I am working on high-energy experimental particle physics in the ATLAS experiment.
ATLAS is a huge particle detector that is installed 100 m underground in the Geneva area in Switzerland. It records data from proton-proton collisions delivered by the Large Hadron Collider (LHC). Our goal is to study the interactions between elementary particles of the Standard Model, and look for new phenomena.

One of my main research fields is the search for Supersymmetry. It is a theoretical model that postulates the existence a super-partner for each Standard Model particle, with a different spin (quantum number). My favourite hunt is the search for squarks and gluinos (partners of the quarks and gluons) in events with jets of hadrons, tau leptons, and missing transverse momentum carried by neutralinos. Taus are similar to electrons, but they are much heavier, and therefore decay shortly after they are produced, leaving specific signatures in our tracking and calorimeter detectors.

I am involved in the ATLAS trigger system which allows the experiment to cope with the enormous proton-proton collision rate (1 collision event every 25 nanoseconds) and reduces the rate at which we record the events to disk for data analysis (about 1 event every millisecond). I am developing software algorithms to detect tau leptons in the trigger system.

I also develop algorithms for reconstructing and identifying tau leptons in the offline reconstruction of recorded data, which is a more detailed reconstruction than what we can afford to run in the trigger due to timing constraints. Most of these algorithms employ machine learning techniques.

ATLAS experiment