Professor Gibin Powathil

Professor

Mathematics

+44 (0) 1792 606255

g.g.powathil@swansea.ac.uk

Office - 323
Third Floor
Computational Foundry
Bay Campus

Available For Postgraduate Supervision

Research Links

https://orcid.org/0000-0002-8372-7349

ResearchGate

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Scopus

About

Professor Gibin Powathil is an applied mathematician, focusing his research on interdisciplinary multi-scale approaches to utilise mathematics to understand the underlying complexity of various biological and biomedical problems in medicine and in particular, cancer.

Currently, Gibin is working on developing multiscale models of cancer growth and treatment protocols to study various optimum treatment strategies; eventually to devise much needed predictive patient specific multimodality treatment regimes. These mathematical and computational models can be very helpful in gaining valuable insights into the mechanisms and consequences of various complex intracellular and intercellular changes during and after therapy.

Gibin received his PhD in Applied Mathematics from the University of Waterloo, Canada for his research on mathematical modelling of brain tumours. He has also received a MS in Computational Mathematics from National University of Singapore and MSc in Mathematics from Indian Institute of Technology, Madras, India.

Areas Of Expertise

Mathematical Biology
Mathematical Oncology
Multiscale Cancer Modelling
Modelling Anticancer therapies
Applications of Imaging Techniques in Cancer Modelling
Computational Mathematics

Career Highlights

Teaching Interests

Gibin’s teaching interests are mainly in Applied Mathematics topics. He regularly teaches courses on numerical, computational and biomathematics.

Research Collaborations

Publications

Research Highlights

Xie, X., Styles, I., Powathil, G., & Ceccarelli, M. (2024). Artificial Intelligence in Healthcare Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-67278-1, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67497
Pugh, K., Davies, M., & Powathil, G. (2023). A Mathematical Model to Investigate the Effects of Ceralasertib and Olaparib in Targeting the Cellular DNA Damage Response Pathway. Journal of Pharmacology and Experimental Therapeutics, 387(1), 55-65.
https://doi.org/10.1124/jpet.122.001558, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63760
Mohammadrezaei, D., Moghimi, N., Vandvajdi, S., Powathil, G., Hamis, S., & Kohandel, M. (2023). Predicting and elucidating the post-printing behavior of 3D printed cancer cells in hydrogel structures by integrating in-vitro and in-silico experiments. Scientific Reports, 13(1)
https://doi.org/10.1038/s41598-023-28286-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62393
SPINICCI, K., Jacquet, P., Powathil, G., & Stéphanou, A. (2022). Modeling the role of HIF in the regulation of metabolic key genes LDH and PDH: Emergence of Warburg phenotype. Computational and Systems Oncology, 2(3)
https://doi.org/10.1002/cso2.1040, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60373
Brüningk, S. & Powathil, G. (2022). Modelling Direct and Indirect Effects of Radiation: Experimental, Clinical and Environmental Implications. In NATO Science for Peace and Security Series A: Chemistry and Biology (pp. 69-87). Springer Netherlands.
https://doi.org/10.1007/978-94-024-2101-9_5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59774

