Ryan Humble
Graduate Student Machine Learning
Research
Ryan is a PhD student at Stanford’s Institute for Computational and Mathematical Engineering, collaborating with Daniel Ratner and Finn O’Shea in the SLAC ML Initiative. He works on several anomaly detection projects related to LCLS, including an automated operator-assisting method for RF-station fault identification and a novel deep unsupervised anomaly detection algorithm for general LCLS beamline anomalies.
Education
2016: B.Sc., Mechanical Engineering and Applied Mathematics, Yale University, New Haven, CT, USA
