Max Zhao
Status: Current Trainee
Biography and Interests
I am a second-year PhD student in the CMS group at Princeton University, being advised by Professor Isobel Ojalvo. My software interests are in python tools statistical tools for high energy physics, such as hypothesis tests and likelihood scans. Despite being the last step of analysis, statistical inference is often computationally intensive and difficult to correctly configure. There is much room to create more user friendly and efficient statistics packages. In terms of physics, I am interested in Higgs decays to Tau leptons because of its additional kinematic information due to parity violating decays. I wish to apply novel analysis techniques such as neural simulation-based inference and effective field theory to create new interpretations of observables and improve sensitivity to BSM physics.
Before starting my PhD, I completed my BA at the University of California, Berkeley. There I worked on novel track reconstruction algorithms with machine learning under the supervision of Professor Heather Gray and was a 2022 IRIS-HEP fellow.
Project
I am developing an update to the hepstats package of the Scikit-HEP ecosystem. The goal is to transform hepstats into a general purpose statistical inference package with compatability to many different model building packages. If achieved, hepstats could be used to reach the publishable results of any analyses irrespective of the frameworks used to build them.
Recent Accomplishments
Mentors
Peter Fackeldey (IRIS-HEP, Princeton), Isobel Ojalvo (Princeton)