I lead several research initiatives in applications of machine learning in high-energy physics. Additionally, some group members contribute to open source machine learning software development.
Research group news
Sitong An started in September 2018 as an INSIGHTS Marie-Curie CERN fellow to work on machine learning applications in high-energy physics, and will simultaneously pursue his doctoral studies at Carnegie Mellon University, advised by Manfred Paulini.
Current research group and activities:
Sitong An CERN fellow (co-advised with M. Paulini and L. Moneta) Deep Learning Applications, Graph Networks for HGCAL
Michael Andrews Doctoral student at Carnegie Mellon (M. Paulini) End-to-end deep learning subgroup
Emanuele Usai Postdoctoral researcher at Brown (M. Narain) End-to-end deep learning subgroup
Bjorn Burkle Doctoral student at Brown University (U. Heinz) End-to-end deep learning subgroup
Lucas Kang Undergradutate at Brown University Graph Networks for Particle Physics
Omar Zapata Mesa Undergradutate at University of Antioquia Machine Learning and Software Development
Past members of the research group:
Engin Eren (masters) PhD from University of Hamburg 2018 just graduated
Andrew Carnes (doctoral) PhD from University of Florida 2018 Data Science
Miles Wu (undergrad) PhD from University of Chicago 2017 Data Science/Industry
Simon Pfreundshuh (masters) PhD student at Chalmers Tech current
Sinan Kefeli (masters) Doctoral student at Caltech current
Student involvement in research is one of my research and education priorities. If you are student looking for research opportunities in machine learning and/or particle physics and are interested in my research activities please get it touch with me about possible projects.