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Last updated 17th April 2024

Tianhua Chen received the Ph.D. degree in Computational Intelligence from Aberystwyth University, Aberystwyth, U.K., in 2017. He is currently a Reader (Associate Professor) in Artificial Intelligence with the Department of Computer Science, School of Computing and Engineering, University of Huddersfield.

Tianhua's research interests lie in explainable AI (XAI), with a particular interest in neuro-symbolic/fuzzy systems. He has published over 50 peer reviewed papers in leading international journals and conferences, including a lead-authored paper selected as IEEE Transactions on Fuzzy System Publication Spotlight Article by IEEE Computational Intelligence Society.

Tianhua has edited two book volumes and organised a number of special issues in journals such as Artificial Intelligence in Medicine and Frontiers in Neuroscience. With research supported and funded by Innovate UK, Research England, EPSRC and industrial partners, Tianhua is very keen translating AI techniques into real-world applications particularly the health and care domain.

Tianhua is an Editorial Board Member of:

Artificial Intelligence in Medicine (Elsevier, Q1)

BMC Medical Informatics and Decision Making (Springer, Q1). 

PLOS One (Q1)

Tianhua enjoys and actively engages in frontline research and data science programming. He has consistently published as the lead author on research papers annually since 2015, with some of recent publications below:

• Chen T, , et al., Diagnosing attention-deficit hyperactivity disorder (ADHD) using artificial intelligence: a clinical study in the UK. Frontiers in Psychiatry (Q1). 2023 ​
• Chen, T., Investigating the mental health of university students during the COVID-19 pandemic in a UK university: a machine learning approach using feature permutation importance. Brain Informatics (Q1), 2023​
• Chen T, , et al., The mental health of university students during the COVID-19 pandemic: An online survey in the UK. PloS one (Q1), 2022.​
• Chen T, , et al., A dominant set-informed interpretable fuzzy system for automated diagnosis of dementia. Frontiers in Neuroscience (Q1), 2022. ​
• Chen T, , et al., eds. "Artificial intelligence in healthcare: recent applications and developments." Springer, 2022
• Chen T, , et al., Automatic diagnosis of attention deficit hyperactivity disorder using machine learning. Applied Artificial Intelligence (Q2), 2021.​
• Chen T, , et al., Medical analytics for healthcare intelligence–Recent advances and future directions. Artificial Intelligence in Medicine (Q1), 2021.​
• Chen T, , et al., A decision tree-initialised neuro-fuzzy approach for clinical decision support. Artificial Intelligence in Medicine (Q1), 2021.​
• Chen T, , et al., A new approach for transformation-based fuzzy rule interpolation. IEEE Transactions on Fuzzy Systems (Q1), 2020
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Teaching (2021/2020):

Course Leader: MSc Artificial Intelligence 

Module Leader: MSc CMS3503 Machine Learning 

Module Leader: MSc CMI3506 Case Study in Data Analytics and Artificial Intelligence

Module Tutor: BSc CHA2555 Artificial Intelligence

Services:

• (Special) Session Chair, BI2021, ICIRA 2019, UKCI 2018
• Technical Programme Committee Member: IJCAI 2021, MICCAI 2021 2020, FUZZ-IEEE 2021 2020 2019 2018, UKCI 2021 2020 2019 2018, ICEBE 2021 2020 2019 2018, BI 2021, FSDM 2020, MobiSPC 2020 2019, iSCI 2018
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