Professor Mark Jones

Professor, Computer Science

+44 (0) 1792 513391

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Office - 225
Second Floor
Computational Foundry
Bay Campus

Available For Postgraduate Supervision

Research Links

https://orcid.org/0000-0001-8991-1190

ResearchGate

Google Scholar

ResearcherID

Scopus

About

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

markwjones.github.io (GitHub - publications)

Areas Of Expertise

Ray Tracing;
Global Illumination;
Data Visualization;
Data Science;
Time-Series Data;
Volume Visualization;
Computer Graphics

Publications

Research Highlights

Patel, T., Jones, M., & Redfern, T. (2023). Manifold Explorer: Satellite Image Labelling and Clustering Tool with Using Deep Convolutional Autoencoders. Algorithms, 16(10), 469
https://doi.org/10.3390/a16100469, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64669
http://dx.doi.org/10.3390/a16100469
Nagoor, O., Whittle, J., Deng, J., Mora, B., & Jones, M. (2022). Sampling strategies for learning-based 3D medical image compression. Machine Learning with Applications, 8, 100273
https://doi.org/10.1016/j.mlwa.2022.100273, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59383
Alqahtani, A., Ali, M., Xie, X., & Jones, M. (2021). Deep Time-Series Clustering: A Review. Electronics, 10(23), 3001
https://doi.org/10.3390/electronics10233001, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58874
Alqahtani, A., Xie, X., & Jones, M. (2021). Literature Review of Deep Network Compression. Informatics, 8(4), 77
https://doi.org/10.3390/informatics8040077, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58687
Ali, M., Borgo, R., & Jones, M. (2021). Concurrent time-series selections using deep learning and dimension reduction. Knowledge-Based Systems, 233, 107507
https://doi.org/10.1016/j.knosys.2021.107507, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57939

