Scholar
Michail Chatzianastasis
Google Scholar ID: e0HbE2YAAAAJ
Natera
Citations & Impact
Citations
317
H-index
8
i10-index
7
Publications
20
Co-authors
10
list available
Publications
Resume (English only)
Academic Achievements
- Publications: Including but not limited to 'Prot2Text-V2: Protein Function Prediction with Multimodal Contrastive Alignment' (NeurIPS 2025), 'Explainable Multilayer Graph Neural Network for Cancer Gene Prediction' (Bioinformatics, 2023), etc.; Papers accepted at several international conferences such as AAAI 2024, NeurIPS 2023, ICANN 2023, etc.
Research Experience
- ML Research Scientist at Natera since September 2025; Research Internship at InstaDeep from June 2024 to 2025, working on GNNs and LLMs for genomics; Summer internship at Flatiron Institute, Simons Foundation in New York during 2022, working on the application of graph neural networks for cancer gene prediction, guided by Dr. Zijun Frank Zhang; Participated in multiple research projects and successfully completed Google Summer of Code 2019.
Education
- PhD: École Polytechnique, Data Science and Mining Team, supervised by Prof. Michalis Vazirgiannis; BSc: National Technical University of Athens (NTUA), School of Electrical and Computer Engineering, worked as a Machine Learning Researcher at the Laboratory of Algebraic and Geometric Algorithms, National and Kapodistrian University of Athens, supervised by Prof. Ioannis Emiris.
Background
- Research Interests: Machine learning, graph representation learning, and foundation models for biology. Focused on developing methods that combine structured, multimodal, and generative approaches to better model complex biological systems. Works as a Machine Learning Research Scientist at Natera, focusing on developing genomic large language models (LLMs) for clinical applications and designing deep learning methods for neoantigen prediction in cancer immunotherapy.
Miscellany
- Personal interests and experiences not detailed.
