Giovanni Norbedo

M.Sc. Student in Data Science & Artificial Intelligence
Curriculum: Foundations of Artificial Intelligence and Machine Learning
Università degli Studi di Trieste (UniTS) · Trieste, Italy
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Abstract

I am a graduate student in the M.Sc. in Data Science and Artificial Intelligence (Curriculum: Foundations of Artificial Intelligence and Machine Learning) at the University of Trieste (UniTS), where I also completed my Bachelor's degree in Artificial Intelligence & Data Analytics. I have a practical background in Full Stack development and Linux, but my real passion lies in the theory. I enjoy using code to explore the math behind artificial intelligence and making complex concepts easier to visualize. Ultimately, my goal is to look inside the "black box" of machine learning and understand the mathematical foundations that make it work.

1. Academic Background

Degree & Program Institution Period
M.Sc. in Data Science & Artificial Intelligence
(Foundations of AI & ML)
Università degli Studi di Trieste (UniTS) 2026 - Present
B.Sc. in Artificial Intelligence & Data Analytics Università degli Studi di Trieste (UniTS) 2023 - 2026
Table 1: Academic background and degrees.

2. Selected Projects

2.1. Hastings-Powell Chaos Simulation

[GitHub Code]

Investigation of deterministic chaos and bifurcation phenomena in a continuous tri-trophic food chain ($X, Y, Z$) governed by the Hastings-Powell ODE system with Holling type II functional responses:

$$\begin{cases} \dot{X} = X\left(1 - \dfrac{X}{K}\right) - \dfrac{a_1 X Y}{1 + b_1 X} - h_X X \\[8pt] \dot{Y} = \dfrac{a_1 X Y}{1 + b_1 X} - \dfrac{a_2 Y Z}{1 + b_2 Y} - d_1 Y \\[8pt] \dot{Z} = \dfrac{a_2 Y Z}{1 + b_2 Y} - d_2 Z \end{cases}$$
Hastings-Powell dynamical system with parameter-dependent predation and linear prey harvesting ($h_X$).

Analyzes strange attractors, Lyapunov exponents, bifurcation cascades under carrying capacity $K$, and chaos suppression via linear prey harvesting ($h_X$).

2.2. TensorForth: Parallel C Interpreter

[GitHub Code]

A stack-based C99 interpreter parallelized with OpenMP multi-threading for native 1D/2D tensor operations and cellular automata (Conway's Game of Life), paired with a companion Python 2D renderer for visual output.

2.3. Minesweeper3D & Constraint Solver

[GitHub Code]

A three-dimensional Minesweeper puzzle engine built in Python/Ursina (with Marco Carmignano), featuring an automated exact solver based on linear integer constraint satisfaction:

$$\bigwedge_{v \in V_{\text{revealed}}} \left( \sum_{u \in \mathcal{N}_{3D}(v)} x_u = k_v \right), \quad x_u \in \{0, 1\}$$
Linear integer constraint satisfaction problem over 3D neighborhood $\mathcal{N}_{3D}(v)$.

3. Coursework & Academic Foundations

Curricular coursework completed at the University of Trieste across theoretical and practical disciplines:

Area Representative Subjects
Math & Stats Mathematical Analysis I & II, Linear Algebra and Geometry, Probability Theory, Statistical Inference, Optimization Algorithms, Numerical Analysis, Abstract Algebra 2, General Topology.
AI & ML Mathematical Methods and Models for AI, Introduction to Machine Learning, Introduction to Artificial Intelligence, Information Theory and Complex Systems, Data Analytics.
CS & Systems Algorithms and Data Structures, Computability, Complexity and Logic, Advanced and Parallel Programming (OpenMP/C), Computer Architecture and Operating Systems, Database Systems.
Table 2: Curricular foundation courses (UniTS).

4. Technical Skills

Domain Technologies & Libraries
Scientific Computing PyTorch, Scikit-Learn, NumPy, SciPy, Gurobi, Z3 SMT Solver, SageMath, Statsmodels
Languages Python, C/C++, MATLAB, R, JavaScript, TypeScript, Dart, SQL, Bash
Systems Linux (Debian, Ubuntu, Arch), Docker, Git/GitHub
Software Development React, Next.js, Node.js, FastAPI, Flask, Django, PostgreSQL, SQLite, Flutter
Typesetting $\mathrm{\LaTeX}$, Markdown, Typst, Jupyter Notebooks, Obsidian
Interests & Learning Lean4, Rust, Haskell
Table 3: Technical skills and computing environments.