Tomas McInerney

Tomas McInerney serves as a Lecturer at Queen's University Belfast's School of Law, actively supervising PhD candidates (2024 intake) while bridging legal theory, artificial intelligence, and neuroscience. His scholarship critically examines algorithmic systems' impact on justice frameworks through empirical and theoretical lenses since completing his doctoral research.

Education:

• PhD in Law, Queen's University Belfast (2024)

Research centers on AI-law intersections with emphases on judicial automation, epistemic injustice, and neuroscientific foundations of legal decision-making. His fingerprint analysis reveals 100% concentration in Decision-Making Neuroscience and Psychology, demonstrating how cognitive processes shape algorithmic justice outcomes. Current investigations focus on generative AI's disruptive potential in courts and regulatory responses to automated bias.

Recent publications (2024-2025) form a cohesive critique of AI in justice systems, analyzing epistemic injustice construction, regulatory gaps in automated decision-making, and human-AI collaboration boundaries. His work consistently connects technical AI capabilities (Reinforcement Learning, LLMs) with fundamental legal principles through interdisciplinary frameworks.

Awards:

• Leverhulme Interdisciplinary Network on Cybersecurity and Society (LINCS) scholarship (2020)

As an active PhD supervisor accepting new candidates, McInerney leverages LINCS network resources and Queen's Crucible Programme development opportunities. His LINCS scholarship catalyzed early-career research on cybersecurity-society interfaces while current engagements suggest emerging grant activity in AI-justice system funding streams.

McInerney operates within Queen's University Belfast's interdisciplinary ecosystem through LINCS affiliation and Crucible Programme participation, collaborating across law, computer science, and neuroscience domains. His upcoming presentations on 'Generative AI Judges' indicate expanding leadership in technology-law convergence spaces.