Julian Glatzer

Julian Glatzer is data and software engineer with a focus on data-intensive software development. In the past he worked as a physicist with a focus on the analysis of petabyte-size datasets and the development of new prototypes at CERN's Large Hadron Collider. During his work at ATLAS he became an expert in data analysis, including machine learning methods and distributed computing resources (cloud and grid computing). Julian primarily works with Java and has experience with Python and C++. He has a special interest in mathematical and statistical modelling.

Julian is motivated by new challenges and enjoys to familiarize himself with novel technical topics. He appreciates the work in teams that are both diverse culturally and from the professional background of the members.

Curriculum Vitae


Data and Software Engineer at Nexthink SA
Since 07/19
  • Developed data-taking infrastructure using Java microservices on Kubernetes, Kafka, Clickhouse and others
Associate Member of Personnel at CERN, European Organization for Nuclear Research (CH)
11/08 - 07/19
  • Developed algorithms for the analysis of the petabyte-size data from proton collisions in the ATLAS Experiment at the Large Hadron Collider (LHC)
  • Research on application of machine learning techniques for the local and cloud-based data analysis
  • Major contributor to the operation of the experiment, prototyped new detector parts for upgrade
  • More than 800 publications in renowned scientific journals
Marie Sklodowska-Curie Fellow at Universitat Autònoma de Barcelona (ES)
07/16 - 07/19
  • Fellow of the Horizon 2020 COFUND programme of the European Union
  • Developed a search for new Higgs bosons (C++ and Python, executed locally and on the Worldwide LHC computing grid), research on classification of events using machine learning, leader of the research group
  • Coordinated 30 engineers, physicists and the 24x7 shift crew working on the collision data-taking with the ATLAS Tile Calorimeter
Postdoctoral Researcher at Albert-Ludwigs-Universität Freiburg (DE)
02/16 - 06/16
  • Developed framework for statistical data analysis and machine learning methods for the classification of Higgs boson production and background
  • Lead research group of two postdocs, a Ph.D. and a M.Sc. student
Research Fellow at CERN, European Organization for Nuclear Research (CH)
10/13 - 12/15
  • Extracted the fraction of top quark events with additional b-quarks using a multidimensional fit to collision data and statistical analysis of the results
  • Commissioned new prototype for hardware real-time data acquisition system, wrote the software for the control of the FPGA-based event filter in multi-threaded C++ and a web-based monitoring suite with a strong focus on testing and validation to ensure stability and high availabilitylist


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