Dr. Chanchal Kaushik is a Lecturer in Radiography at the University of Salford's School of Health & Society, affiliated with the Centre for Applied Health Research. She joined in 2023 after previous academic positions in India and Bournemouth, bringing 11 years of international experience focused on equity and inclusion in healthcare education. Her research examines: Radiation dosimetry optimization and safety protocols Health technology assessment for diagnostic imaging AI applications for data variability analysis Real-time feedback systems in medical imaging Quality improvement in health services Recent publications (2020-2024) demonstrate consistent focus on medical imaging optimization, radiation dose management, and educational innovation. Work spans technical evaluations of PET-CT systems, patient dose monitoring frameworks, and novel teaching methodologies in radiography education. Awards and recognitions: Active Researcher Excellence Award (2020) £9,300 grant as Co-PI for AI segmentation research (2024-2025) Fellow of Advance HE (2025) Peer reviewer for Radiography Journal and Radiation and Environmental Biophysics Leads research-informed teaching modules across all academic levels in radiography, including Scientific Principles for Diagnostic Radiography, Research Methods, and Masters Dissertation supervision. Contributes to UN Sustainable Development Goals through medical imaging innovation.
Dr. Mahakim Newton is a Lecturer in Data Science at the University of Newcastle, Australia, and an Adjunct Senior Research Fellow at Griffith University’s Institute for Integrated and Intelligent Systems. He holds a PhD in Computer and Information Sciences from the University of Strathclyde, alongside degrees from Bangladesh University of Engineering and Technology (BUET). His research focuses on artificial intelligence, machine learning, bioinformatics, and computer education, with notable contributions to protein structure prediction and IoT interoperability. Education: Ph.D., University of Strathclyde M.Sc.Engg., Bangladesh University of Engineering and Technology B.Sc.Engg., Bangladesh University of Engineering and Technology Research Interests: Dr. Newton’s work bridges AI and computational biology, including protein-ligand binding affinity prediction, bioinformatics algorithms, and IoT edge networks. He explores machine learning techniques for environmental informatics and drug discovery, emphasizing scalable solutions for complex problems. Teaching: He coordinates courses like Computing Project , Algorithms , and Deterministic and Stochastic Optimisation at the University of Newcastle, integrating practical and theoretical insights. Grants and Labs: Involved in interdisciplinary projects on water quality prediction and edge computing interoperability. His collaborations span academic and industrial partners, advancing applications in healthcare and environmental monitoring.
Nick Barlow is a Research Fellow in Medicinal Chemistry at Monash University, leading a drug discovery group focused on peptide chemistry and small molecule drug development. His work bridges fundamental and translational research, targeting drug mechanisms involving peptidases, proteases, and GPCRs. He currently oversees diabetes research programs investigating melanocortin receptors' role in glucose control and has developed technologies enhancing membrane permeability of chemical tools and bioactive peptides. Barlow's team has advanced three peptide drug candidates to preclinical stages over the past five years, establishing startup companies for commercialization. His research contributes to UN Sustainable Development Goals addressing good health and well-being (SDG 3). Recent collaborations include projects on HIV-1 reverse transcriptase inhibition and cardiovascular disease mechanisms. Key projects include the 2021-2023 'Lead optimisation of novel inhibitors of IRAP' funded by Australian Research Council. His publications span peptide design, enzyme inhibition, and immunomodulatory mechanisms, reflecting expertise in drug delivery systems and fragment-based approaches.
Dr. Ian Morris is a Reader in Mathematics at Queen Mary University of London and Deputy Director of Postgraduate Research Studies. Previously, he held positions at the University of Surrey (2012–2020) and postdoctoral roles at institutions including the University of Rome Tor Vergata and the University of Warwick. His research focuses on ergodic theory, with applications to fractal geometry, matrix analysis, and dynamical systems. Education: PhD in Mathematics, University of Manchester (2006), supervised by Dr. Charles Walkden. Bachelor’s degree in Mathematics, University of Warwick. Research Interests: Morris specializes in ergodic theory and its applications to fractal geometry, joint spectral characteristics of matrices, and dynamical systems. His work includes studies on self-affine fractals, Lyapunov exponents, and thermodynamic formalism for linear cocycles. He has explored topics such as marginal instability in switched systems and the interplay between self-affine measures and fractal dimensions. Grants: Leverhulme Trust Research Project Grant (2024–2028): "An ergodic optimisation approach to stability of linear switched systems" (£189,097). Leverhulme Trust Grant (2017–2022): "Lower bounds for Lyapunov exponents" (£267,776). Advising and Collaborations: Morris supervised PhD student Jonah Varney (2018–2022) and postdoctoral researchers Natalia Jurga and Argyrios Christodoulou. His collaborations include work with Balázs Bárány, Antti Käenmäki, and Çağrı Sert on topics like self-affine measures and matrix equilibrium states. Labs/Teams: Morris is affiliated with the Centre for Complex Systems at Queen Mary University of London, focusing on interdisciplinary research in dynamical systems and fractal geometry.
