Baptiste Ravina

Baptiste Ravina

Alexander von Humboldt Fellow

University of Göttingen

ATLAS Experiment

Particle physics. Machine learning. ATLAS.

I am a Fellow of the Alexander von Humboldt Foundation, hosted by the University of Göttingen. My research focuses on searching for new physics at the Large Hadron Collider with the ATLAS experiment, using precision measurements of the top quark and machine learning tools.

Education
  • PhD in Experimental Particle Physics, 2020

    University of Sheffield (UK)

  • Part III Maths, 2016

    University of Cambridge, DAMTP (UK)

  • BSc in Physics & Philosophy, 2015

    King's College London (UK)

Research interests
  • psychology Machine Learning
  • insights Likelihood-free Inference
  • filter_tilt_shift Anomaly detection
  • blur_on Effective Field Theory
  • equalizer Monte Carlo Generators
Recent activity

Experience

 
 
 
 
 
Alexander von Humboldt Foundation
Research Fellow
Apr 2022 – Present Göttingen (DE)

My research focuses on the electroweak couplings of the top quark: $t\bar{t}Z$, $tZq$, $tWZ$ and $t\bar{t}\gamma$. Besides my contributions to the measurement of these Standard Model processes with the ATLAS experiment, I lead their interpretation in the framework of Effective Field Theory. With colleagues from the CMS collaboration, I am preparing the very first cross-experiment combination of top+X results. I also plan to be involved in the further development of the MadGraph Monte Carlo event generator.

Other responsibilities include:

  • Supervision of BSc and PhD students
  • Leading the ATLAS Top Reconstruction subgroup
 
 
 
 
 
The Royal Society of Edinburgh
Saltire Early Career Fellow
Sep 2021 – Mar 2022 Glasgow (UK)
The focus of my RSE fellowship was on measuring the spin correlations of top quarks in associated production with a $Z$ boson ($t\bar{t}Z$). In my related phenomenological paper, I used Monte Carlo generators to predict this quantum property of top quarks in the Standard Model, highlighted how it differs from the more common $t\bar{t}$ case, and showed how to interpret any deviation from these predictions in the framework of Effective Field Theory.
 
 
 
 
 
University of Glasgow
Post-Doctoral Research Associate
Apr 2020 – Aug 2021 Glasgow (UK)

I led the legacy $t\bar{t}Z$ ATLAS measurement and contributed to the first measurement of the $t\bar{t}$ spin density matrix with the full Run 2 dataset; for both analyses, I developed an extensive Effective Field Theory fitting framework in the Julia language. I was also involved in background estimations for a combination of Dark Matter searches with $t\bar{t}+E_\mathrm{T}^\mathrm{miss}$ signatures, as well as prototyping an auto-encoder for an Anomaly Detection based search for new physics.

Other responsibilities included:

  • Supervision of MSc and PhD students
  • Summarising ATLAS and CMS $t\bar{t}+X$ results for the LHC Top working group
  • Supporting the ATLAS Top group in Monte Carlo generation
  • Acting as ATLAS Trigger online expert and online release coordinator
 
 
 
 
 
The Institute of Physics
Committee Member, High Energy Particle Physics group
Apr 2018 – Apr 2022
  • Funding assistance for UK HEP workshops
  • Organisation of the yearly Astrophysics + HEP conference
  • Liaison with UK students
  • Outreach activities

Meet the team!

Main collaborators

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Caterina Doglioni

University of Manchester

Professor of Particle Physics

Dark Matter, Anomaly detection

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James Howarth

University of Glasgow

University Research Fellow (Royal Society)

Top physics & spin correlations

PhD students

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Ethan Simpson

EFT & spin correlations
(post-doctoral supervision for James Howarth)

BSc students

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Daniel Werner

$tZq$ polarisation

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Ireas Tom Raschke

$t\bar{t}Z$ and $t\bar{t}W$

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Kia-Jung Yang

$t\bar{t}Z$ and $tZq$

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Theresa Reisch

$t\bar{t}$ spin correlations

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Tim Schlömer

$tZq$ EFT

Alumni

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Craig Shewry

EFT & machine learning
MSc 2021-2022

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George Dialektakis

Anomaly detection
CERN / Google Summer of Code 2021

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Hassan Shahid

Anomaly detection
MSc 2021-2022

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Honey Gupta

Anomaly detection
CERN / Google Summer of Code 2020, then Applied Scientist at Amazon

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Marija Vaškevičiūtė

Anomaly detection
MSc 2020–2021, then PhD Glasgow

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Varsha Senthilkumar

Machine learning in SUSY
MSc 2019, then PhD IFIC Valencia

Get in touch