Tomaso Aste

Tomaso Aste is a Professor of Complexity Science at the Department of Computer Science, University College London (UCL). He founded the Financial Computing and Analytics group and co-founded the UCL Centre for Blockchain Technologies. His work bridges complex systems, data science, and finance, with applications in blockchain, fintech, and market modeling.

• Education: PhD in Physics (Politecnico di Milano, 1994); Laurea in Physics (University of Genoa, 1990)
• Prior Appointments: Reader at University of Kent's School of Physics; Associate Professor at Australian National University's Applied Mathematics

His research focuses on data-driven modeling of complex systems, particularly financial systems, complex networks, and statistical physics. He has pioneered information filtering networks and topological machine learning methods for financial applications, including portfolio optimization, risk assessment, and cryptocurrency analysis.

Recent publications highlight his expertise in financial time-series analysis, blockchain technology, and AI-driven modeling. Articles explore topics like limit order books, cryptocurrency market fragility, and topological neural networks. His work has influenced regulatory technology (RegTech) frameworks and digital economy strategies.

Scientific Awards:

• Marie Curie Individual Fellowship
• University of Genoa graduate study specialization Fellowship
• Bacheflor Boncompagni-Ludovisi Foundation Fellowship

Awarded fellowships from European Commission and academic foundations support his interdisciplinary research. He has held editorial roles at journals like Philosophical Magazine and Granular Matter, and contributed to professional societies including American Physical Society and Australian Research Council panels.

Teaching & Academic Leadership:

• Co-created four UCL Master's programs: Financial Risk Management, Computational Finance, Financial Technologies, Emerging Digital Technologies
• Coordinates executive training on AI, blockchain, fintech, and regtech for regulators and private firms
• Teaches graduate-level courses in Data-Driven Modeling, Data Science, and Advanced AI