Azam Tafreshi is a Lecturer in Mechanical and Aerospace Engineering at the University of Manchester. She holds a PhD in computational solid mechanics from Imperial College London and has expertise in fracture mechanics, composite structures, and numerical methods. Her research focuses on boundary element methods, shape optimization, and interface crack analysis in anisotropic materials. She developed novel algorithms for stress analysis and has authored over 20 international journal papers and book chapters. Her teaching roles include leading lecture modules on aerospace structures and numerical stress analysis. Education: BSc and MSc in Mechanical Engineering, PhD (Imperial College London), DIC. Postdoctoral research at University College London's NDE Centre. Awards include Fellow of the Institution of Mechanical Engineers (FIMechE). Research interests include computational solid mechanics, fracture mechanics, and composite materials. Her work emphasizes analytical and numerical approaches to crack propagation, structural integrity, and material failure mechanisms. Notable contributions include studies on interfacial cracks in bimaterial systems, delamination buckling in composite shells, and boundary element method applications. She collaborates in the Solid Mechanics Group at Manchester, focusing on residual stress and composite material behavior.
Dr Gu Pang is an Associate Professor in Procurement and Operations Management at the Department of Management, Birmingham Business School, University of Birmingham. She joined the university in January 2018 and currently serves as the Head of the Procurement and Operations Management Group. Her academic journey includes a PhD and MSc from Nottingham University Business School and a BSc in Management Science from Lancaster University Management School. PhD, Nottingham University Business School MSc, Operations Management, Nottingham University Business School BSc, Management Science, Lancaster University Management School Gu Pang's research focuses on interdisciplinary areas at the intersection of operations, sustainability, and digital innovation. Her primary interests include blockchain technology, remanufacturing, reverse logistics, closed-loop and sustainable supply chains, food value chains, food waste management, transportation network design, optimization, time series econometrics, machine learning, and digital transformation. She emphasizes student-centered learning and promotes self-sufficient learners through her educational philosophy. Her recent publications (2024–2025) demonstrate a strong trend toward digital transformation and sustainability in supply chains. Her work frequently explores blockchain applications in food safety and remanufacturing, AI in food systems and travel, and optimization of green supply chains. She has contributed to high-impact journals such as Long Range Planning , International Journal of Production Economics , IEEE Transactions on Engineering Management , and Journal of Cleaner Production , reflecting a consistent focus on technological innovation for sustainable operations. Dr Pang has led significant research initiatives, including the EU Horizon 2020 Project VALUMICS on food value chains (€318,555, completed May 2020) and an ESRC Knowledge Transfer Partnership with Byker Community Trust on sustainable marketing (£130,000, completed July 2020). These projects highlight her ability to secure competitive funding and deliver impactful, interdisciplinary research. EU Horizon 2020 Project VALUMICS: Understanding food value chains and network dynamics (€318,555, 48 months) ESRC Knowledge Transfer Partnership: Sustainable and strategic marketing strategy, brand development, and change management (£130,000, 24 months) She teaches courses such as Operations Management, Managing Operations and Projects (Year 2), and Exec MBA (UK) modules. As a Senior Fellow of the Higher Education Academy, she is committed to excellence in teaching. She welcomes PhD applicants interested in machine learning, blockchain, remanufacturing, reverse logistics, closed-loop supply chains, food value chains, and optimization, encouraging informal discussions via email.
Professor Iskander Aliev holds a Personal Chair in the School of Mathematics at Cardiff University. His research spans integer optimization, discrete mathematics, and number theory, with significant contributions to the geometry of numbers and Diophantine approximations. Research Interests: Integer Optimization using Algebraic and Geometric Methods Discrete Mathematics including Geometry of Numbers and Discrete Geometry Number Theory with focus on Diophantine Approximations and Additive Number Theory His recent publications demonstrate strong trends in integer programming, particularly examining sparsity properties, proximity bounds, and integrality gaps. His work connects discrete geometry with optimization theory, often focusing on lattice structures and their applications to computational problems across mathematics and computer science. Scientific Recognition: Editor of Beiträge zur Algebra und Geometrie Editor of Combinatorics and Number Theory Recipient of EPSRC grant EP/Y032551/1 for "Average-case proximity for integer optimisation" (June 2024-May 2025) Professor Aliev is actively involved in research within the Operational Research, Mathematical Analysis, and Discrete Mathematics and Data Science groups at Cardiff University. His teaching includes MA3007 Coding Theory and MA3603 Optimisation courses. His extensive publication record spans from 1998 to 2025, reflecting sustained contributions to his fields of expertise. His PhD was completed at IM PAN under Prof. Andrzej Schinzel, and his MSc at St.-Petersburg State University under Prof. Yuri Matiyasevich, establishing strong foundations in mathematical theory that continue to inform his research.