All Research

Journal Articles

Pugh, K., Davies, M., & Powathil, G. (2023). A Mathematical Model to Investigate the Effects of Ceralasertib and Olaparib in Targeting the Cellular DNA Damage Response Pathway. Journal of Pharmacology and Experimental Therapeutics, 387(1), 55-65.
https://doi.org/10.1124/jpet.122.001558, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63760
Mohammadrezaei, D., Moghimi, N., Vandvajdi, S., Powathil, G., Hamis, S., & Kohandel, M. (2023). Predicting and elucidating the post-printing behavior of 3D printed cancer cells in hydrogel structures by integrating in-vitro and in-silico experiments. Scientific Reports, 13(1)
https://doi.org/10.1038/s41598-023-28286-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62393
SPINICCI, K., Jacquet, P., Powathil, G., & Stéphanou, A. (2022). Modeling the role of HIF in the regulation of metabolic key genes LDH and PDH: Emergence of Warburg phenotype. Computational and Systems Oncology, 2(3)
https://doi.org/10.1002/cso2.1040, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60373
HAMIS, S., Yates, J., Chaplain, M., & Powathil, G. (2021). Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs. Bulletin of Mathematical Biology, 83(10)
https://doi.org/10.1007/s11538-021-00935-y, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57780
Liu, R., Higley, K., Swat, M., Chaplain, M., Powathil, G., & Glazier, J. (2021). Development of a coupled simulation toolkit for computational radiation biology based on Geant4 and CompuCell3D. Physics in Medicine & Biology, 66(4), 045026
https://doi.org/10.1088/1361-6560/abd4f9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55919
Hamis, S., Kohandel, M., Dubois, L., Yaromina, A., Lambin, P., & Powathil, G. (2020). Combining hypoxia-activated prodrugs and radiotherapy in silico: Impact of treatment scheduling and the intra-tumoural oxygen landscape. PLOS Computational Biology, 16(8), e1008041
https://doi.org/10.1371/journal.pcbi.1008041, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54884
Mothersill, C., Oughton, D., Schofield, P., Abend, M., Adam-Guillermin, C., Ariyoshi, K., Beresford, N., Bonisoli-Alquati, A., Cohen, J., Dubrova, Y., Geras’kin, S., Hevrøy, T., Higley, K., Horemans, N., Jha, A., Kapustka, L., Kiang, J., Madas, B., Powathil, G...., & Wood, M. (2020). From tangled banks to toxic bunnies; a reflection on the issues involved in developing an ecosystem approach for environmental radiation protection. International Journal of Radiation Biology, 1-16.
https://doi.org/10.1080/09553002.2020.1793022, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54697
Stéphanou, A., Ballet, P., & Powathil, G. (2020). Hybrid data-based modelling in oncology: successes, challenges and hopes. Mathematical Modelling of Natural Phenomena, 15, 21
https://doi.org/10.1051/mmnp/2019026, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50956
Meaney, C., G Powathil, G., Yaromina, A., J Dubois, L., Lambin, P., Kohande, M., & Powathil, G. (2019). Role of hypoxia-activated prodrugs in combination with radiation therapy: An in silico approach. Mathematical Biosciences and Engineering, 16(6), 6257-6273.
https://doi.org/10.3934/mbe.2019312, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50957
Hamis, S., Powathil, G., & Chaplain, M. (2019). Blackboard to Bedside: A Mathematical Modeling Bottom-Up Approach Toward Personalized Cancer Treatments. JCO Clinical Cancer Informatics(3), 1-11.
https://doi.org/10.1200/CCI.18.00068, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48867
Mothersill, C., Abend, M., Bréchignac, F., Copplestone, D., Geras’kin, S., Goodman, J., Horemans, N., Jeggo, P., McBride, W., Mousseau, T., O’Hare, A., Papineni, R., Powathil, G., Schofield, P., Seymour, C., Sutcliffe, J., & Austin, B. (2019). The tubercular badger and the uncertain curve:- The need for a multiple stressor approach in environmental radiation protection. Environmental Research, 168, 130-140.
https://doi.org/10.1016/j.envres.2018.09.031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa44623
Hamis, S., Nithiarasu, P., & Powathil, G. (2018). What does not kill a tumour may make it stronger: In silico insights into chemotherapeutic drug resistance. Journal of Theoretical Biology, 454, 253-267.
https://doi.org/10.1016/j.jtbi.2018.06.014, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa40715
Kim, Y., Kang, H., Powathil, G., Kim, H., Trucu, D., Lee, W., Lawler, S., & Chaplain, M. (2018). Role of extracellular matrix and microenvironment in regulation of tumor growth and LAR-mediated invasion in glioblastoma. PLOS ONE, 13(10), e0204865
