Anomaly detection with SOFIE - Digging the tiniest signals at the LHC

by Juan Antonio Aguilar Saavedra (IFT UAM-CSIC)

Friday 21 Jan 2022, 12:00 → 14:00 Europe/Brussels

Universe

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      Meeting ID: 629 9339 7552
      Passcode: 518909

 

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[ABSTRACT]

 

With the boom of machine learning, anomaly detection methods are gaining traction as a tool to test at the LHC the ample variety of new physics models proposed up to date, and those still not imagined. SOFIE is a novel concept in anomaly detection, joining the best features of supervised methods with the model independence of unsupervised ones, whose performance largely improves over purely unsupervised tools .

 

 

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[SPEAKER]

Dr. Juan Antonio Aguilar Saavedra defended his PhD at Universidad de Granada in 2000. Postdoc at IST Lisboa from 2001 to 2006 and Ramón y Cajal at UGR from 2006 to 2010. Profesor Titular UGR 2010-2021. Dr. Aguilar currently works at IFT (CSIC) where he got his position as Científico Titular in 2021.

Seminario Red LHC - Anomaly Detection with SOFIE - JA Aguilar.pdf Seminario Red LHC - Anomaly Detection with SOFIE - JA Aguilar.png SOFIE.pdf Video-JATalk.mp4