable AI for optimization algorithms, with applications spanning transportation systems, renewable energy infrastructure, and complex supply chains. These works showcase his ability to translate theoretical advances into practical solutions for real-world problems with societal impact. Dr. Christie has secured research funding for projects including the A.R.T. Forum NSR (2019-2022), which developed implementation roadmaps for automated road transport in the North Sea Region. He teaches programming for business analytics courses and actively contributes to the Aberdeen Python User Group as a steering committee member. His academic service includes supervision of PhD students, with Dr. Martin Fyvie recently completing a dissertation on 'Explainability of Non-Deterministic Solvers' under his guidance as second supervisor. Dr. Christie maintains active collaborations with researchers including John McCall, A.-C. Zăvoianu, and A.E.I. Brownlee, resulting in consistent publication output across reputable venues in evolutionary computation and artificial intelligence.
Dr. Atakan Sahin is a researcher at Robert Gordon University's School of Computing, Engineering & Technology, affiliated with the Complex Optimisation Research Group. His work focuses on computational approaches to energy system optimization and industrial process control. His educational background includes a PhD in Pure and Applied Chemistry from University of Strathclyde (2016-2020), an MSc in Control and Automation Engineering from Istanbul Teknik Üniversitesi (2014-2016), and a Bachelor's degree in the same field from the same institution (2009-2014). His doctoral research addressed monitoring complex nonstationary industrial processes. Dr. Sahin's research spans Computational Intelligence, Control Theory, and Fuzzy Logic applications with emphasis on Statistical Process Control and Machine Learning. His current work through the D4NZ project optimizes energy grids for renewable integration, focusing on multi-objective criteria including cost and robustness in offshore wind farm infrastructure. His recent publication output demonstrates active contribution to optimization research, particularly in renewable energy systems where computational methods solve complex engineering challenges. The 2024 conference paper on wind farm cable layouts represents practical application of his optimization expertise. Dr. Sahin maintains active research funding through the Scottish Government's Energy Transition Fund and collaborates internationally, as evidenced by recent conference participation in Austria. His work bridges theoretical computational methods with practical energy infrastructure challenges, supporting the UK's net-zero emissions targets through advanced optimization techniques.
Dr. Ciprian Zavoianu is an academic researcher at Robert Gordon University (RGU) in the School of Computing, Engineering & Technology. He leads the Net Zero Operations research programme at the National Subsea Centre and is affiliated with the Complex Optimisation Research Group. His work focuses on applying artificial intelligence, particularly evolutionary computation algorithms, to solve complex real-world optimization problems with practical engineering applications. Dr. Zavoianu earned his academic qualifications from West University of Timisoara, Romania (BSc and MSc in Computer Science) and Johannes Kepler University Linz, Austria (PhD in Computer Science, 2015). His doctoral research focused on enhancing multi-objective evolutionary algorithms for computationally-intensive optimization problems. His primary research interests include: Evolutionary Computation Multi-Objective Optimization Data Mining & Machine Learning (particularly for surrogate modeling) Timetabling and Rostering Parallel/Distributed Computing Dr. Zavoianu's recent publications (2021-2025) demonstrate a strong focus on applying optimization techniques to transportation systems, electrical machine design, and sustainable energy solutions. His work consistently addresses the challenge of computationally expensive optimization through innovative surrogate modeling approaches, enabling practical applications of evolutionary algorithms to real-world engineering problems. He has secured multiple research grants including 'Data For Net Zero' and 'Ferry Passenger and Freight Modelling for Shetland,' demonstrating the practical relevance and industry applicability of his research. Dr. Zavoianu actively supervises five PhD/EngD students across diverse topics including predictive analytics for subsea installations, optimization of electrical machines, and operations optimization for harbor operations. His supervision approach emphasizes bridging theoretical algorithm development with practical implementation in engineering contexts. His laboratory work is centered around the National Subsea Centre, where he leads the Net Zero Operations research programme, focusing on sustainable solutions for the energy transition through advanced computational methods.
Prof. Izabela Lubowiecka serves as a Professor at the Department of Structural Mechanics within the Faculty of Civil and Environmental Engineering at Gdańsk University of Technology. Her office is located in the Main Building (room 467A) with contact details including email lubow@pg.edu.pl and phone (58) 348 64 08. She maintains an active research profile with current projects and recent publications through 2025. Her research spans computational biomechanics with specific focus on abdominal wall mechanics, hernia repair systems, and temporomandibular joint analysis. She integrates structural engineering principles with medical applications through advanced computational modeling, uncertainty quantification, and machine learning techniques. Key methodologies include Self-Organising Maps for biomechanical data clustering and digital image correlation for in vivo strain analysis, targeting improvements in medical device design and surgical outcomes. Recent publications (2023-2025) demonstrate consistent interdisciplinary work bridging engineering and clinical medicine. Core themes include mechanical compatibility optimization of hernia implants, failure analysis of surgical mesh systems, and machine learning applications for identifying biomechanically similar tissue regions. This research emphasizes patient-specific modeling through uncertainty quantification and sensitivity analysis to address clinical challenges like hernia recurrence. Prof. Lubowiecka secures significant research funding through national programs: Mechanics of anterior abdominal wall in optimisation of hernia treatment : OPUS project (UMO-2017/27/B/ST8/02518) since 2018 3D-JAW : TMJ modeling for dental applications (POIR.04.01.02-00-0029/17-00) since 2017 Geometric-strength analysis of historical carpentry joints : OPUS project (UMO-2015/17/B/ST8/03260) since 2016 She leads a research team collaborating with medical professionals on translating computational biomechanics into clinical solutions for hernia repair and dental prosthetics, with emphasis on practical implementation of research findings.
