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Welcome to my GitHub portfolio containing select projects at the intersection of data analytics, environmental science, and geophysics, and reflecting a transition from a research-intensive background in Earth Sciences to applied work in Data Science.

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GitHub Portfolio

Welcome to my GitHub portfolio. These projects reflect a transition from a research-intensive background in Earth and Environmental Sciences to applied work in data analytics and machine learning.

Each project was developed as part of the Udacity Data Analyst Nanodegree or through independent research initiatives. All work includes self-sourced datasets, rigorous data cleaning, and thorough documentation of the analytical process, with attention to reproducibility and clarity.

Projects

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  • Udacity_Advanced_Data_Wrangling
    Explores renewable energy production and consumption trends across U.S. states. Includes a supervised regression model and clustering to identify regional energy resilience patterns.
    Skills: pandas, scikit-learn, matplotlib, data cleaning, ML modeling

  • Udacity_Data_Visualization
    Investigates the solar augmentation potential of fossil power plants across 22 U.S. states. Geospatial analysis and custom visualizations highlight technology-specific and regional trends.
    Skills: pandas, matplotlib, seaborn, GeoPandas, data storytelling

Scientific_Research_Projects

Projects from my academic research career in geophysics and magnetism.

  • Magnetic_Nanoparticles_Granulometry
    Peer-reviewed study (Bondar et al., 2025) on grain size distribution of nanometer-scale titano-magnetite particles using low-temperature frequency-dependent susceptibility and hysteresis data.
    Skills: numpy, pandas, scipy.optimize, scipy.interpolate, scipy.special, matplotlib =======
  • Modeled renewable energy production-consumption dynamics across U.S. states using linear regression and clustering.
  • Applied supervised ML to impute missing data and uncover regional trends in energy resilience.
  • Conducted geospatial analysis on solar augmentation potential of fossil fuel power plants across 22 U.S. states.
  • Created visualizations to identify high-value targets for solar retrofitting, by energy type and state.

All projects demonstrate a full pipeline: data acquisition, wrangling, EDA, analysis/modeling, and communication of insights.

Tools & Skills

Python · Pandas · NumPy · Matplotlib · Seaborn · Scikit-learn · GeoPandas · Jupyter Notebooks

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About Me

I’m Dario Bilardello, a geophysicist with 15+ years of scientific research experience, now focused on applying data science skills to environmental, energy, and public sector challenges. My work emphasizes clarity, collaboration, and robust analytics. If you want to know more or collaborate, feel free to reach out.

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Welcome to my GitHub portfolio containing select projects at the intersection of data analytics, environmental science, and geophysics, and reflecting a transition from a research-intensive background in Earth Sciences to applied work in Data Science.

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