All Research

Journal Articles

Patel, T., Jones, M., & Redfern, T. (2023). Manifold Explorer: Satellite Image Labelling and Clustering Tool with Using Deep Convolutional Autoencoders. Algorithms, 16(10), 469
https://doi.org/10.3390/a16100469, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64669
http://dx.doi.org/10.3390/a16100469
Nagoor, O., Whittle, J., Deng, J., Mora, B., & Jones, M. (2022). Sampling strategies for learning-based 3D medical image compression. Machine Learning with Applications, 8, 100273
https://doi.org/10.1016/j.mlwa.2022.100273, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59383
Ali, M., Borgo, R., & Jones, M. (2021). Concurrent time-series selections using deep learning and dimension reduction. Knowledge-Based Systems, 233, 107507
https://doi.org/10.1016/j.knosys.2021.107507, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57939
Alqahtani, A., Ali, M., Xie, X., & Jones, M. (2021). Deep Time-Series Clustering: A Review. Electronics, 10(23), 3001
https://doi.org/10.3390/electronics10233001, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58874
Alqahtani, A., Xie, X., & Jones, M. (2021). Literature Review of Deep Network Compression. Informatics, 8(4), 77
https://doi.org/10.3390/informatics8040077, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58687
Alqahtani, A., Xie, X., Jones, M., & Essa, E. (2021). Pruning CNN filters via quantifying the importance of deep visual representations. Computer Vision and Image Understanding, 208-209, 103220
https://doi.org/10.1016/j.cviu.2021.103220, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56831
Ali, M., Jones, M., Xie, X., & Williams, M. (2019). TimeCluster: dimension reduction applied to temporal data for visual analytics. The Visual Computer, 35(6-8), 1013-1026.
https://doi.org/10.1007/s00371-019-01673-y, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa49701
Ali, M., Alqahtani, A., Jones, M., & Xie, X. (2019). Clustering and Classification for Time Series Data in Visual Analytics: A Survey. IEEE Access, 7, 181314-181338.
https://doi.org/10.1109/access.2019.2958551, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52963
MAN, D., Jones, M., LI, D., ZHANG, H., & SONG, Z. (2019). Calibration of Turntable Based 3D Scanning Systems. IEICE Transactions on Information and Systems, E102.D(9), 1833-1841.
https://doi.org/10.1587/transinf.2019EDP7043, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51640
Manduhu, M. & Jones, M. (2019). A Work Efficient Parallel Algorithm for Exact Euclidean Distance Transform. IEEE Transactions on Image Processing, 28(11), 5322-5335.
https://doi.org/10.1109/TIP.2019.2916741, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50104
Dearden, J., Gong, Y., Jones, M., & Wilson, A. (2019). Using the State Space of a BLV Retail Model to Analyse the Dynamics and Categorise Phase Transitions of Urban Development. Urban Science, 3(1), 31
https://doi.org/10.3390/urbansci3010031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48971
https://www.mdpi.com/2413-8851/3/1/31
Xie, X., Jones, M., & Tam, G. (2017). Recognition, Tracking, and Optimisation. International Journal of Computer Vision, 122(3), 409-410.
https://doi.org/10.1007/s11263-017-1008-8, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa32785
Whittle, J., Jones, M., & Mantiuk, R. (2017). Analysis of reported error in Monte Carlo rendered images. The Visual Computer, 33(6-8), 705-713.
https://doi.org/10.1007/s00371-017-1384-7, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa33015
Whittle, J., Borgo, R., & Jones, M. (2016). Implementing generalized deep-copy in MPI. PeerJ Computer Science, 2, e95
https://doi.org/10.7717/peerj-cs.95, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa31197
Wilson, R., Holton, M., Walker, J., Shepard, E., Scantlebury, D., Wilson, V., Wilson, G., Tysse, B., Gravenor, M., Ciancio, J., McNarry, M., Mackintosh, K., Qasem, L., Rosell, F., Graf, P., Quintana, F., Gomez-Laich, A., Sala, J., Mulvenna, C...., & Gravenor, M. (2016). A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle. Movement Ecology, 4(1)
https://doi.org/10.1186/s40462-016-0088-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa30318
Walker, J., Jones, M., Laramee, R., Holton, M., Shepard, E., Williams, H., Scantlebury, D., Marks, N., Magowan, E., Maguire, I., Bidder, O., Di Virgilio, A., Wilson, R., & Laramee, B. (2015). Prying into the intimate secrets of animal lives; software beyond hardware for comprehensive annotation in ‘Daily Diary’ tags. Movement Ecology, 3(1)
