Statistics, Data Science, & Machine Learning

Our group is a leader in bridging modern data science approaches to high-energy particle physics and developing sophisticated statistical techniques. Recently, our group has been active in developing machine learning techniques for particle physics and beyond. Below is a collection of our work on the subject.

Much of this work is done in connection to NYU's Center for Data Science and IRIS-HEP. Kyle Cranmer is the Executive Director for the Moore-Sloan Data Science Environment at NYU and leads the Analysis Systems activity in IRIS-HEP. He is also one of the founders of the Machine Learning for Physical Sciences workshop held at NeurIPS in 2017 & 2019.