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Dr. Nathan Daniel Lee

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Max Delbrück Center

© Lee

Dr. Nathan Daniel Lee

Dr. Nathan Daniel Lee applied his PhD in mathematics at the University of Washington, with experience in computational biology, data science, and high-performance computing. His research uses computational and mathematical models to study cancer evolution. During his PhD, he also worked with a team of bioinformaticians, physicians, and research scientists at the Fred Hutch Cancer Center to integrate these models into a molecular diagnostics software tool for use by oncologists. 

He has a strong background in programming and data science. While pursuing his research, he made extensive use of parallel/high-performance computing, developed optimization algorithms and Monte Carlo simulations, and analyzed various types of genomics datasets. During his PhD he had the unique opportunity to serve as his department's system administrator, where he managed the department's computing resources for research and teaching, which included its computing servers. He also obtained grants to upgrade the GPUs on these servers to current state-of-the-art hardware for deep learning and computational neuroscience.

Bridget Ratcliffe, Sergey Khoperskov, Nathan Lee, Ivan Minchev, Paola Di Matteo, Glenn van de Ven, Misha Haywood, Léa Marques, John Paul Bernaldez, Davor Krajnović, Matthias Steinmetz

Rediscovering the Milky Way with an orbit superposition approach and APOGEE data V. The disc growth and history of star formation

September 02, 2025
https://doi.org/10.48550/arXiv.2509.02691

Bridget Ratcliffe, Sergey Khoperskov, Ivan Minchev, Nathan D. Lee, Tobias Buck, Léa Marques, Lucy Lu, Matthias Steinmetz

Evolution of the radial ISM metallicity gradient in the Milky Way disk since redshift ≈ 3

October 22, 2024
https://doi.org/10.48550/arXiv.2410.17326