https://doi.org/10.1371/journal.pone.0204865, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa44785
Bowness, R., Chaplain, M., Powathil, G., & Gillespie, S. (2018). Modelling the effects of bacterial cell state and spatial location on tuberculosis treatment: Insights from a hybrid multiscale cellular automaton model. Journal of Theoretical Biology, 446, 87-100.
https://doi.org/10.1016/j.jtbi.2018.03.006, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa39000
Mothersill, C., Abend, M., Bréchignac, F., Iliakis, G., Impens, N., Kadhim, M., Møller, A., Oughton, D., Powathil, G., Saenen, E., Seymour, C., Sutcliffe, J., Tang, F., & Schofield, P. (2018). When a duck is not a duck; a new interdisciplinary synthesis for environmental radiation protection. Environmental Research, 162, 318-324.
https://doi.org/10.1016/j.envres.2018.01.022, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa38187
Brüningk, S., Powathil, G., Ziegenhein, P., Ijaz, J., Rivens, I., Nill, S., Chaplain, M., Oelfke, U., & Haar, G. (2018). Combining radiation with hyperthermia: a multiscale model informed by in vitro experiments. Journal of The Royal Society Interface, 15(138), 20170681
https://doi.org/10.1098/rsif.2017.0681, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa37332
Borasi, G., Nahum, A., Paulides, M., Powathil, G., Russo, G., Fariselli, L., Lamia, D., Cirincione, R., Forte, G., Borrazzo, C., Caccia, B., di Castro, E., Pozzi, S., & Gilardi, M. (2016). Fast and high temperature hyperthermia coupled with radiotherapy as a possible new treatment for glioblastoma. Journal of Therapeutic Ultrasound, 4(1)
https://doi.org/10.1186/s40349-016-0078-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa31385
Powathil, G., Munro, A., Chaplain, M., & Swat, M. (2016). Bystander effects and their implications for clinical radiation therapy: Insights from multiscale in silico experiments. Journal of Theoretical Biology, 401, 1-14.
https://doi.org/10.1016/j.jtbi.2016.04.010, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18359
http://dx.doi.org/10.1016/j.jtbi.2016.04.010
Chaplain, M. & Powathil, G. (2015). Multiscale modelling of cancer progression and treatment control: The role of intracellular heterogeneities in chemotherapy treatment. Biophysical Reviews and Letters
https://doi.org/10.1142/S1793048015500058, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18361
Kim, Y., Powathil, G., Kang, H., Trucu, D., Kim, H., Lawler, S., & Chaplain, M. (2015). Strategies of Eradicating Glioma Cells: A Multi-Scale Mathematical Model with MiR-451-AMPK-mTOR Control. PLOS ONE, 10(1), e0114370
https://doi.org/10.1371/journal.pone.0114370, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18362
Powathil, G., Swat, M., & Chaplain, M. (2014). Systems oncology: Towards patient-specific treatment regimes informed by multiscale mathematical modelling. Seminars in Cancer Biology
https://doi.org/10.1016/j.semcancer.2014.02.003, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18357
Powathil, G., Chaplain, M., & Swat, M. (2014). Investigating the development of chemotherapeutic drug resistance in cancer: A multiscale computational study (preprint). arXiv.org
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18360
http://arxiv.org/abs/1407.0865
Powathil, G., Adamson, D., & Chaplain, M. (2013). Towards Predicting the Response of a Solid Tumour to Chemotherapy and Radiotherapy Treatments: Clinical Insights from a Computational Model. PLoS Computational Biology, 9(7), e1003120
https://doi.org/10.1371/journal.pcbi.1003120, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18356
Powathil, G., Gordon, K., Hill, L., & Chaplain, M. (2012). Modelling the effects of cell-cycle heterogeneity on the response of a solid tumour to chemotherapy: Biological insights from a hybrid multiscale cellular automaton model. Journal of Theoretical Biology, 308, 1-19.
https://doi.org/10.1016/j.jtbi.2012.05.015, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18354
Powathil, G., Kohandel, M., Milosevic, M., & Sivaloganathan, S. (2012). Modeling the Spatial Distribution of Chronic Tumor Hypoxia: Implications for Experimental and Clinical Studies. Computational and Mathematical Methods in Medicine, 2012, 1-11.
https://doi.org/10.1155/2012/410602, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18353
Powathil, G., Kohandel, M., Sivaloganathan, S., Oza, A., Milosevic, M., & Powathil, G. (2007). Mathematical modeling of brain tumors: effects of radiotherapy and chemotherapy. Physics in Medicine and Biology, 52(11), 3291-3306.
https://doi.org/10.1088/0031-9155/52/11/023, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18352