https://doi.org/10.1186/s40462-015-0056-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa21998
http://www.movementecologyjournal.com/content/3/1/29
Bidder, O., Walker, J., Jones, M., Holton, M., Urge, P., Scantlebury, D., Marks, N., Magowan, E., Maguire, I., Wilson, R., Jones, M., Holton, M., & Wilson, R. (2015). Step by step: reconstruction of terrestrial animal movement paths by dead-reckoning. Movement Ecology, 3(1)
https://doi.org/10.1186/s40462-015-0055-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa21955
http://www.movementecologyjournal.com/content/3/1/23
Walker, J., Borgo, R., & Jones, M. (2015). TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data. IEEE Transactions on Visualization and Computer Graphics, 22(1), 549-558.
https://doi.org/10.1109/TVCG.2015.2467751, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23067
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7192735&tag=1
Wilson, G., Holton, M., Walker, J., Jones, M., Grundy, E., Davies, I., Clarke, D., Luckman, A., Russill, N., Wilson, V., Plummer, R., & Wilson, R. (2015). A new perspective on how humans assess their surroundings; derivation of head orientation and its role in ‘framing’ the environment. PeerJ, 3(e908), e908-29.
https://doi.org/10.7717/peerj.908, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa20646
Walker, J., Jones, M., Laramee, R., Bidder, O., Williams, H., Scott, R., Shepard, E., Wilson, R., & Laramee, B. (2015). TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data. The Visual Computer, 31(6-8), 1067-1078.
https://doi.org/10.1007/s00371-015-1112-0, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa20645
Dearden, J., Jones, M., & Wilson, A. (2015). DynaMoVis: Visualization of dynamic models for urban modeling. The Visual Computer, 31(6-8), 1079-1088.
https://doi.org/10.1007/s00371-015-1096-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa20644
Spencer, B., Jones, M., Lim, I., & Jones, M. (2015). A Visualization Tool Used to Develop New Photon Mapping Techniques. Computer Graphics Forum, 34(1), 127-140.
https://doi.org/10.1111/cgf.12464, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18728
http://cs.swansea.ac.uk/%7Ecsmark/PDFS/2014_metavis.pdf
Borgo, R., Dearden, J., & Jones, M. (2014). Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection. IEEE Transactions on Visualization and Computer Graphics, 20(12), 2261-2270.
https://doi.org/10.1109/TVCG.2014.2346428, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18118
http://cs.swansea.ac.uk/~csmark/PDFS/2014_infovis_order_of_magnitude_markers.pdf
Najim, S., Lim, I., Wittek, P., & Jones, M. (2014). FSPE: Visualization of Hyperspectral Imagery Using Faithful Stochastic Proximity Embedding. IEEE Geoscience and Remote Sensing Letters, 12(1), 18-22.
https://doi.org/10.1109/LGRS.2014.2324631, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18053
Hughes, D., Lim, I., Jones, M., Knoll, A., Spencer, B., & Jones, M. (2013). InK-Compact: In-Kernel Stream Compaction and Its Application to Multi-Kernel Data Visualization on General-Purpose GPUs. Computer Graphics Forum, 32(6), 178-188.
https://doi.org/10.1111/cgf.12083, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15061
Doidge, I. & Jones, M. (2013). Probabilistic illumination-aware filtering for Monte Carlo rendering. The Visual Computer, 29(6-8), 707-716.
https://doi.org/10.1007/s00371-013-0807-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15063
Spencer, B. & Jones, M. (2013). 2013 Cover Image: Prism. Computer Graphics Forum, 32(1), 216-217.
https://doi.org/10.1111/cgf.12017, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15064
Legg, P., Chung, D., Parry, M., Bown, R., Jones, M., Griffiths, I., & Chen, M. (2013). Transformation of an Uncertain Video Search Pipeline to a Sketch-Based Visual Analytics Loop. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2109-2118.
https://doi.org/10.1109/TVCG.2013.207, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16829
Spencer, B., Jones, M., & Jones, M. (2013). Photon Parameterisation for Robust Relaxation Constraints. Computer Graphics Forum, 32(2pt1), 83-92.
https://doi.org/10.1111/cgf.12028, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa14358
Spencer, B. & Jones, M. (2013). Progressive photon relaxation. ACM Transactions on Graphics, 32(1), 1-11.
https://doi.org/10.1145/2421636.2421643, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa14350
