- Searching for evidence of strongly-coupled dark matter from hidden sectors in the forms of semivisible jets, emerging jets, and soft unclustered energy patterns.
- L3 Machine Learning for Simulation (ML4Sim) Convener: organizing projects to use machine learning for detector simulation.
- Developing SONIC (Services for Optimized Network Inference on Coprocessors) for CMSSW.
- Developing graph neural networks for fast and accurate clustering with the High Granularity Calorimeter.
- L2 Offline/Computing Upgrade Software Coordinator and Deputy Release Manager: reviewing code, managing workflows and needs of various subdetector groups, integrating pull requests and building releases.
- Searching for supersymmetry via production of gluinos and squarks with hadronic final states in the 13 TeV data from the LHC. The latest result, using the full Run 2 dataset, is available at arxiv:1908.04722.
- L3 HCAL CMSSW Co-convener: coordinating HCAL software and simulation needs, focusing on the Phase 1 upgrades.
- Developing reconstruction algorithms and software for the High Granularity Calorimeter, focusing on computing performance.
- Supervising studies of the effects of endcap calorimeter radiation damage on physics performance.
Curriculum vitae: PDF, LaTeX
This uses the LaTeX resume class res.cls. Merged .tex files were generated with flatex.
Here are a few highlights from my recent research work on the CMS experiment:
I was selected as an LPC Distinguished Researcher for 2018 and 2019.
I was presented with the CMS Offline & Computing Achievement Award in February 2018 for my work coordinating the Phase 2 upgrade software development.
I was presented with the CMS HCAL Detector Award in April 2017 for my work on the Phase 1 software and radiation damage studies.
I attended the SUSY2016 conference in Melbourne, Australia in July 2016 to present results from the hadronic supersymmetry search.
I began a postdoctoral research position at Fermilab in February 2015.
I defended my PhD thesis on November 5, 2014!