Jon Zink

Jon Zink is an accomplished researcher in astrophysics with extensive experience in data science and machine learning. As a Graduate Researcher at UCLA from September 2016 to June 2021, Jon Zink designed a Python algorithm that identified planet signals in contaminated time series data, leading to the discovery of 372 planets. Jon Zink also implemented a random forest regression with TensorFlow, improving star classification accuracy significantly. As a NASA Sagan Postdoctoral Fellow at Caltech from September 2021 to July 2024, Jon Zink utilized K-means clustering and Bayesian hierarchical modeling to enhance measurements and address long-standing planetary formation questions. Currently, Jon Zink serves as a Research Data Scientist at Google, starting in July 2024. Educational qualifications include a Bachelor's degree and a Ph.D. in Astrophysics, both obtained from UCLA.