Dr Dani Harmanto is an Associate Professor in Aeronautical Engineering at the School of Engineering and Sustainable Development, De Montfort University, Leicester. He is a chartered engineer with over 20 years of experience in UK higher education. His educational background includes: PhD in Automotive Engineering from Coventry University, UK MSc in Automotive Engineering from Coventry University, UK Bachelor's degree in Mechanical Engineering from Institut Teknologi Malang, Indonesia Dr Harmanto's research focuses on multidisciplinary areas including Computational Fluid Dynamics, Design Optimisation, and Material Selection. He integrates material science, design optimization, and fluid dynamics to address engineering challenges in sustainable energy systems and aeronautics. His work emphasizes practical applications in thermal management and aerodynamic efficiency. He has been recognized as an Inspirational Lecturer by the School of Engineering and Sustainable Development at De Montfort University in 2023. Inspirational Lecturers 2023 | School of Engineering and Sustainable Development, De Montfort University Dr Harmanto actively supervises postgraduate research, currently guiding Teerapath Limboonruang's PhD on optimizing heat transfer in solar parabolic trough collectors. He maintains strong research collaborations with Indonesia and other Far East nations, leveraging his background to develop sustainable research ecosystems and facilitate international partnerships in engineering education. He contributes to the Institute of Energy and Sustainable Development (IESD), holds Chartered Engineer status, and is a member of the Institution of Engineering Designers. His administrative roles include service on the Teaching and Learning committee (IED).
Dr. Noura Al Moubayed serves as an Associate Professor in the Department of Computer Science at Durham University, specializing in Explainable Machine Learning, Natural Language Processing, and Optimisation for high-dimensional data challenges. Education PhD from Robert Gordon University Post-doctoral positions at University of Glasgow and Durham University Research Focus Her work develops machine learning solutions for healthcare, social signal processing, cyber-security, and Brain-Computer Interfaces, specifically targeting noisy and imbalanced datasets through advanced NLP and optimization techniques. Current projects integrate deep learning with explainability frameworks to enhance real-world applicability. Publication Trends Recent publications (2020-2022) demonstrate consistent focus on improving question answering systems via bilinear pooling and paraphrasing techniques, alongside novel deep learning approaches for probabilistic topic modeling. These works bridge computer vision, NLP, and multimodal learning to address data imbalance challenges across healthcare and social computing domains. Academic Service PeerJ Computer Science Editorial Board Member 335 authorship points and 30 reviewer points on PeerJ platform
Khaled MESGHOUNI serves as a Lecturer at Centrale Lille, affiliated with the OSL (Optimisation et Sûreté des Systèmes) research team within the CRIStAL laboratory. His office is located in C313 at the Scientific City campus. His research centers on optimization and system safety in transportation infrastructure, with specific expertise in railway operations, autonomous vehicle systems, and port logistics. He employs computational intelligence methods including genetic algorithm hybridization to solve complex scheduling and routing challenges in real-world mobility networks. Dr. MESGHOUNI has supervised multiple doctoral candidates through CRIStAL, including Quoc Khanh Dang's work on train routing in railway stations (2021), Zhanjun Wang's research on shared vehicle management systems (2015), and Radhia Zaghdoud's thesis on autonomous vehicle applications for port infrastructure (2015). His OSL team focuses on developing intelligent solutions for transportation system reliability and efficiency.
Dr. Sadaf Hina is a Lecturer in Cybersecurity at the School of Science, Engineering and Environment (SSEE), University of Salford, Manchester, UK. She serves as the Programme Leader for the BSc Computer Science with Cybersecurity and holds significant research leadership roles as REF 2029 Co-Lead for People, Culture and Environment. Dr. Hina is an active member of the IoT Research and Innovation Lab (IRIL) and contributes to the Informatics Research Centre at the university. Her research interests span the critical intersection of artificial intelligence and cybersecurity, with specific expertise in IoT/IIoT security, zero-trust architectures, threat modeling in cyber-physical systems, and AI-aided security optimization. Over the past five years, her publication record shows consistent output in high-impact journals, with a notable increase in 2023-2025 focusing on cutting-edge applications of deep learning and vision transformers for security challenges. Her work demonstrates strong connections between theoretical security frameworks and practical industrial applications, particularly in critical infrastructure sectors. Dr. Hina has received significant professional recognition including: Fellow of the Higher Education Academy (FHEA, 2024) Advance HE Aurora Leadership Development Program certification (2025) REF Co-Lead roles for both People, Culture and Environment (2025) and Contributions to Knowledge and Understanding (2023) Editorial position for Applied Sciences journal (2024) Membership in professional organizations including IEEE (since 2014) and British Computer Society As a dedicated educator, Dr. Hina teaches Information Security, Information Security Management, Network Penetration Testing, Security and Privacy in IoT, and Fundamentals of Cybersecurity. She actively supervises BSc final year projects, MSc dissertations, and three PhD candidates working on AI-aided cybersecurity solutions. Her leadership extends to serving as Faculty Advisor for Women in Cybersecurity (WiCyS) and participation in cross-institutional mentoring programs, demonstrating commitment to developing the next generation of cybersecurity professionals.
