MSc Data Science, Machine Learning and Statistics — Uppsala University, Sweden
GitHub: github.com/tbimbatoMSc in Data Science at Uppsala. Architecture degree at IUAV Venice, five years of practice before switching fields.
Interested in how data science can model systems that have a physical reality, medical and health data, acoustic spaces, complex environments. Currently working on acoustic scene classification and machine learning and signal processing. Self-taught in DSP: Max/MSP, gen~, audio modelling.
Still figuring out where these things connect.
Outside: trail running, hiking, gardening.
| Uppsala University, Sweden —
MSc Data Science, Machine Learning and Statistics (2025 - 2027)
Machine learning · statistics · time series analysis · deep learning · data engineering (Hadoop, Spark) ·
combinatorial optimization (MiniZinc) · software engineering · scientific computing
| University of Verona, Italy —
Coursework in Computer Science and Data Science (2023 - 2025)
Statistical learning · probability · databases · mathematical logic ·
computer architecture & assembly · C · SystemVerilog · FPGA prototyping · algorithms and data structures
| IUAV University of Venice, Italy — BA Architecture (2020)
| 2026 Acoustic Space Classification: ML Benchmarking vs. Neural Baselines —
Ongoing project applying classical machine learning to acoustic environment classification.
Systematic benchmark of lightweight ML classifiers against state-of-the-art neural network systems,
with the goal of establishing a computationally efficient, standardised pipeline for acoustic space
recognition.
| (in progress)
| 2026 Helsinki Urban Noise Analysis: Hourly LAeq Time-Series Modelling —
Comprehensive SARIMA analysis of hourly equivalent sound pressure level (LAeq) measurements from
a Helsinki urban sensor. Stationarity testing (ADF/KPSS), seasonal differencing,
ACF/PACF-guided model identification. Performed model diagnostics (residual analysis, Ljung-Box test) and
forecasting evaluation.
| [Repository]
| 2025 Diabetes Classifier: EDA, Benchmarking &
Interactive Prediction —
End-to-end ML pipeline on a clinical diabetes dataset (blood markers:
HbA1c, BMI, lipid panel, renal indicators).
Physiologically-motivated outlier detection, unit inconsistency discovery
(VLDL mg/dL vs mmol/L), benchmark of four classifiers on balanced and
imbalanced splits. Streamlit dashboard with interactive patient input,
confidence scoring, and cross-model comparison.
| [Repository]
| Nov 2025 — 1st place, AWS Immersion Day Hackathon — Stockholm
| Nov 2025 — 3rd place, Lovable x UUAIS Hackathon Night — Uppsala
| 2026 Deep Learning — Informal Notes (PDF) —
Informal notes on deep learning.
| [PDF Link]
| 2024 Probability Theory Handbook & Formula Sheet —
Reference handbook and formula sheets.
| [Repository]
| [Handbook PDF]
| 2018 — Mentioned in IQD n. 53 (Singolarità) and cited in
Lampedusa: La Cattedrale di Solomon — Vol. II
as student-contributor to a project with Arch. Renato Rizzi.
| [ResearchGate]
| 2015 — Co-designed Nothing Personal — exhibition at IUAV's Ex Cotonificio combining spatial layout and immersive audiovisual experience. Extended beyond its initial run due to public and academic reception. Team of six.