Technical Competencies

• Econometrics as applied statistical science: explicit assumptions, uncertainty quantification, stress-testing
• Financial statistical learning: time-series ML, anomaly detection, decision support for markets and trading
• Causal analysis: causal inference and causal ML for evaluation and decision-making under uncertainty
• Risk analytics: tail risk, stress testing, scenario analysis
• Reproducible data science: ETL, feature engineering, and governance for models used in operational contexts
• Programming: R, Python, statistical software development

Business Applications

• Risk Management: Systemic risk assessment, VaR modeling, stress testing
• Regulatory Compliance: AI-driven compliance solutions, computational approaches to financial regulation
• Trading & Markets: Currency trading, liquidity management, market microstructure
• Strategic Analytics: ESG analytics, performance measurement, scenario analysis

Recent Major Projects

Grant figures below are the full economic costs recorded in the canonical data/Grant_income.csv.

PhD Scholarships — Centre for Finance and Responsible Technology (2025) | £360K, Department of the Economy NI - Three PhD scholarships to establish the Centre for Finance and Responsible Technology. - Two collaborative doctoral partnerships with local firms: Pytillia and Napier AI. - Building research capacity in computational approaches to financial regulation.

AI-Driven Regulatory Compliance (2024–2025) | £100K, UKFin+ / UKRI - Partnership with Funds Axis Ltd developing AI solutions for investment-management compliance. - Reducing regulatory burden through automated compliance monitoring.

ESG Fair-Value Analytics Platform (2022–2023) | £173K, Innovate UK - State-of-the-art financial data science and business analytics for ESG prediction.

Regulatory Technology and Portfolio Analytics (2021–2023) | £173K, Innovate UK - Econometrics and financial machine learning for regulatory and portfolio applications.

AI Retail Analytics (2018–2021) | £165K, Innovate UK KTP - Machine learning and predictive analytics for retail business optimisation with Pearl AI Ltd.

Industry Advisory & Consulting

• Pytillia - Collaborative Doctoral Partnership (PhD scholarship, £120K, 2025)
• Napier AI - Collaborative Doctoral Partnership (PhD scholarship, £120K, 2025)
• Financial Conduct Authority Tech Sprint Mentor (2023-present)
• Citigroup Belfast - Anomaly detection for trading data (2022-2023)
• Multiple industry partnerships - Computational approaches to financial regulation and compliance solutions

Awards & Recognition

• 1st Place - CFA European Quantitative Finance Awards (2018)
• Advanced Data Science Professional - Royal Statistical Society (2023)
• Teaching Fellow - Higher Education Authority (2012)

Research Impact

• 14 peer-reviewed publications in top-tier finance and technology journals
• ~£1.18M in direct research awards as PI or Co-I across 13 projects, from Department of the Economy NI, Innovate UK, UKFin+/UKRI, and industry partners, with additional industry co-funding through KTPs and collaborative doctoral partnerships
• International recognition — invited speaker at major finance conferences

Leadership & Innovation

• Director - Centre for Finance and Responsible Technology (2024-present)
• Co-founder - Queen’s Student Managed Fund (managing real investment portfolio)
• Programme Director - MSc Quantitative Finance (2018-2022)

Working Papers (Selected)

• 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.
• Quinn, Barry (2025). Hierarchical Flag Classification through Economic Domain Knowledge: A Vision Transformer Approach for Cultural Symbol Recognition. MSc thesis and reproducible research codebase (economic-flag-classification), Queen’s University Belfast; manuscript for journal submission in preparation.

Immediate Impact Areas

1. AI-Driven Risk Management: Leverage cutting-edge ML for enhanced risk analytics
2. Computational Approaches to Financial Regulation: Develop data-driven compliance and monitoring solutions using advanced statistical and machine learning methods
   
3. Market Intelligence: Apply advanced analytics to trading and investment strategies
4. Strategic Innovation: Bridge academic research with practical business applications

Unique Differentiators

• Proven Industry Track Record: Real trading floor experience combined with academic rigor
• Research-to-Practice Pipeline: Translate cutting-edge research into business solutions
• Regulatory Expertise: Deep understanding of financial regulation and compliance
• Technology Leadership: At forefront of AI/ML applications in finance

Available for: Board positions, strategic consulting, research partnerships, executive roles in financial technology and computational approaches to financial regulation

References and detailed project portfolios available upon request