Nicolas Knudde is a physics engineer with a focus on computational physics with a PhD in machine learning where he identified novel applications of specialized machine learning and statistical models, more specifically Gaussian Processes, and delivered practical machine learning solutions in many industry-driven projects. He has demonstrated experience in bringing machine learning models in production systems and has experience working in a multi-cultural and multi-disciplinary environment.

He was elected to prestigious and competitive internship positions at Amazon and JPMorgan. At Amazon he researched bayesian techniques for use in proprietary market applications, working together with leading experts in the field, such as Professor Neil Lawrence. At JPMorgan Chase & Co he formulated and programmed data-efficient machine learning techniques for sparsely traded products in the Credit QR department, incorporating the expert knowledge of financial experts and traders in intelligent decision-making systems and enabling a real practical impact of machine learning models and advanced statistical analysis by bringing models into production with the team, resulting in 60% of automated trades.

Education

  • PhD Computerscience, Machine Learning – Ghent University
  • Master in Engineering Physics – Ghent University

Key skills

  • Phython, TensorFlow, sklearn, MATLAB, linux, git
  • Demonstrated experience in bringing machine learning models in production systems
  • Extensive knowledge of Bayesian modeling via PhD studies with top publications
  • Expert in machine learning and statistical analysis with a solid academic education