Authored Books

Xie, X., Styles, I., Powathil, G., & Ceccarelli, M. (2024). Artificial Intelligence in Healthcare Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-67278-1, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67497

Book Chapters

Hamis, S., Stratiev, S., & Powathil, G. (2020). Uncertainty and Sensitivity Analyses Methods for Agent-Based Mathematical Models: An Introductory Review. In Bernard S Gerstman (Ed.), The Physics of Cancer (pp. 1-37). WORLD SCIENTIFIC
https://doi.org/10.1142/9789811223495_0001, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52960
Hamis, S. & Powathil, G. (2020). Can we Crack Cancer?. The Art of Theoretical Biology (pp. 50-51). Springer International Publishing
https://doi.org/10.1007/978-3-030-33471-0_25, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54698
Powathil, G. & Chaplain, M. (2014). A Hybrid Multiscale Approach in Cancer Modelling and Treatment Prediction. Mathematical Oncology 2013 (pp. 237-263). Birkhauser
https://doi.org/10.1007/978-1-4939-0458-7_8, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18358

Conference Contributions

Brüningk, S. & Powathil, G. (2022). Modelling Direct and Indirect Effects of Radiation: Experimental, Clinical and Environmental Implications. In NATO Science for Peace and Security Series A: Chemistry and Biology (pp. 69-87). Springer Netherlands.
https://doi.org/10.1007/978-94-024-2101-9_5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59774
Powathil, G., Thompson, A., Chaplain, M., & Powathil, G. (2012). The role of cellular heterogeneity on the therapeutic response of breast cancer: Clinical insights from a hybrid multiscale computational model. In Cancer Research (pp. P5-05-02-P5-05-02).
https://doi.org/10.1158/0008-5472.SABCS12-P5-05-02, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18355

Other Research Outputs

Powathil, G. (2009). Modelling of brain tumours: Effects of microenvironment and associated therapeutic strategies
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18364
https://uwspace.uwaterloo.ca/handle/10012/4738
Powathil, G. (2004). A heat and mass transfer model for bread baking: an investigation using numerical schemes
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa18365
http://scholarbank.nus.sg/handle/10635/14601

Supervision

Mathematical modelling the role of circulating tumor DNA in diagnosis and therapy (current)

PhD

Other supervisor: Dr Noemi Picco
Modelling Cancer Immunotherapy: Investigating T-cell engaging therapies in Oncology (current)

PhD

Other supervisor: Prof Mark Jones
Modelling the spatial ecology of cancer. (current)

PhD

Other supervisor: Dr Noemi Picco
Mathematical Modelling of Cancer-Adipocyte Interactions in Ovarian Cancer (current)

PhD

Other supervisor: Dr Noemi Picco

Other supervisor: Prof Deya Gonzalez
Mathematical models of tumour growth: the beyond mean-field approach (current)

PhD

Other supervisor: Dr Dmitri Finkelshtein
Computational and mathematical approaches to understand glioma cells metabolism : characterization from transcriptomic data and focus on HIF pathways (awarded 2024)

PhD

Other supervisor: Dr Noemi Picco
Modelling the Effects and Responses of DNA Damage Response (DDR) Inhibitor Drugs (awarded 2024)

PhD

Other supervisor: Dr Noemi Picco
An Exploration into the Usage of Augmented Reality Hardware Within Educational Institutions. (current)

PhD

Other supervisor: Dr Tom Owen

Other supervisor: Dr Sean Walton

Taught Modules

CSC360 Mathematical Modelling: Theory and Practice

This module focusses on developing mathematical models of real world problems. It considers how to create a model, how to simulate and analyse the model and how to use the model to answer questions about the world around us. It will consider a diverse selection of examples from a range of areas including biology, mechanics, medicine and physics. There will be weekly modelling workshops and PC labs in which students will actively create and analyse their own models. The module will culminate in a group project in which students will create, analyse and simulate a model of their own.
MA-243 Mathematical Modelling: Theory and Practice

This module focusses on developing mathematical models of real world problems. It considers how to create a model, how to simulate and analyse the model and how to use the model to answer questions about the world around us. It will consider a diverse selection of examples from a range of areas including biology, mechanics, medicine and physics. There will be weekly modelling workshops and PC labs in which students will actively create and analyse their own models. The module will culminate in a group project in which students will create, analyse and simulate a model of their own.
MA-M17 Modelling and Machine Learning

The module provides a basic introduction to mathematical modelling and computational methods. The module covers basic problems in computation including error analysis and methods for solving equations. It also highlights the use of Python in the numerical solution of problems, as well as symbolic computation. The module will also introduce some of the most widely used and state-of-the-art artificial intelligence and machine learning techniques and their applications to big data problems.

