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rricc22/README.md

Hi, I'm Riccardo Castellano

MSc AI @ CentraleSupélec | Materials Engineer | TensorFlow Certified Developer


About Me

From the foundry floor to neural networks - I build AI that solves real manufacturing problems.

Spent 3 years at Howmet Aerospace developing gas turbine components, where I saw firsthand how quality issues impact production. Now pursuing MSc AI at CentraleSupélec to bring cutting-edge ML to aerospace manufacturing.

Focusing in materials characterization through deep learning: built YOLO-based systems for steel microstructure classification, CNNs for casting defect detection, and Physics-Informed Neural Networks that solve computational physics problems.

Upcoming: Internship at SAFRAN TECH POLE focusing on microstructure prediction

Franco-Italian | Fluent in 🇮🇹🇫🇷🇬🇧 (TOEIC 910, IELTS 7/9) + 🇪🇸🇯🇵

Looking for: AI/ML opportunities in aerospace, manufacturing, and materials science


Socials

LinkedIn Portfolio Email


Tech Stack

AI/ML Frameworks

Python TensorFlow PyTorch Keras scikit-learn

MLOps & Cloud

Google Cloud Kubernetes Docker

Data Science & Computer Vision

OpenCV Pandas NumPy Plotly

Web Development & Tools

Flask HTML5 CSS3 Jupyter Git


Featured Projects

Developed conditional PINNs solving 2D heat diffusion with 3.21× performance improvement over image-based approaches. Systematic comparison of CNN vs MLP vs PINN architectures.

YOLO-based system for automated Martensite/Pearlite identification in steel samples. Full-stack deployment with Flask.

LSTM & Transfer Learning achieving MAE: 8.94 BPM on physiological time-series data.

Strategic game AI using Alpha-Beta pruning with smart move filtering. Production ready!

Multi-objective optimization for sales territory assignment using NSGA-II and Simulated Annealing.

Formula 1 data analysis and visualization using Python, exploring race strategies and performance metrics.


Certifications

  • TensorFlow Developer Certificate - Google
  • Google ML Engineer Path (8/12 badges completed)
  • Deep Learning Specialization - DeepLearning.AI (Coursera)

GitHub Stats




Current Focus

  • Preparing for internship at SAFRAN TECH POLE (microstructure prediction)
  • Advancing in Google ML Engineer Path
  • Exploring robotics control and physics-guided machine learning
  • Building production-grade ML systems with MLOps best practices

Fun Facts

  • Marathon runner - trained ML models to predict heart rate during runs
  • F1 enthusiast - analyzing race data with Python
  • Studied Japanese with 3-month immersion (100+ hours)
  • Built strategic game AI that beats human players

Profile Views


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  1. SUB_3H_42KM_DL SUB_3H_42KM_DL Public

    Heart Rate Prediction from Activity Data using LSTM & Transfer Learning | Deep Learning Course Project @ CentraleSupélec | MAE: 8.94 BPM

    Jupyter Notebook 1

  2. heat-equation-ml heat-equation-ml Public

    Jupyter Notebook