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| Projects | Contact Person | Student | Location |
|---|---|---|---|
| Silicon sensor testing | Su Dong | SLAC | |
| RCE readout developments | SLAC/CERN | ||
b-tagging: studying RNN | Michael Kagan | CERN | |
| b-tagging: studying RNN based double b-tagging | Michael Kagan | CERN | |
| tau tagging with 3D imaging and deep neural networks | Michael Kagan | CERN | |
| Boosted H(->bb)+j: studying signal selection and impact of new physics | Michael Kagan | CERN | |
| hh->4b: study using ML algorithms for selection | Michael Kagan | CERN | |
| Boosted hh->4b study for high luminosity LHC | Michael Kagan | CERN | |
Quark/gluon tagging using deep convolutional neural networks | Francesco Rubbo, Ariel Schwartzman | SLAC | |
Forward pileup jet suppression using deep convolutional neural networks | Francesco Rubbo, Ariel Schwartzman | SLAC | |
New algorithms for primary vertex selection and reconstruction at high luminosity: addressing the challenge of vertex merging using new techniques and a timing detector | Ariel Schwartzman | SLAC | |
| Double b-tagging reconstruction algorithms | Ariel Schwartzman | SLAC | |
Pileup jet suppression algorithms for the calorimeter phase 2 upgrade | Ariel Schwartzman | SLAC | |
Exploring the use of calorimeter timing information to improve the jet energy resolution | Ariel Schwartzman | SLAC | |
| Track-based pileup suppression in the forward region | Ariel Schwartzman | SLAC | |
Neural network anti-kt jet finding for the phase 2 trigger upgrade | Ariel Schwartzman | SLAC | |
Improving the jet energy scale calibration using machine learning techniques | Ariel Schwartzman | SLAC | |
Implementation and study of a new technique for jet pileup mitigation at very high luminosity ("shrinking cone" algorithm) | Ariel Schwartzman | SLAC | |
Study of vertex pointing in Higgs to gamma gamma events at high luminosity | Ariel Schwartzman | SLAC | |
| Search for New Physics in “untriggerable” final states at ATLAS | Francesco Rubbo | SLAC |
Summer 2016 Rotation Project Proposals
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