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Last updated 17th April 2024

I received the Ph.D. degree in Computational Intelligence from Aberystwyth University, Aberystwyth, U.K., in 2017, and then joined the University of Huddersfield as a Research Fellow and have since progressed to Lecturer, Senior Lecturer, and now Reader (~Associate Professor) in Artificial Intelligence. I’m the Course Leader for MSc Artificial Intelligence and MSc Applied Artificial Intelligence MSc. I’m the Team Lead on AI for Health and Wellbeing at the Centre for Autonomous and Intelligent Systems. 

My research in AI has primarily focused on probabilistic machine learning, sequence modelling and affective computing, with their applications in wellbeing and mental health.  I’ve published over 60 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.
 
I’m very keen translating AI techniques into real-world applications particularly the wellbeing and mental health domain with research supported and funded by Innovate UK, Research England, EPSRC, NHS and industrial partners. I have edited two book volumes and organised a number of special issues in leading journals in my field, and sit in the Editorial Board of the following journals:

Artificial Intelligence in Medicine (Elsevier, Q1)

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

PLOS One (Q1)

I enjoy and actively engage in frontline research and data science programming, consistently publishing as lead author since 2015, with some recent publications below:

• Chen, T., Can heart rate sequences from wearable devices predict day-long mental states in higher education students: a signal processing and machine learning case study at a UK university. Brain Informatics (Q1), 2024
• 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
• …..

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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