Meet the Team Powering Quantum AI

Liam brings over 18 years of experience spanning quantitative finance, institutional asset management, and enterprise software. Before founding Y-Predict, he held senior leadership roles at two leading London-based hedge funds, where he oversaw systematic trading desks managing in excess of $2.4 billion in assets. He holds an MBA from London Business School and a BSc in Mathematics from the University of Edinburgh.

Connor is a recognised authority in applied machine learning and distributed systems. With a PhD in Computer Science from Imperial College London, he led engineering teams at two fintech unicorns before joining Y-Predict to architect the Quantum AI engine. He holds 4 patents in algorithmic signal processing and has published research in IEEE Transactions on Neural Networks.

Declan leads our global engineering organisation, overseeing platform reliability, infrastructure, and product delivery. He holds a MEng in Software Engineering from University College Dublin and has 14 years of experience building high-frequency trading systems and real-time data pipelines for Tier 1 investment banks across Europe and Asia.

Rohan brings a data-driven approach to brand growth, user acquisition, and international expansion. With an MSc in Marketing Analytics from the London School of Economics and ten years of experience scaling fintech products across EMEA and APAC, he has led campaigns that collectively generated over 240,000 qualified user registrations across three platforms.

Jason specialises in statistical modelling, time-series analysis, and predictive market algorithms. He holds a PhD in Applied Mathematics from the National University of Singapore and has previously worked at Bloomberg LP and Two Sigma, where he developed factor models used in live trading environments across global equity and crypto markets.

Emily leads fundamental AI research at Y-Predict, focusing on reinforcement learning, neural architecture search, and adaptive trading strategies. She holds a DPhil in Artificial Intelligence from the University of Oxford and has contributed to groundbreaking research published in Nature Machine Intelligence and NeurIPS, with a focus on robust decision-making in non-stationary environments.