Summary
Michail Chatzianastasis is a Machine Learning Scientist based in Paris with eight years of experience blending academic research and applied ML, currently building foundation models for multimodal genomic and clinical data at Natera. He completed a PhD in graph representation learning at École Polytechnique under Prof. Michalis Vazirgiannis, and has a track record of translating graph neural network research into biomedical applications, including cancer gene prediction at the Flatiron Institute. His background spans industry and research internships—working on foundation models for biology at InstaDeep and practical ML engineering for energy forecasting and early Alzheimer’s detection—demonstrating an ability to move ideas from prototype to production. Michail’s training in electrical and computer engineering from NTUA and early successes in neural architecture search and operation embeddings reflect a strong blend of theoretical rigor and systems-level pragmatism. Notably, he has repeatedly bridged domains (genomics, clinical data, energy, and NLP), making him adept at designing ML solutions where heterogeneous, multimodal data is the norm.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at École Polytechnique
GPA 19,44/20 (top 1%), GPA 19,44/20 (top 1%) at 3rd Senior High School of Rhodes
Master of Engineering - MEng, Electrical and Computer engineering, Master of Engineering - MEng, Electrical and Computer engineering at National Technical University of Athens