Kolios Athanasios is a Visiting Professor in the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde, where he joined in 2018 as Professor in Risk and Asset Management. He is affiliated with the Faculty of Engineering and has held leadership roles in multiple major research initiatives, including EPSRC CDTs and EU H2020 projects. His research focuses on risk, reliability, and asset management in offshore and marine renewable energy systems. Key areas include: Quantitative risk and decision-making in engineering Performance- and risk-based design of offshore energy assets Reliability analysis using stochastic methods Integrity assessment of ageing structures Development and optimisation of renewable energy technologies Calibration of design standards The recent publications reflect a strong trend in reliability modelling, maintenance optimisation, and economic viability of offshore wind farms. Themes include leading-edge erosion, pitch system failures, data-driven maintenance, and uncertainty in weather forecasting. The work combines field data, stochastic modelling, and machine learning to improve O&M decision-making and reduce LCoE. His scientific recognition includes: Chartered Engineer, Institution of Mechanical Engineers Fellow of the Higher Education Academy Board Member, European Academy of Wind Energy Member, ISSC Offshore Renewable Energy Committee He has served as Principal Investigator and Co-Investigator on numerous grants, including EPSRC Supergen, H2020-ROMEO, and REMS CDT. He has supervised research students and datasets, led the development of open-access O&M tools, and contributed to joint industry projects like SLIC. His work supports UN Sustainable Development Goals related to affordable and clean energy. He is actively involved in research networks and has contributed to the development of frameworks for floating offshore wind and vertical axis turbines. His collaborations span academia, industry, and certification bodies across Europe.
Sam Cocking is a Researcher at the University of Cambridge , affiliated with the Department of Engineering . He works at the Centre for Smart Infrastructure and Construction , focusing on structural monitoring and assessment of ageing railway infrastructure. Research Focus: Structural monitoring, masonry/concrete construction, acoustic emission, fibre-optic sensing, and decarbonisation/climate resilience decision-support tools for transport infrastructure. Projects: UK National Hub for Decarbonised, Adaptable, and Resilient Transport Infrastructures (DARe), monitoring church pinnacles, and structural assessment of a 350-year-old tree. Technologies: Fibre-optic sensing, acoustic emission sensors, videogrammetry, LiDAR, and finite-element modeling. Collaborations: Centre for Smart Infrastructure and Construction (CSIC), DARe Hub. Research Trends: Publications emphasize masonry arch bridges, structural monitoring technologies, seismic analysis, and machine learning applications for form-finding. Studies span 2016-2025, reflecting long-term engagement with infrastructure resilience and historical preservation. Conservation Efforts: Interdisciplinary work includes monitoring church pinnacles and ancient trees, bridging civil engineering with cultural and environmental conservation.
Justin Pearson is an Associate Professor at the Department of Information Technology; Division of Computing Science at Uppsala University . He is a member of the university's optimisation group and coordinates the IT department's mentor programme for new employees . Research Interests include Constraint Programming , Combinatorial Optimisation , Artificial Intelligence , Software Testing , and Complexity Theory . His work focuses on theoretical and practical aspects of constraint satisfaction, local search algorithms, and symmetry breaking in constraint programming. Teaching involves courses such as Algorithms and Data Structures II (1DL231) and Introduction to Machine Learning for Bachelor Students (1DL034), with a PhD-level course on Category Theory offered periodically based on demand. Scientific Contributions span publications in constraint programming for air traffic management, sensor networks, and industrial applications. Recent work includes parameterised treewidth in constraint models, time-series constraints, and symmetry breaking techniques. Students supervised include PhD candidates Frej Knutar Lewander (co-supervised with Pierre Flener), Yi Zhao (co-supervised with Di Yuan), and previously graduated students Gustav Björdal , María Andreína Francisco Rodríguez , and Joseph Scott .
Professor Andreas Albrecht is a faculty member in the Department of Computer Science at Middlesex University, located at Hendon Town Hall, London. His research focuses on advanced computational techniques and interdisciplinary applications, including combinatorial optimisation, stochastic algorithms, nature-inspired computing, and machine learning. He also explores biomolecular structure prediction, microRNA pathway analysis, boolean circuit complexity, and VLSI design. For research collaborations or knowledge transfer, contact Dr. Aboubaker Lasebae. Postgraduate research enquiries (PhD/MRes) should contact Professor Juan Augusto. Undergraduate/postgraduate taught programmes (BSc/MSc) enquiries go to Dr. Serengul Smith. Contact details: Office TG19b, Town Hall Building, Hendon Campus. Address: Department of Computer Science, Middlesex University, The Burroughs, London NW4 4BT, UK.
