Mathieu Molina
About Mathieu Molina
Mathieu Molina is a research intern specializing in privacy, fairness, and healthcare within artificial intelligence. He has a diverse educational background and extensive experience in research and internships across various prestigious institutions.
Work at Inria
Mathieu Molina has been working as a Research Intern at Inria since 2021. His role focuses on the intersection of privacy, fairness, and healthcare within the field of artificial intelligence. In this position, he conducts research that investigates the trade-offs between different notions of fairness in machine learning models. His work emphasizes the theoretical aspects of artificial intelligence, aiming to enhance the understanding and effectiveness of fair classifiers.
Education and Expertise
Mathieu Molina holds a Master's Degree in Science and Executive Engineering from MINES ParisTech, where he studied Spatial Statistics and Applied Probability from 2017 to 2021. He also obtained a Master's degree in Artificial Intelligence from PSL Research University in 2021. His academic background includes studies in science at Lycée Louis-le-Grand, Lycée Janson-de-Sailly, and Lycée Henri IV, culminating in a High School Diploma. His expertise lies in the theoretical study of fair classifiers, particularly in high-dimensional protected attributes.
Background
Mathieu Molina has a diverse background that includes international experience. He was a foreign exchange student at Tokyo Institute of Technology from 2018 to 2019. Prior to his current role, he completed internships at various organizations, including a Manual Work internship at HERMES SELLIER in 2018, a Program Manager Intern position at Amazon in 2020, and a Research Intern role at Harvard University from 2019 to 2020.
Research Focus
Molina's research primarily revolves around the trade-offs between fairness and utility in machine learning. He utilizes tools such as Keras, ScikitLearn, and Pandas in his research work. His focus on the theoretical aspects of artificial intelligence aims to contribute to the development of fair classifiers, which are essential for ensuring equity in AI applications, particularly in healthcare.