Education and Professional Qualifications

Research Programme

My research develops across three methodological strands. The first is trustworthy machine learning for market integrity and risk, covering representation-learning approaches to market-manipulation detection (Dai, Quinn, Kearney et al., under review at Information Processing and Management and at Economics Letters) and transformer-based crash-risk modelling (Birem, Abidi Perier, Quinn & Kearney, under review at the European Journal of Operational Research). The methodological commitment throughout is that model performance and model trustworthiness are separable properties, both of which must be evidenced before deployment in operational or regulatory settings.

The second is computer vision for socio-economic measurement: the Hannon, French, Quinn & O’Hagan geospatial study of vehicle crime in Northern Ireland (submitted to Insurance: Mathematics and Economics), and the hierarchical flag-classification programme (4,501-image NI dataset; 70→16→7 taxonomy; ViT-H-14 baseline at 94.78% on the 7-category task; codebase at economic-flag-classification). Both treat vision pipelines as measurement instruments rather than accuracy-maximising systems.

The third is causal and statistical evidence for governance and regulation: innovation signals and strategic exits in computational approaches to financial regulation (Kearney, Quinn & Pramanick, under review at the Journal of Business Venturing); ownership, risk and regulation in Chinese banking (Zhang, Quinn & Sheenan, CRBF WP 25-017); and the collaborative doctoral partnerships with Pytillia, Napier AI and Funds Axis. Across all three strands the methodological priority is that evidence survive operational and regulatory scrutiny — assumptions explicit, uncertainty quantified, and claims proportionate to what the data can support.

Key Publications (Selected from 14 peer-reviewed papers)

ABS4 Journal:

• Liu, Weilong, Zhang, Yong, Liu, Kailong, Quinn, Barry, Yang, Xingyu, Peng, Qiao (2024). Evolutionary Multi-Objective Optimisation for Large-Scale Portfolio Selection With Both Random and Uncertain Returns. IEEE Transactions on Evolutionary Computation (ABS4).

Recent ABS3 Publications:

• McKillop, Donal, Liu, Kailong, Quinn, Barry, Peng, Qiao (Forthcoming). Modelling and Predicting Credit Union Failures. International Journal of Forecasting (ABS3).
• Bouri, E., Quinn, B., Sheenan, L. & Tang, Y. (2024). Investigating extreme linkage topology in the aerospace and defence industry. International Review of Financial Analysis (ABS3).
• Quinn, Barry, Gallagher, Ronan, Kuosmanen, Timo (2023). Lurking in the shadows: The impact of CO2 emissions target setting on carbon pricing in the Kyoto agreement period. Energy Economics (ABS3).

Full publication list: see index.qmd or request on application.

Research Impact and Funding

Figures are read from the canonical data/Grant_income.csv. For the full grants register and total research income across 13 awards, see cv_grants.qmd.

Working Papers

• Dai, Yongsheng, Quinn, Barry, Kearney, Fearghal, Wang, Hui (Submitted). Amplifying Market Manipulation Detection Signals. Submitted to Economics Letters. Manuscript EL66561.
• Dai, Yongsheng, Quinn, Barry, Kearney, Fearghal, Liu, Weilong, Spence, Ivor, Rafferty, Karen, Wang, Hui (Submitted). Detecting Market Manipulation with Dual-branch Self-supervised Learning: A Unified Framework Integrating Frequency-informed Anomaly Synthesis and Domain-Specific Features. Submitted to Information Processing and Management. Manuscript IPM-D-25-06138.
• Hannon, James (Corresponding Author), French, Declan, Quinn, Barry, O’Hagan, Adrian (Submitted). Geospatial modeling of vehicle crime in Northern Ireland using computer vision to identify environmental factors. Submitted to Insurance: Mathematics and Economics. Manuscript IME-D-25-00419.

PhD Supervision Excellence

Completed Supervisions (6):

1. Dr Jiadong Liu (graduated 2018): Momentum in Empirical Asset Pricing (Principal Supervisor).
2. Dr Ashleigh Neil (graduated 2019): Law and Financial Stability (Principal Supervisor).
3. Dr Colm Kelly (graduated 2021): Machine Learning in Empirical Asset Pricing (Principal Supervisor).
4. Veronica Zhang (2024): Capital Policy and State Sponsorship in Chinese Banking (Principal Supervisor).
5. Dr Kevin Johnson (graduated 2019): A Case Study in Industrial Consolidation — The Irish Credit Union Sector (Co-Supervisor).
6. Dr Qiao (Olivia) Peng (graduated 2021): US Credit Union Mergers — Causes and Consequences (Co-Supervisor).

Current Supervisions (6): Including students working on AI applications in finance, sustainable investing, and computational approaches to financial regulation — see cv_grants.qmd for the full current register.

Teaching Excellence

• Programme Director, MSc Quantitative Finance (2018–2022).
• Programme Director, MSc Computational Finance & Trading (2014–2018).
• Co-Founder, Queen’s Student Managed Fund (2012–2024).
• Teaching Award, QUB (2016).

Current Modules: Financial Data Science; Causal AI; AI in Trading; Financial Econometrics.

Academic Service

• Co-founder, Finance and AI Research Lab (with Dr Fearghal Kearney), Queen’s University Belfast (2022–2024).
• Programme Director, MSc Quantitative Finance (2018–2022).
• Lead Developer, Queen’s Business School Remote Analytics Lab Platform.
• Organiser, Symposium on AI and the Future of Financial Regulation (2023).
• Senior Research Fellow (Sabbatical), International Research Centre on Cooperative Finance, HEC Montreal University, Canada (May–September 2018).
• Implementation Team Member, Bloomberg Trading Room, Queen’s University Belfast.
• External Grant Reviewer, UKFin+ (UKRI specialist funded project) — reviewed feasibility grant application (£100K) for financial services innovation research (2024).