Dr. Georgios Tzimiropoulos is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on Computer Vision and Deep Learning, with an emphasis on image/video recognition, 3D reconstruction, face recognition, and action recognition. He leads projects in data-efficient deep learning and its applications to video analysis. He teaches an undergraduate module on Artificial Intelligence, covering search algorithms, logic, and decision theory. Recent research includes advancements in neural networks, generative models (GANs), and multimodal AI. He has secured grants such as the EPSRC-funded 'Reliable AI and Data Optimisation' (2024–2026), totaling £339,312. Collaborators include Dr. Ioanna Ntinou and others in the Centre for Multimodal AI. His work spans facial dynamics, video super-resolution, and efficient model quantization, published in top venues like CVPR and ICCV.
Sobhan (Sean) Arisian is Associate Professor of Supply Chain and Logistics at La Trobe Business School. He leads the Sustainable Operations Management discipline and serves as Associate Investigator at the ARC Training Centre in Optimisation Technologies (OPTIMA). Research focuses on supply chain resilience, digitalization, and sustainability—particularly decarbonization of maritime transport and disaster relief logistics. Recent publications demonstrate strong emphasis on quantitative optimization models, with recurring themes in: Robust optimization for disruption management Sustainable logistics decarbonization Humanitarian supply chain coordination Quantum computing applications in operations Awarded the Inaugural Collaborative Research Award by BAM/ANZAM and Outstanding Reviewer recognition. Secured $382,742 from Australian Government for Quantum Enhanced Optimisation project and $234,400 DFAT National Focused Grant. Collaborates with University of Cambridge scholars and industry partners on digital transformation strategies. Editorial roles include Associate Editor for Transportation Research Part E and IEEE Transactions on Engineering Management.
Dr. Jiaming Ma is a post-doctoral researcher at RMIT University's Centre for Innovative Structures and Materials (CISM), working on the ARC Laureate Fellowship project. His research focuses on material and structural innovations for sustainable civil engineering, including rammed earth, metamaterials, and topology optimization. He holds a Researcher academic rank and is affiliated with the School of Engineering's Department of School of Engineering. Dr. Ma has received notable awards such as the 2022 Hangai Prize and Best Paper Award. He has led roles in organizing academic symposia and professional associations, including the Chinese Association of Professionals and Scholars in Australia. His work emphasizes sustainable construction and digital fabrication methods. Research Interests: Rammed earth, Sustainable building materials, Topology optimisation, Digital Construction, Computational morphogenesis, Shell structures. These areas address environmental sustainability and advanced structural solutions. Key achievements include pioneering bio-binder stabilization for rammed earth and developing deployable tubular structures. His articles span structural optimization, metamaterials, and sustainable design, reflecting interdisciplinary contributions to civil engineering and materials science. Awards include the Hangai Prize for shell structure innovation, DNA Paris Design Award, and leadership in academic conferences. He supervises research projects on metamaterials and rammed earth construction. Professional contributions include roles as President of the Chinese Association of Professionals in Australia and organizing the IASS Annual Symposium 2023. His work bridges academic research with industry applications, particularly in eco-friendly construction practices.
Professor Zheng-Tong Xie is a Professor at the University of Southampton's Department of Engineering and Environment. His research focuses on Aerodynamics, Computational Fluid Dynamics (CFD), Turbulence, and Urban Wind Engineering. He leads modules in Applications of CFD, Race Car Design GDP, and Computational Aerodynamics. Active in professional roles, he serves as a Fellow of the Royal Meteorological Society (since 2009), Chair of the Urban Fluid Mechanics Special Interest Group (since 2017), and Council Member of the UK Wind Engineering Society (since 2014). His work spans urban dispersion modeling, tall building aerodynamics, and CFD methodology development. Current research includes the FUTURE project on urban tall-building clusters and the DIPLOS project on localized urban dispersion. Advises PhD students Keertan Kumar Maskey and Donnchadh Eoghan MacGarry. Collaborates on EPSRC and industry-funded projects, with a focus on wind engineering, turbulence, and fluid dynamics applications. Key research interests include urban airflow dynamics, pollutant dispersion, and CFD validation against sensor data. He contributes to large-eddy simulation (LES) advancements for urban environments, addressing challenges like tall building clusters and street network dispersion. His external roles reflect leadership in both academic and professional wind engineering communities. Research outcomes bridge theoretical CFD models with practical urban design and environmental monitoring needs.
