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A Federated Learning Method for Real-time Emotion State Classification from Multi-modal Streaming

Home Page: https://www.sciencedirect.com/science/article/abs/pii/S104620232200072X

License: MIT License

Python 50.80% Shell 0.35% Jupyter Notebook 48.85%
federated-learning federated-learning-algorithm realtime-framework emotion-recognition realtime-emotion-recognition federated-learning-application data-streaming data-stream-classification

fed-remecs-mqtt's Introduction

Hi 👋 , I'm Arijit Nandi

  • 🧑‍💼 I work as AI researcher at the Big Data and Data Science Unit of Eurecat - Centro Tecnológico de Cataluña, Barcelona, Spain.
  • 🧑🏻‍🎓 Ph.D. (pursuing) in AI at UPC Universitat Politècnica de Catalunya, Barcelona, Spain.
  • 🌱 I’m currently working on Real-time emotion classification from physiological data (EEG, ECG, GSR, etc.) streams in E-Learning. Also developing a Federated Learning-based application for the same.
  • 📚 I’m currently learning: XAI, MLOps.
  • 💬 Ask me about: Federated Learning | Data Streaming | Affective Computing | Docker.
  • 👯 I’m looking to collaborate on Federated learning and its application in real-time emotion recognition |
  • 📫 How to reach me: Email: [email protected]
  • 😄 Pronouns: Aa-rii-jeet
  • ⚡ Fun fact: 1.0


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Tech stack I work with 👇

Web development stack

JavaScript  PHP  Flask  Bootstrap  HTML  CSS  JSON  MySQL 

Languages

Python  C  MATLAB

ML/DL stack

Keras  NumPy Pandas scikit-learn TensorFlow OpenCV scikit-multiflow

Version Control

Git  GitHub


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