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
During this 5-month internship in Switzerland at CALYPS SA, I designed and implemented a patients’ hospital stays automatized codification SaaS to improve operational costs, codification efficiency and reliability.I ran the automatic codification with a classification model I developed and fine-tuned on 30K+ natural language medical notes with 400+ target classes, using state-of-the-art NLP and achieving a 60% accuracy.Finally, I ran the operational implementation of the SaaS for an external client.
Deep Learning, BERT (camembert), Python, PyTorch, MySQL, Team-based project
- Carnegie Mellon University: School of Computer Science, Fall 2020
During the Fall semester, I have been learning about Instructional Design, which is a set of methodologies to develop aligned learning goals, assessment and instruction.
I joined a semester-long research project aiming at providing tools for low-resourced Ivoirian teachers. I extracted valuable insights from a SQL database storing chatbot conversational metadata to refine interaction design and for usage visualization. Python, numpy, seaborn, sqlite
Cognitive Science: Research Intern at ENS, Paris, at the Lab of Cognitive Science and Psycholinguistics, 09/2019 – 01/2020
I ran an observational study on a 30K+ Junior High School student cohort to identify grade repetition's effects on learning. Statistical Analysis, RThank to this research internship, I learned about research methodologies and research studies' design. I gained a strong understanding of research protocols and procedures in an interdisciplinary team.