Jonas Landman is a PhD student at IRIF, Université Paris Diderot, under the supervision of Iordanis Kerenidis. He has graduated from Ecole Polytechnique with a degree in electrical engineering and machine learning.
His main research focus is to develop and analyze new quantum algorithms for faster and more accurate application in machine learning. His team develops fundamental tools to cover all aspects of statistical learning (distance estimation, linear algebra, gradient descent, etc.). His first project was a quantum algorithm for reproducing the k-means clustering algorithm. His most recent project is a quantum algorithm to perform Convolution Neural Network. He is interested in other applications in unsupervised learning (Spectral Clustering, ML method for soving partial differential equations) and in near term quantum computing.