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Rossi Stefano

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Physics and Statistics

Physics and Statistics

Rossi Stefano
skills
  • Mathematics
  • Physics
  • Statistics
  • Physics and Statistics

    At the heart of every intelligent algorithm lies the language of physics and statistics. These foundational sciences provide the tools to understand data, model uncertainty, and distinguish meaningful patterns from random noise. This quantitative foundation allows me to build models that are not only accurate but also interpretable, robust, and grounded in first principles.

    Key Technologies & Frameworks

    NumPy: The fundamental library for numerical and scientific computing in Python, providing the building blocks for nearly all data analysis.

    Pandas: The essential data manipulation and analysis library, offering powerful data structures like DataFrames to clean, transform, and explore datasets.

    R: Tools for rigorous statistical modeling, hypothesis testing, and exploring the relationships within data.

    Visualization Libraries: Matplotlib, Seaborn, Plotly For creating insightful and interactive visualizations to communicate findings and understand model behavior.

    EDA (Exploratory Data Analysis): Techniques for summarizing the main characteristics of datasets, often using visual methods to uncover patterns, spot anomalies, and test hypotheses.

    Key Projects

    Statystical Data Analysis: A project made in R and Shyny. This is an interactive web application that demonstrates the power of statistical techniques in understanding complex statistical methodologies. It includes inferential statistics, regression analysis, and hypothesis testing and more, showcasing how to derive insights from data.

    Comprehensive EDA: A detailed exploratory data analysis project that demonstrates the power of statistical techniques in understanding complex datasets. It includes visualizations, summary statistics, and insights derived from real-world data.

    Time Series Prediction: A project focused on analyzing temporal data, applying statistical methods to forecast future trends and understand seasonal patterns. It showcases the application of statistical models to real-world time series data.

    VR Haptics Suite: This is an implementation of VR framework for eventdrive project with Unity which is not my area of expertize. Still, is relevant to mention it here as it uses physics and statistics to simulate haptic feedback in virtual reality environments.