Legg, P., Chung, D., Parry, M., Jones, M., Long, R., Griffiths, I., Chen, M., Jones, M., & Griffiths, I. (2012). MatchPad: Interactive Glyph-Based Visualization for Real-Time Sports Performance Analysis. Computer Graphics Forum, 31(3pt4), 1255-1264.
https://doi.org/10.1111/j.1467-8659.2012.03118.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15066
McLoughlin, T., Jones, M., Laramee, R., Malki, R., Masters, I., Hansen, C., Jones, M., Masters, I., & Laramee, B. (2012). Similarity Measures for Enhancing Interactive Streamline Seeding. IEEE Transactions on Visualization and Computer Graphics, 19(8), 1342-1353.
https://doi.org/10.1109/TVCG.2012.150, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15062
http://cs.swan.ac.uk/%7Ecsmark/PDFS/similaritymeasures.pdf
Doidge, I., Jones, M., & Mora, B. (2012). Mixing Monte Carlo and progressive rendering for improved global illumination. The Visual Computer, 28(6-8), 603-612.
https://doi.org/10.1007/s00371-012-0703-2, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13561
Spencer, B., Jones, M., Jones, M., & Spencer, B. (2009). Hierarchical Photon Mapping. IEEE Transactions on Visualization and Computer Graphics, 15(1), 49
https://doi.org/10.1109/TVCG.2008.67, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa173
Blaas, J., Botha, C., Grundy, E., Jones, M., Laramee, R., Post, F., Jones, M., Laramee, B., & Grundy, E. (2009). Smooth Graphs for Visual Exploration of Higher-Order State Transitions. IEEE Transactions on Visualization and Computer Graphics, 15(6), 969
https://doi.org/10.1109/TVCG.2009.181, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa175
Spencer, B., Jones, M., Jones, M., & Spencer, B. (2009). Into the Blue: Better Caustics through Photon Relaxation. Computer Graphics Forum, 28(2), 319
https://doi.org/10.1111/j.1467-8659.2009.01371.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa176
Grundy, E., Jones, M., Laramee, R., Wilson, R., Shepard, E., & Laramee, B. (2009). Visualisation of Sensor Data from Animal Movement. Computer Graphics Forum, 28(3), 815
https://doi.org/10.1111/j.1467-8659.2009.01469.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa182
Spencer, B. & Jones, M. (2009). CGForum 2009 Cover Image. Computer Graphics Forum, 28(1), 172-172.
https://doi.org/10.1111/j.1467-8659.2009.01415.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15067
Chen, M., Correa, C., Islam, S., Jones, M., Shen, P., Silver, D., Walton, S., Willis, P., & Jones, M. (2007). Manipulating, Deforming and Animating Sampled Object Representations. Computer Graphics Forum, 26(4), 824-852.
https://doi.org/10.1111/j.1467-8659.2007.01102.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15068
Jones, M., Baerentzen, J., Sramek, M., & Jones, M. (2006). 3D distance fields: a survey of techniques and applications. IEEE Transactions on Visualization and Computer Graphics, 12(4), 581-599.
https://doi.org/10.1109/TVCG.2006.56, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1679
Brodlie, K., Brooke, J., Chen, M., Chisnall, D., Fewings, A., Hughes, C., John, N., Jones, M., Riding, M., & Roard, N. (2005). Visual Supercomputing: Technologies, Applications and Challenges. Computer Graphics Forum, 24(2), 217-245.
https://doi.org/10.1111/j.1467-8659.2005.00845.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1685
Satherley, R. & Jones, M. (2002). Hypertexturing complex volume objects. The Visual Computer, 18(4), 226
https://doi.org/10.1007/s003710100143, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1681
Satherley, R. & Jones, M. (2001). Vector-City Vector Distance Transform. Computer Vision and Image Understanding, 82(3), 238-254.
https://doi.org/10.1006/cviu.2001.0915, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1683
Jones, M. (1996). The Production of Volume Data from Triangular Meshes Using Voxelisation. Computer Graphics Forum, 15(5), 311-318.
https://doi.org/10.1111/1467-8659.1550311, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16834
Chen, M., Jones, M., & Townsend, P. (1996). Volume distortion and morphing using disk fields. Computers & Graphics, 20(4), 567-575.
https://doi.org/10.1016/0097-8493%2896%2900027-1, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16835
Jones, M. & Chen, M. (1994). A New Approach to the Construction of Surfaces from Contour Data. Computer Graphics Forum, 13(3), 75-84.
https://doi.org/10.1111/1467-8659.1330075, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16837

