I lead several research initiatives in machine learning for particle physics and astrophysics. Additionally, some group members contribute to open source machine learning software development.
Research opportunities
Student involvement in research is one of my research and education priorities. If you are looking for a PhD position in high-energy physics and machine learning or machine learning and astrophysics, please get in touch with me by email about possible opportunities. If you are an MS or an undergraduate 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 research projects. If you are interested in any of the current GSoC projects, please reach out via the GSoC program.
Research group news
Dr. Davide di Croce started in August 2020 as a postdoctoral research associate in our group. Dr. di Croce works on the development of machine learning methods for detector reconstruction and their integration into CMS Software Framework and the development of new physics analyses based on these methods.
A number of students have joined the group in the areas of end-to-end deep learning for particle physics, CMS physics analysis, ML for fast simulation, quantum machine learning and deep learning applications to strong gravitational lensing.
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, co-advised by Manfred Paulini.
Current research group and activities:
Davide di Croce Postdoc at UA Rare Higgs Decays, End-to-end reconstruction
Emanuele Usai Postdoc at Brown (M. Narain) End-to-end deep learning subgroup
Sitong An CERN fellow (co-advised with M. Paulini and L. Moneta) Graph Neural Networks for HGCAL and Fast Simulation
Ana Maria Slivar Doctoral student at University of Alabama End-to-end deep learning subgroup
Michael Andrews Doctoral student at Carnegie Mellon (M. Paulini) End-to-end deep learning subgroup
Bjorn Burkle Doctoral student at Brown University (U. Heinz) End-to-end deep learning subgroup
Hanna Parul Doctoral student at University of Alabama DeepLense subgroup
Michael Toomey Doctoral student at Brown University (S. Alexander) DeepLense subgroup
Suzanne Rozenzweig Doctoral student at University of Florida (J. Konigsberg) Machine Learning for Exotic Higgs Searches
Ali Hariri Masters student at American University of Beirut Falcon Project
Pranath Reddy Masters student at Bits Pilani DeepLense Subgroup
Ryker von Klar Undergraduate student at University of Alabama DeepLense subgroup
Anthony Filoromo Undergraduate student at University of Alabama Machine Learning
Asit Singh Undergraduate student at University of Alabama DeepLense subgroup
Nikolas Pervan Undergraduate student at Brown University End-to-end deep learning subgroup
Shravan Chaudhari Undergraduate student at Bits Pilani End-to-end deep learning subgroup
Prateek Kumar Undergraduate student IIT Delhi Machine learning for L1Trigger
John Blue Undergraduate student at Davidson College (M. Kutchera) Falcon Project
Darya Dyachkova Undergraduate student at Minerva Schools KGI End-to-end deep learning, Falcon Project
Raphael Koh Undergraduate student at University of Waterloo QMLHEP project
Current and Past Google Summer of Code Projects (ML4SCI Umbrella Organization Founder/Org Admin/Mentor 2021-present; CERN-HSF Umbrella Organization Founder/Org Admin/Mentor 2016 – present):
Graph Neural Networks for End-to-End Particle Identification with the CMS Experiment
End-to-End Deep Learning Regression for Measurements with the CMS Experiment
End-to-End Deep Learning Reconstruction for CMS Experiment
On the potential of graph-based models in High Energy Physics
Normalizing Flows for Fast Detector Simulation
Domain Adaptation for Decoding Dark Matter with Strong Gravitational Lensing
Equivariant Neural Networks for Dark Matter Morphology with Strong Gravitational Lensing
Direct Objective Function for Anomaly Detection
Quantum Convolutional Neural Networks for High Energy Physics Analysis at the LHC
Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System
Machine Learning Model for the Albedo of Mercury
Machine Learning Model for the Planetary Albedo
Background Estimation with Neural Autoregressive Flows
Dimensionality Reduction for Studying Diffuse Circumgalactic Medium
Cosmic-Ray Imaging Studies via Mission-Imagery from Space (CRISMIS)
Pre-processing and feature engineering in TMVA
IRIS-HEP Fellowship Project(s):
- Graph Generative Models for Fast Detector Simulations in Particle Physics (2021)
- Accelerating End-to-End Deep Learning Reconstruction using Graph Neural Networks (2021)
Past members of the research group:
Omar Zapata Mesa Undergraduate U of Antiochia CERN Junior Fellow
Engin Eren (masters) PhD from University of Hamburg 2018 DESY Fellow
Andrew Carnes (doctoral) PhD from University of Florida 2018 Data Science
Miles Wu (undergrad) PhD from University of Chicago 2017 Data Science/Industry
Jason Terry (undergrad) Undergraduate Brown University UGA PhD student
Lucas Kang (undergrad) Undergraduate Brown University JHU PhD student
Simon Pfreundshuh (masters) MS student Chalmers Chalmers PhD student
Selim Hotinli (masters) MS student at Bogazici University Imperial PhD student
Sinan Kefeli (masters) Undergraduate student at Bogazici University Caltech PhD student
