Research output per year
Research output per year
Personal profile
Biography
Professor Barry Quinn is Professor of Finance & Financial Technology at Ulster University Business School, where he developing the Centre for Financial and Regulatory Technology. He is an applied econometrician and Chartered Statistician whose work integrates econometrics, machine learning, and computational approaches to address challenges in financial markets, risk, and regulatory compliance.
His research combines causal policy analysis, algorithmic trading risk detection, and trustworthy AI methods, with a particular interest in how financial technology can support resilient markets and evidence-based regulation. Barry’s work is collaborative and interdisciplinary, bridging economics, statistics, computer science, and law.
He teaches across quantitative finance, econometrics, and AI applications in finance, encouraging students to engage with rigorous, ethical, and reproducible methods. Pedagogically, he emphasises employability, resilience, and critical thinking.
Before entering academia, Barry worked in financial markets, specialising in currency trading and liquidity management. He holds a PhD in Finance from Queen’s University Belfast, is a Chartered Statistician, and is completing an MSc in Artificial Intelligence. He actively collaborates with industry and policy partners to ensure his research delivers academic, societal, and regulatory impact.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Keywords
- HG Finance
- HA Statistics
- HB Economic Theory
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Modeling and predicting failure in US credit unions
Peng, Q., McKillop, D., Quinn, B. & Liu, K., 4 Jun 2025, In: International Journal of Forecasting. 41, 3, p. 1237-1259 23 p.Research output: Contribution to journal › Article › peer-review
3 Citations (Scopus) -
TDSRL: time series dual self-supervised representation learning for anomaly detection from different perspectives
Dai, Y., Spence, I., Rafferty, K., Quinn, B., Huang, J. & Wang, H., 1 Sept 2025, In: IEEE Internet of Things Journal. 12, 17, p. 35078-35096 19 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile14 Downloads (Pure) -
Evolutionary multi-objective optimisation for large-scale portfolio selection with both random and uncertain returns
Liu, W., Zhang, Y., Liu, K., Quinn, B., Yang, X. & Peng, Q., 1 Jan 2024, In: IEEE Transactions on Evolutionary Computation. 29, 1, p. 76-90 15 p.Research output: Contribution to journal › Article › peer-review
5 Citations (Scopus) -
Lurking in the shadows: The impact of CO2 emissions target setting on carbon pricing in the Kyoto agreement period
Quinn, B., Gallagher, R. & Kuosmanen, T., 1 Feb 2023, In: Energy Economics. p. 1-10 10 p., 106338.Research output: Contribution to journal › Article › peer-review
28 Citations (Scopus) -
Developing a Value-at-Risk Analytics Platform: Theoretical foundations
Quinn, B. & Kearney, F., 12 Dec 2021Research output: Book/Report › Commissioned report