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General Information

Full Name Alessio Brini
Email alessiobrini@gmail.com / alessio.brini@duke.edu
Phone +1 (919) 904-5994
Links LinkedIn, GitHub, Google Scholar, ORCID

Education

  • 2018–2022
    Ph.D. in Mathematical Finance
    Scuola Normale Superiore, Pisa, Italy
  • 2016–2018
    M.Sc. in Quantitative Finance and Risk Management
    Università degli Studi di Firenze, Florence, Italy
    • Thesis: "Beyond the parameters’ estimation burden: a Bayesian framework for option pricing."
  • 2012–2015
    B.Sc. in Business and Economics
    Università degli Studi di Firenze, Florence, Italy

Experience

  • 2024–present
    Executive in Residence
    Duke University, Pratt School of Engineering — DAREC
    • Faculty in FinTech; machine learning and data science for decentralized finance and digital assets
    • Teaching, research, and student mentoring
  • 2022–2024
    Postdoctoral Researcher
    Duke University, Pratt School of Engineering — DAREC
    • Applied supervised, unsupervised, and reinforcement learning to financial challenges in DeFi
    • Taught graduate courses and directed capstone/summer research projects
  • 2018
    Actuarial Analyst
    Milliman (Florence, Remote)
    • Built analytical spreadsheets/databases and reports for financial/insurance projects

Teaching

  • FINTECH 540: Machine Learning for FinTech — Duke University
  • FINTECH/ECE 590: Data Wrangling and Visualization with Python — Duke University
  • FINTECH 502: FinTech Capstones — Duke University
  • FINTECH 520: Introduction to Statistics — Duke University
  • Python for Data Science — University of Florence (2020)

Publications

  • Deep Reinforcement Trading with Predictable Returns — Physica A
  • Reinforcement Learning Policy Recommendation for Interbank Network Stability — Journal of Financial Stability
  • Assessing the resiliency of investors against cryptocurrency market crashes through the leverage effect — Economics Letters
  • A Comparison-Based Study of Cryptocurrency Volatility — Financial Innovation
  • Tree-Based Cryptocurrency Option Pricing — Economic Modelling
  • SpotV2Net: Multivariate Intraday Spot Volatility Forecasting — International Journal of Forecasting
  • Data-driven Derivative Hedging with Quadratic Variation Penalty — ICAIF’24 Proceedings
  • Modeling and Simulating a Startup Ecosystem Development — Soft Computing

Working Papers

  • A Machine Learning Approach to Forecasting Honey Production with Tree-Based Methods (with Elisa Giovannini and Elia Smaniotto), arXiv:2304.01215, submitted to Applied Soft Computing
  • On Deep Reinforcement Learning for Dynamic Trading with PPO: Challenges and Future Directions (with Petter Kolm), submitted to Journal of Financial Data Science
  • Honey-at-Risk: A study to quantify honey production risk in Italy (with G.V. Lombardi, M.E. Mancino, E. Smaniotto, G. Toscano), SSRN 4562432 (2023)
  • Empirical Evaluation of Machine Learning Models for Option Pricing (with David Hsieh, Patrick Kuiper, Sean Mouseghian, David Ye), arXiv:2506.17511 (2025)
  • Improving DeFi Accessibility through Efficient Liquidity Provisioning with Deep Reinforcement Learning (with Haonan Xu), arXiv:2501.07508 (2025)

Academic Interests

  • Machine Learning applications in Finance and Economics
  • Decentralized Finance (DeFi) and Digital Assets
  • Reinforcement Learning for Trading, Liquidity Provision, and Market Design
  • Forecasting and Risk Management (time series, volatility, honey-at-risk)
  • Graph Neural Networks and network models for financial systems

Grants

  • Co-Investigator — “Risk Management in Times of Unprecedented Geo-Political Volatility: A Machine-Learning Approach”, Institut Europlace de Finance / Institute Louis Bachelier (≈ €10k)
  • Collaborator — “BEEkeepers Weather Indexed INsurance” project, University of Florence (Italian Ministry of Agricultural; ≈ €600k)

Conferences

  • AAAI Conference (AI for Social Impact), 2025 — Contributed Talk; Best Paper Award
  • ICAIF’24 (ACM International Conference on AI in Finance), 2024 — Poster
  • NBER-NSF Time Series Conference, 2024 — Poster
  • Machine Learning of Dynamic Processes & Time Series Analysis (Pisa), 2020 — Contributed Talk
  • European Financial Mathematics Summer School (Vienna), 2020 — Contributed Talk
  • Eastern European Machine Learning Summer School (Krakow), 2020 — Poster

Professional Activities and Service

  • Admissions and recruitment for Duke FinTech MEng program (2023–ongoing)
  • Organizer — Digital Assets at Duke (DA@D), 2023–2024
  • Referee: Annals of Operations Research; Expert Systems with Applications; Financial Innovation; Finance Research Letters; Scientific Reports; Applied Economics; Journal of Applied Economics; Qeios; Animal Science Journal; AI, Computer Science and Robotics Technology; ICAIF 2024; ECAIF 2024
  • Scientific Committee — Florence-Paris Workshop on Financial Econometrics, 2023