Jinzhe Zhang

Jinzhe Zhang is a researcher at Preferred Networks, Inc. since April 2022, specializing in artificial intelligence-driven drug discovery. Prior experience includes a research internship at Microsoft, where work focused on enantioselective catalyst design and the acceleration of density functional theory calculations using neural networks. Jinzhe Zhang served as a junior research associate at RIKEN, contributing to the de novo design of chemical compounds and improving NMR similarity measurement with metric learning and transformers. Earlier roles include a summer internship at Preferred Networks, developing latent space optimization for Variational Autoencoder (VAE) models in drug design, and a position as a machine learning assistant at GE Healthcare, applying deep learning methods to medical image recognition. Jinzhe Zhang holds a PhD in Computational Biology and Medical Sciences from The University of Tokyo, a Diplôme d'ingénieur in Bioinformatics & Modeling from INSA Lyon, a Bachelor's degree in Computer Science and Biology from Université Paris Cité, and completed the first two years of undergraduate study in Bioengineering at Universite de Lorraine.