Scholar
Giuseppe Masi
Google Scholar ID: WMu-pA8AAAAJ
PhD Student, Sapienza Univeristy of Rome
Citations & Impact
Citations
33
H-index
2
i10-index
2
Publications
6
Co-authors
6
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- - Publications:
- - 'Robust Causal Discovery in Real-World Time Series with Power-Laws'
- - 'Patrolling Heterogeneous Targets with FANETs'
- - 'Lob-based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study'
- - 'On Correlated Stock Market Time Series Generation'
- - 'Stock Shocks Modelling and Forecasting'
- - Projects:
- - PLACy: A robust causal discovery method for stochastic time series leveraging power-law spectral features.
- - LOBCAST: An open-source Python framework for standardizing Stock Price Trend Prediction (SPTP).
- - CoMeTS-GAN: A correlated multivariate time series generative framework based on Conditional Generative Adversarial Networks (C-GANs).
- - Stock Shocks Modelling and Forecasting: Formal definition of stock shocks using Lévy-stable distributions and high-precision forecasting algorithms.
Research Experience
- - AI Scientist, Outsampler, July 2025 - Present, Building conversational agents for time-series in the context of fraud detection and financial reports generation.
Education
- - PhD in Computer Science, Sapienza, University of Rome, 2022 - Present
- - MS in Computer Science, Sapienza, University of Rome, 2020 - 2022, Thesis: 'Adversarial Learning to Rank - Transferable Text-Based Attacks to Black-Box Neural Ranking Models: WARA and WSRA'
- - BS in Computer Science, Tor Vergata, University of Rome, 2017 - 2020, Thesis: 'Diffusion in the Presence of Ambivalent relationships: The Role of the Negative relationships in the complexity of the Problem'
Background
- - Research Interests: Artificial Intelligence for Finance, including generative modeling and causal discovery in time series data
- - Professional Field: Computer Science
- - Introduction: As an AI Scientist at Outsampler, focuses on research and innovation at the intersection of artificial intelligence and finance. Also a dedicated PhD candidate in Computer Science at Sapienza, University of Rome.
Miscellany
- - Skills: C, C++, Java, Python, SQL, Git, (Deep) Machine Learning, PyTorch, Natural Language Processing, Data Visualization, Statistical Analysis
