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Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2

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lorenzo-delsignore/README.md

About me

Recently graduated in Computer Science from the Sapienza University of Rome, I am passionate about artificial intelligence and its subfields. I have experience using PyTorch Lightning, Weight & Biases, and Docker.

My research thesis focused on Dynamic Neural Radiance Fields, enabling novel view synthesis for dynamic data. In particular, I implemented a technique which improve these fields. In my university path, I have worked on numerous projects involving 3D objects such as Point Clouds, Meshes, and Implicit shapes.

My core competencies include:

  • 3D Modelling & Geometric Learning
  • Computer Vision
  • Natural Language Processing (NLP)
  • Interpretability & Representation Learning

Education

  • Master's degree in Computer Science (110/110 with honors), May 2024
  • Bachelor's degree in Computer Science, May 2021

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  1. smooth-dnerf smooth-dnerf Public

    My master's research thesis on the application of Lipschitz regularization to dynamic neural radiance fields (NeRFs) for enhancing animation quality.

    Python 1

  2. smooth-interpolation smooth-interpolation Public

    This research focused on the application of Lipschitz regularization to neural implicit fields for improving shape interpolation in computer graphics and 3D modeling.

    Python

  3. pointclouds-search-engine pointclouds-search-engine Public

    A web application acting as a search engine for 3D Point Clouds, utilizing deep learning for shape completion and classification with a constrastive learning approach.

    Jupyter Notebook 3

  4. q-learning-based-routing-protocols q-learning-based-routing-protocols Public

    This research focus on Q-Learning algorithms to optimize routing protocols for N drones deployed in dynamic environments.

    Python 1

  5. loan-approval-prediction loan-approval-prediction Public

    This research aims to automate the loan qualification process using machine learning algorithms.

    Jupyter Notebook

  6. smallgrad smallgrad Public

    Backpropagation from scratch

    Python