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Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Shark

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mariotrerotola/README.md

Mario Trerotola

Ph.D. in Artificial Intelligence - Politecnico di Torino

Research Interests

  • Explainable AI (XAI) and rule extraction from black-box models
  • Blockchain forensics and fraud detection
  • Multi-agent systems and market simulation
  • Machine learning for financial applications

Experience

Role Organization Period
CTO Lizard, Furniture as a Service Sep 2025 - Present
Venture Fellow MITdesignX Venice Sep 2025 - Nov 2025
AI Expert CONSOB (Italian Securities and Exchange Commission) Apr 2024 - Oct 2025
Co-Founder and CTO RELLAI (Exor-backed PropTech) Apr 2023 - Sep 2025
Entrepreneur in Residence Vento (Exor Ventures) Jan 2023 - Apr 2023

Education

Degree Institution Period
Ph.D. in Artificial Intelligence Politecnico di Torino, Dept. of Control and Computer Engineering 2022 - present
Visiting Researcher HES-SO Valais-Wallis, Switzerland Oct 2024 - May 2025
M.Sc. in Data Science and Innovation Management Universita degli Studi di Salerno 2021 - 2022
B.Sc. in Economia e Management LUISS Guido Carli 2017 - 2020

Publications

Journal Articles

A profitable trading algorithm for cryptocurrencies using a Neural Network model
M. Parente, L. Rizzuti, M. Trerotola
Expert Systems with Applications, vol. 238, Part A, March 2024
DOI: 10.1016/j.eswa.2023.121806

Conference Papers

AI-Driven Multi-Agent Systems for Automated Regulatory Analysis of Crypto Projects
M. Trerotola, D. Calvaresi
2025 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
DOI: 10.1109/metroxraine66377.2025.11340415

Enhancing Blockchain Transaction Tracking: A Systematic Review of DLT-Based Financial Systems
M. Trerotola, D. Calvaresi
2025 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
DOI: 10.1109/metroxraine66377.2025.11340456

Selected Projects

Repository Description
trace-xai Model-agnostic framework for global explainability via surrogate decision trees
aioagent Lightweight async multi-agent framework for Python
abides-rs Rust-based agent-based market simulator
twilio-openai-bridge Bridge between Twilio and OpenAI Realtime API

Tech Stack

Python - Rust - PyTorch - scikit-learn - Jupyter

Links

Italy

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  1. abides-rs abides-rs Public

    Forked from abides-sim/abides

    Rust-only agent-based market simulator for microstructure research, execution strategy testing, and privacy-preserving federated learning experiments.

    Rust

  2. aioagent aioagent Public

    Lightweight async multi-agent framework for Python. Build multi-agent systems with pure asyncio — no XMPP, no infrastructure, no external dependencies. Features cyclic/periodic/FSM behaviours, FIPA…

    Python 1

  3. AMLSim AMLSim Public

    Forked from IBM/AMLSim

    The AMLSim project is intended to provide a multi-agent based simulator that generates synthetic banking transaction data together with a set of known money laundering patterns - mainly for the pur…

    Python

  4. twilio-openai-bridge twilio-openai-bridge Public

    Production-ready Python bridge between Twilio phone calls and OpenAI Realtime API — with LangChain tools, MCP servers, and multi-tenant routing.

    Python