Book Chapters

Satherley, R. & Jones, M. (2001). Hybrid Distance Field Computation. Volume Graphics 2001-209).
https://doi.org/10.1007/978-3-7091-6756-4_13, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16831
Satherley, R. & Jones, M. (2000). Extending Hypertextures to Non-Geometrically Definable Volume Data. Volume Graphics (pp. 211-225).
https://doi.org/10.1007/978-1-4471-0737-8_13, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16833
Chen, M., Jones, M., Townsend, P., & Jones, M. (1995). Methods for Volume Metamorphosis. Image Processing for Broadcast and Video Production (pp. 280-292).
https://doi.org/10.1007/978-1-4471-3035-2_24, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16836

Conference Contributions

Alqahtani, A., Xie, X., Essa, E., & Jones, M. (2021). Neuron-based Network Pruning Based on Majority Voting. In 2020 25th International Conference on Pattern Recognition (ICPR)IEEE.
https://doi.org/10.1109/icpr48806.2021.9412897, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55572
Nagoor, O., Whittle, J., Deng, J., Mora, B., Jones, M., & Whittle, J. (2021). MedZip: 3D Medical Images Lossless Compressor Using Recurrent Neural Network (LSTM). In 2020 25th International Conference on Pattern Recognition (ICPR)IEEE.
https://doi.org/10.1109/icpr48806.2021.9413341, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55395
http://dx.doi.org/10.1109/icpr48806.2021.9413341
Nagoor, O., Whittle, J., Deng, J., Mora, B., & Jones, M. (2020). Lossless Compression For Volumetric Medical Images Using Deep Neural Network With Local Sampling. In 2020 IEEE International Conference on Image Processing (ICIP) (pp. 2815-2819). IEEE.
https://doi.org/10.1109/icip40778.2020.9191031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55355
Alqahtani, A., Xie, X., Deng, J., & Jones, M. (2019). Learning Discriminatory Deep Clustering Models. In M. Vento & G. Percannella (Ed.), Computer Analysis of Images and Patterns (pp. 224-233).
https://doi.org/10.1007/978-3-030-29888-3_18, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50907
Colasanti, R., Borgo, R., & Jones, M. (2019). Emoji and Chernoff - A Fine Balancing Act or are we Biased?. In 2019 IEEE Pacific Visualization Symposium (PacificVis) (pp. 102-111).
https://doi.org/10.1109/PacificVis.2019.00020, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48170
Ali, M., Jones, M., Xie, X., & Williams, M. (2018). Towards Visual Exploration of Large Temporal Datasets. In In 2018 International Symposium on Big Data Visual Analytics (BDVA) 2018
https://doi.org/10.1109/BDVA.2018.8534025, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa43563
Alqahtani, A., Xie, X., Deng, J., Jones, M., Jones, M., Xie, X., & Deng, J. (2018). A Deep Convolutional Auto-Encoder with Embedded Clustering. In 2018 25th IEEE International Conference on Image Processing (ICIP) (pp. 4058-4062). 25th IEEE International Conference on Image Processing (ICIP).
https://doi.org/10.1109/ICIP.2018.8451506, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa40682
https://ieeexplore.ieee.org/document/8451506
Whittle, J. & Jones, M. (2018). A Deep Learning Approach to No-Reference Image Quality Assessment For Monte Carlo Rendered Images. In Computer Graphics and Visual Computing (CGVC) 2018
https://doi.org/10.2312/cgvc.20181204, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa43567
Li, D., Zhang, H., Song, Z., Man, D., & Jones, M. (2017). An Automatic Laser Scanning System for Accurate 3D Reconstruction of Indoor Scenes. In 2017 IEEE International Conference on Information and Automation (ICIA)2017 IEEE International Conference on Information and Automation (ICIA).
https://doi.org/10.1109/ICInfA.2017.8079017, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa34894
Nagoor, O., Borgo, R., & Jones, M. (2017). Data Painter: A Tool for Colormap Interaction. In Computer Graphics & Visual Computing (CGVC) 2017
https://doi.org/10.2312/cgvc.20171280, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa35294
Walton, S. & Jones, M. (2007). Interacting with Volume Data: Deformations using Forward Projection. (pp. 48-53).
https://doi.org/10.1109/MEDIVIS.2007.12, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa15069
Treavett, S., Chen, M., Satherley, R., Jones, M., & Jones, M. (2001). Volumes of expression: artistic modelling and rendering of volume datasets. (pp. 99-106).
https://doi.org/10.1109/CGI.2001.934663, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16830
Jones, M., Satherley, R., & Jones, M. (2001). Shape representation using space filled sub-voxel distance fields. (pp. 316-325).
https://doi.org/10.1109/SMA.2001.923403, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa16832

