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heitornolla/README.md

Hey there! I'm Heitor :)

  • 🔭 Information Systems bachelor at UNICAMP.
  • 🌐 RYEP Exchange Student to Coahuila, Mexico 2019/2020.
  • 🌱 Interested in Data Engineering, AI, ML and Computer Vision Research.
  • 😄 Pronouns: he/him.

About Myself:

I'm a researcher and developer working at the intersection of AI, biometrics, and data engineering.

Currently, I'm part of LinkedIn's Central Operations team, where I work with data engineering and analysis. I'm also a researcher at Unicamp, working with deep learning applied to biometric security and human activity recognition data.

Aside from that, I'm always learning and exploring new research areas. I'm interested in topics such as green software, remote sensing, cloud computing, application and web security, cryptography and AI fairness and explainability.

In my profile, you'll find a few of my personal projects, research and some study material which I found helpful. If you think I can help you in any way or are interested in learning more about my experiences, feel free to reach out via LinkedIn.

Professional Experiences

  • Languages: Python, C++
  • AI/ML: PyTorch, Scikit-Learn, OpenCV, LangGraph
  • Data & DevOps: Airflow, dbt, Docker, GitHub Actions, SQL, Pydantic, Poetry
  • Cloud: AWS, Azure

Currently Learning

  • AgenticAI: reasoning patterns, tool calling frameworks and orchestration
  • Security: Web and Application Security
  • Cryptography: FHE & Privacy-preserving AI for biometric systems

Python PyTorch Airflow Docker AWS

Pinned Loading

  1. WebScraping-MercadoLivre WebScraping-MercadoLivre Public

    This project performs Web Scraping on Mercado Livre's website, scraping data related to 5 string basses. It then cleans this data and turns it into a SQL database to be loaded on Streamlit. This ca…

    Python 2 1

  2. Computer-Vision-Studies Computer-Vision-Studies Public

    A lot of useful books, lessons and codes I've studied. All neatly compiled, hoping to save time for other learners :)

    Jupyter Notebook

  3. Sentiment-Analysis-with-Natural-Language-Processing Sentiment-Analysis-with-Natural-Language-Processing Public

    We develop a classification model, which will identify if a customer review was positive or negative. Furthermore, we gather explainability from the model by applying LIME and SHAP.

    Jupyter Notebook

  4. Analysis-of-Voter-Abstention-through-Clustering Analysis-of-Voter-Abstention-through-Clustering Public

    Unsupervised Learning-based analysis on voter abstention data from Brazilian elections. Using clustering techniques, we aim to identify behavioral patterns in abstention reasons across demographic …

    Jupyter Notebook