About

Michaël Karpe is Machine Learning Scientist at Next Gate Tech, a Luxembourg-based FinTech scaleup providing Data Management as a Service for the financial industry. He has 5 years of experience in Machine Learning Science & Engineering and Quantitative Research & Development, working with global financial services companies and scaleups.

Michaël Karpe studied Applied Mathematics & Computer Science, including Machine Learning, Computer Vision, Operations Research, and Financial Engineering. He received a Master of Engineering from the University of California, Berkeley, and a Master of Science from the École des Ponts ParisTech.

Michaël Karpe is passionate about real-world applications of Machine Learning, having won a Kaggle Analytics competition in 2020. He is also a fervent public speaker and debater, having reached the semifinals of the French Debating Association tournament in 2018.

Interests
  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Algorithmic Trading
  • Public Speaking
Education
  • MEng in Industrial Engineering & Operations Research - FinTech Concentration

    University of California, Berkeley

  • MSc in Applied Mathematics & Computer Science - Machine Learning & Computer Vision Concentration

    Ecole des Ponts ParisTech, France

  • Classe Préparatoire in Mathematics and Physics

    Aux Lazaristes, Lyon, France

Machine Learning Projects

Optimization Projects

Quantitative Finance Projects

Covariance estimation by sparse method
Identifying clusters of correlated variables