Supervision

Untitled (current)

PhD

Other supervisor: Prof Gibin Powathil
Text-Based Person Re-identification for Robustness Research (current)

PhD

Other supervisor: Prof Xianghua Xie

Other supervisor: Dr Scott Yang
Novel human-in-the-loop 3D point cloud completion for sub sea surveying (current)

PhD

Other supervisor: Dr Muneeb Ahmad

Other supervisor: Dr Gary Tam
Developing methodologies for the efficient creation of data labels, tools to reduce human effort, and aid perception and understanding of big datasets in an underwater context, supporting rapid development and explainability of machine learning models. (current)

PhD

Other supervisor: Dr Scott Yang
Labelling of neural network nodes utilising a neural network trained on aerial imagery (current)

PhD

Other supervisor: Prof Matt Jones
Machine Learning for geospatial placement (current)

PhD

Other supervisor: Dr Sarah Roberts
Geospatial machine learning in safety critical systems (current)

PhD

Other supervisor: Dr Mike Edwards
3D Medical Image Lossless Compressor Using Deep Learning Approaches (awarded 2022)

PhD

Other supervisor: Prof Xianghua Xie
Face Reenactment with Generative Landmark Guidance (awarded 2023)

MSc

Other supervisor: Prof Xianghua Xie

Taught Modules

CS-256 Visual Computing

This module will provide an introduction to Visual Computing and its applications including visualisation, visual analytics, graphics and machine learning. It will help students to extend their programming skills and theoretical knowledge on the analysis and understanding of advanced algorithms. It will also allow students to make good choices about specialist modules they can take in year 3, the projects they can follow in year 3, and future careers.

Key Grants and Projects

Data Release - Trust, Identity, Privacy and Security 2016 - 2019

EPSRC Grant Number, EP/N028139/1 , £993,796
Advanced Visualisation Techniques for Urban Modelling/Simulation 2013 - 2015

Leverhulme Grant, RPG-2013-190, £89,523
Faster and higher quality global illumination 2011 - 2014

EPSRC Grant Number EP/I031243/1, £247,013

Other Roles

Programme chair and co-chair, BMVC

2015 - 2015
Member of the Editorial Board (Associate Editor), Computer Graphics Forum

2014 - 2017
Management Board, RIVIC

2010 - Present
Organiser, RIVIC Graduate School

2014 - 2014
Director of Admissions , Swansea University

2011 - 2014
Member, REF Working Group

2012 - Present
Environment Lead, REF

2012 - Present

Professor Mark Jones

Telephone number

Email address

Research Links

About

Areas Of Expertise

Research Highlights

All Research

Untitled (current)

Text-Based Person Re-identification for Robustness Research (current)

Novel human-in-the-loop 3D point cloud completion for sub sea surveying (current)

Developing methodologies for the efficient creation of data labels, tools to reduce human effort, and aid perception and understanding of big datasets in an underwater context, supporting rapid development and explainability of machine learning models. (current)

Labelling of neural network nodes utilising a neural network trained on aerial imagery (current)

Machine Learning for geospatial placement (current)

Geospatial machine learning in safety critical systems (current)

3D Medical Image Lossless Compressor Using Deep Learning Approaches (awarded 2022)

Face Reenactment with Generative Landmark Guidance (awarded 2023)

CS-256 Visual Computing

Programme chair and co-chair, BMVC

Member of the Editorial Board (Associate Editor), Computer Graphics Forum

Management Board, RIVIC

Organiser, RIVIC Graduate School

Director of Admissions , Swansea University

Member, REF Working Group

Environment Lead, REF