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Role:
Department staff:
Research staff:
- blockchain
- Artificial Intelligence
- Machine Learning
- Building Energy Modelling
- Building Information Modelling
- Finance in Sport
- Energy in Buildings
- Renewable and Sustainable Energy
- Fintech
- Digital governance
- Fairness
Teaching staff:
- Qualifications:FHEA, PhD, BSc,
- Position:Senior Lecturer - Financial Technology
- Department:FBL - Accounting, Economics and Finance
- Telephone:+441173283432
- Email:Xiaojun.Luo@uwe.ac.uk
About me
Office Hour: Mondays 14:00-16:00 at 3X111 or on Teams: Xiaojun's office
I am a Senior Lecturer in Financial Technology, and my work sits at the intersection of FinTech, machine learning, blockchain, fairness and sustainable built environments. I am listed in the Stanford Top 2% rankings for scientists. My research examines how emerging digital technologies can be designed, implemented, and governed responsibly, particularly in the finance, business, and energy sectors. I have published 45 peer-reviewed journal articles (41 as first or corresponding author), with an h-index of 24 and 1,600+ citations, and 27 of these papers appear in SCImago Q1 journals across energy, buildings, technology and finance. I am passionate about mentoring students in converting their dissertations into journal papers. I am also the chief editor of an Elsevier book on Net-Zero Transition in Buildings.
I have obtained several external and internal funding sources for my research projects, including a British Academy Small Grant on bridging legal and statistical fairness in AI systems, an ACFE Data Access Award on machine learning-based fraud detection in financial statements, and a UKFin+ award on Fintech and Blockchain Accelerator, along with two UWE-funded projects on AI and blockchain in building energy management. I am a member of the UKRI Talent Peer Review College and ESRC Assessor College, and I have also reviewed funding applications for the Royal Academy of Engineering and the Hong Kong Research Grants Council.
I value teaching and pedagogic innovation. I led modules in Financial Technology, FinTech Project, Financial Investment in Practice, and Governance and Accountability. I have redesigned key modules to introduce hands-on Python machine learning and Solidity smart-contract programming, giving business and finance students practical exposure to coding. My pedagogic research on mapping blockchain into accounting and finance curricula and on teaching programming to novice coders has been published in Accounting Education and the Journal of International Education in Business. I am also keen on game-based learning activities in my modules.
I am passionate about supervising students' dissertations and projects and is open to supervising new PhD candidates.
Area of expertise
Financial technology, blockchain, cryptocurrency, artificial intelligence, machine learning, big data analytics, data mining, governance and accountability, evolutionary optimisation, sustainability, sustainable energy management, building energy modelling, building physics, life-cycle inventory assessment, renewable energy system, building decarbonisation.
Publications
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