Affiliated Positions

Deputy Co-Director, Centre for Biomathematics

2021 - Present
Associated Researcher , Health Data Research UK

2019 - Present

Career History

Professor, Swansea University

2023 - Present
Associate Professor, Swansea University, UK

2019 - 2023
Senior Lecturer, Swansea University, UK

2014 - 2019
Postdoctoral Researcher , University of Dundee, UK

2009 - 2014

Other Roles

Member, Newton International Fellowships Committee, The Royal Society

2024 - 2026
Deputy Head, Department of Mathematics, Swansea University

2022 - Present
Vice Secretary , Society for Mathematical Biology

2023 - 2024
Secretary , Society for Mathematical Biology

2020 - 2023
Editorial Board Member, npj Systems Biology and Applications

2023 - Present
Editorial Board Member, Journal of Theoretical Biology

2019 - Present
Associate Editor, Mathematical Bioscience and Engineering

2018 - Present
Impact Lead- UoA, Department of Mathematics, Swansea University

2016 - Present
Outreach Officer, Department of Mathematics, Swansea University

2020 - Present

Key Grants and Projects

HDRUK (NIWA1) 2018 - 2023

with Lyons RA, Lawler M, Ford DV, Berridge D, Kee F, Powathil GG, Brophy S, O’Reilly D, John A et al., £4,702,650
Multiscale Modelling of Angiogenesis and Lymphangiogenesis 2018 - 2021

Joint project with Dr van Loon (Swansea) and Dr Stephanou (Grenoble), £85K
Computational and Mathematical Approaches to Understand Cancer Cells Metabolism 2020 - 2023

Joint project with Dr Stephanou (Grenoble), £85K

Conference and Workshop Organisation

Programme C0-Chair, AI in Healthcare 2024, Swansea.
Organizing Committee, 2021 Annual Conference of Society for Mathematical Biology, SMB2021
Scientific Committee, 2021 Annual Conference of Society for Mathematical Biology, SMB2021
Program Committee, 1st (2019) and 2nd (2020) International Symposium on Mathematical and Computational Oncology
Workshop on Mathematical Medicine and Pharmacology- 2017, Centre for Biomathematics, Swansea University

Professor Gibin Powathil

Telephone number

Email address

Twitter Account

LinkedIn Account

Research Links

About

Areas Of Expertise

Career Highlights

Research Highlights

All Research

Mathematical modelling the role of circulating tumor DNA in diagnosis and therapy (current)

Modelling Cancer Immunotherapy: Investigating T-cell engaging therapies in Oncology (current)

Modelling the spatial ecology of cancer. (current)

Mathematical Modelling of Cancer-Adipocyte Interactions in Ovarian Cancer (current)

Mathematical models of tumour growth: the beyond mean-field approach (current)

Computational and mathematical approaches to understand glioma cells metabolism : characterization from transcriptomic data and focus on HIF pathways (awarded 2024)

Modelling the Effects and Responses of DNA Damage Response (DDR) Inhibitor Drugs (awarded 2024)

An Exploration into the Usage of Augmented Reality Hardware Within Educational Institutions. (current)

CSC360 Mathematical Modelling: Theory and Practice

MA-243 Mathematical Modelling: Theory and Practice

MA-M17 Modelling and Machine Learning

Deputy Co-Director, Centre for Biomathematics

Associated Researcher , Health Data Research UK

Professor, Swansea University

Associate Professor, Swansea University, UK

Senior Lecturer, Swansea University, UK

Postdoctoral Researcher , University of Dundee, UK

Member, Newton International Fellowships Committee, The Royal Society

Deputy Head, Department of Mathematics, Swansea University

Vice Secretary , Society for Mathematical Biology

Secretary , Society for Mathematical Biology

Editorial Board Member, npj Systems Biology and Applications

Editorial Board Member, Journal of Theoretical Biology

Associate Editor, Mathematical Bioscience and Engineering

Impact Lead- UoA, Department of Mathematics, Swansea University

Outreach Officer, Department of Mathematics, Swansea University

HDRUK (NIWA1) 2018 - 2023

Multiscale Modelling of Angiogenesis and Lymphangiogenesis 2018 - 2021

Computational and Mathematical Approaches to Understand Cancer Cells Metabolism 2020 - 2023