I'm a data scientist and a learning engineer improving human learning by combining computer science with educational design and learning science

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I implemented several Machine Learning projects in both academic and professional settings, and I'm motivated by improving how people learn thanks to Technology. I am interested in any type of learning, with a preference for language. I specialized in Natural Language Processing algorithms that find themselves useful in all learning contexts (course material, questions/answers, language learning, etc.).

The two masters I graduate from: Master of Science and Engineering (June 2021) from CentraleSupelec, and the Master of Educational Technology and Applied Learning Science (August 2021) of Carnegie Mellon University give me a better understanding of the upsides and limitations of technology applied to learning.

My background in theoretical math and engineering provided me with the relevant skills to improve machine learning algorithms. I then focused on applying these skills to human learning at Carnegie Mellon University, at the intersection of computer science, instructional design and learning science. To illustrate, I designed an online course in Geography following evidence-based e-learning design principles. I worked as a data consultant in a research project at CMU, aiming at empowering low-resource Ivoirian teachers with an accessible chatbot.

I'm excited to apply my skills to improve existing learning solutions or design new ones.


  • Machine Learning Engineer Intern, 03/2020 – 08/2020
  • Carnegie Mellon University: School of Computer Science, Fall 2020
  • Cognitive Science: Research Intern at ENS, Paris, at the Lab of Cognitive Science and Psycholinguistics, 09/2019 – 01/2020