Overview
Scientific simulations and instruments like MRI or CT-scans produce nowadays a large amount of data that can be hard for scientists to interpret. The use of advanced Graphics and Visualisation algorithms possibly supported by AI can allow people to get a better understanding of the data. This group is particularly concerned with efficient processing of 3D datasets that can be encoded for instance as a 3D mesh or rectilinearly sampled grids.
This group has successfully looked at various problems in recent years, including issues related to dealing with large amount of data while still providing real-time processing and/or display of images to users. Members of this group have for instance worked on new algorithms having a better complexity to render 3D datasets or proposed better data encoding data to meet these goals. The use of AI to provide state-of-the-art lossless compression of large medical datasets was for instance pioneered within the group.
This group is also interested in various aspects of modelling Physical phenomena used in 3D renderings, including real-time visualisation of incompressible fluids or using bonded discrete element methods for simulating fractures.
Simulation of incompressible fluids
Lossless compression of medical data using an LSTM network to predict the next voxel value
3D display of the classical “Stanford bunny”
Our Facilities
Key Enabling Technologies:
Specialist Area Leads
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Professor Mark Jones
Available for Postgraduate Supervision Profile Professor Mark W. Jones is a data scientist with areas of expertise in photon mapping, ray tracing, global illumination, visualization, kernel density estimation, time-series data, accelerometry data, transfer functions, probability density functions, clustering, Monte-Carlo techniques, statistics, distance measures, Lloyd’s relaxation, Voronoi diagrams, vector/chamfer distances, volume rendering, data structures (kd-trees). YouTube…
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Dr Benjamin Mora
Available for Postgraduate Supervision Profile Ben Mora is an Associate Professor in the department of Computer science, Swansea University. Area of Expertise Projects Specialist Areas Events
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Professor Chenfeng Li
Profile Chenfeng Li FLSW, Professor of Civil Engineering, is internationally recognized for pioneering research in engineering computation, data analytics, uncertainty quantification, and risk assessment. He has developed innovative computational solutions to tackle complex technical challenges across civil infrastructure, materials, manufacturing, and energy sectors. His expertise is widely valued by leading organizations in infrastructure and construction, including ARUP, Costain, Bauer, and Soletanche Bachy.…
Projects
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Digital Twinning for Temporary Works Enabling Safe and Economic Project Implementation
Project Overview The construction industry currently relies on engineers, experience, prescribed codes and manual design processes to deliver buildings andinfrastructures. Due to the growing scale and complexity of construction projects, this existing system has become inefficient and costly. In some cases, it has even compromised safety and quality. Digital technology has significantly improved other industries…
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Cyber Physical modelling of Deep Pile Foundations
Project Overview This project aims to develop a cyber-physical model of deep pile foundations to enhance the construction process through real-time monitoring, simulation, and data-driven decision-making. By integrating computational fluid dynamics (CFD) with sensor-based data acquisition and concrete flow simulation using tools like OpenFOAM, the model will provide valuable insights into the behavior of tremie…
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Image-based Digital Testing for Functional Construction Materials
Project Overview This project integrates physical modelling, data analysis, and microstructural characterisation into long-term product assessment tests. Traditional construction material assessments are costly and time-consuming, limiting industry innovation. By leveraging microstructural imaging, this research aims to simulate and eventually predict accurate material behaviour through structural analysis, enhancing the development of functional construction materials. Project Aims…
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Smart digital representation and reconstruction in material science with AI and computer vision
Project Overview This project aims to integrate computer vision and artificial intelligence into materials science, utilizing deep learning and other AI methodologies to enable efficient and cost-effective digital characterization and reconstruction of heterogeneous materials. By advancing the application of emerging AI technologies, this research seeks to accelerate the development of materials informatics and enhance digital…
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Explicit and Implicit Finite Element Techniques
Project Overview Explicit and Implicit Finite Element Techniques Applied to Mechanical and Coupled Geomechanical Problems October 2018-March 2022 In this work we determine the classes of problems within computational geomechanics where the staggered or fully implicit monolithic coupling schemes are most effective. These techniques can be applied in industries such as civil engineering and the energy-based sector, in particular the oil and gas industry.…
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Numerical Modelling of Concrete Rheology in Deep Foundation Constructions
Project Overview Defects such as mattressing, inclusions, blockage and bleed caused by insufficient concrete flow or sub-par concrete quality within deep foundation constructions lead to costly delays that impact all project stakeholders. This research aims to use multiphase flow modelling to further our understanding of the mechanisms that impact concrete flow within deep foundations like…
Events
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Zienkiewicz Institute Community Event – 19th November 2025
Date: 19th November 2025 Time: 13:30 – 15:30 Location: Engineering North, 102 Speakers: Oubay Hassan, Siraj Shaikh Overview of Event: Dear colleague, For the upcoming ZI community event, Professor Oubay Hassan and Professor Siraj Shaikh have kindly agreed to share their recent experience in winning a Programme Grant and a Prosperity Partnership Grant. Date: Wednesday…
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Zienkiewicz Institute Community Event for Grant Calls
Time: 15th October 2025 Location: Eng North 010 and 008 Speakers: Overview of the Conference: The next Zienkiewicz Institute community event will be held on Wednesday, 15th October 2025. It will focus on the following three grant calls: UKRI Artificial Intelligence for Environmental Science Phase One (Deadline 11 December 2025) UKRK Addressing Nuclear Fission Challenges for a…
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Networking Session and Lunch at the Distinguished Zienkiewicz Institute Seminar Organized by ZI PGR Society
Time: 12:00 pm – 15:00 pm, 8th October 2025 Location: The atrium area in the computational foundry Speakers: Dr Royston Jones is CTO, Altair Product Design & Senior Vice President, Global Automotive Vertical List of Participants: ZI-PGR society and members of ZI community Contact Information: Mohsin Ali (ZI-PGR society President), email: mohsin.ali@Swansea.ac.uk Overview of the…
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Zienkiewicz Institute Community Event – July 2025
Time: 23rd July 2025 Location: B001, Engineering Central, Bay Campus Speakers: Chenfeng Li, Arnold Beckmann, Djordje Peric, Khiêm Vu Ngoc, Fabio Caraffini, PhD Students Overview of the Conference: Programme:• 09:30-10:00: Welcome coffee & collection of your FREE ZI polo shirt• 10:00-11:00: Celebrating ZI’s achievements and looking ahead to new opportunities.• 11:00-12:00: Launch of the ZI…
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MadeAI2025: The 2nd International Conference of Modelling, Data Analytics and AI in Engineering
Conference Introduction: This event serves as a dynamic platform for the exchange of ground breaking ideas and insights. Delve into the powerful synergy of modelling, data analytics, and AI in engineering, uncovering new opportunities to advance innovation and solve complex challenges. The conference is dedicated to driving research and fostering transformative breakthroughs in these fields,…
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Computational Methods for Multiscale, Multiuncertainty and Multiphysics Problems
Conference Introduction: Over the past two decades, research in multi-physics, multi-scale, and multi-uncertainty modeling has grown significantly, driven by advances in mathematical methods, numerical strategies, and computational power. This field integrates homogenization, parallel computing, and stochastic analysis, with applications ranging from materials science to biomedical engineering. The CM3P(Computational Methods for Multiscale, Multi-uncertainty and Multi-physics Problems)…
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2nd ZI Community event on AI and Data Science for Healthcare
Speaker: Time: 9am, 5th June 2025 Location/Room: Wallace 218 The ZI has hosted a collaborative event aimed at Swansea-based researchers (and others) who are interested in advancing healthcare research through Data, Modelling and AI.
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UK-Belgium Deeptech Innovation Event
Speaker: Professor Xianghua Xie, Computer Science, Swansea University Time: 20th March 2025 Location/Room: Brussels, Belgium Together with AI4Belgium, British Embassy Belgium invited leading Belgian companies, UK representatives, and innovators in the health tech, medtech, and life sciences sectors to meet to exchange ideas and explore collaborations during the European AI Week. This Conference was attended by Professor Xianghua…
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Registration open for event with Hartree Centre
“Extreme Scaling Computing and Emerging Computational Approaches in Science and Engineering” Find further programme details here Venue: Y Twyni, Room 105 (Bay Campus) Registration Deadline: Wed 18th September Register here The main purpose of the workshop is to scope future collaborations between Swansea and the Hartree Centre. Subjects covered include Artificial Intelligence, Automotive, Transport and Logistics, Computational Chemistry,…