CERN/CMS - Computing and Technology Workshop in Vilnius

Europe/Vilnius
Faculty of Mathematics and Informatics Vilnius University Šaltinių g. 1A (Computer Labs) LT-08303 Vilnius Faculty website: <a href="http://mif.vu.lt/lt3/en/">http://mif.vu.lt/lt3/en/</a> Google Maps: <a href="https://goo.gl/maps/c2jzsL4vXXE2">https://goo.gl/maps/c2jzsL4vXXE2</a> OpenStreetMap: <a href="http://osm.org/go/0lP6hLeow?way=203572293">http://osm.org/go/0lP6hLeow?way=203572293</a>
Andrius Bernotas (Lithuanian Academy of Sciences (LT)), Andrius Juodagalvis (Vilnius University (LT)), Aurelijus Rinkevicius (Cornell University (US)), Daniele Bonacorsi (University of Bologna), David Abdurachmanov (University of Nebraska-Lincoln (US)), David Lange (Princeton University (US)), Peter Elmer (Princeton University (US)), Valdas Rapsevicius (Fermi National Accelerator Lab. (US))
Description

Workshop goals: To discuss collaboration opportunities between the Lithuanian / Baltic countries scientific research community and the CERN Compact Muon Solenoid (CMS) experiment in the areas of software engineering, data analytics and detector technologies. CMS is a high-energy collider experiment operating at the Large Hadron Collider (LHC) facility investigating the energy frontier of particle physics research. CMS relies on advanced particle detector technologies as well as extensive software and distributed computing infrastructure. CMS collaborators are investigating a range of detector and computing upgrades in light of a major facility upgrade next decade and an expected 20 year horizon for operations. Workshop presentations will cover research projects in CMS and Lithuania including software engineering for distributed computing and processor technologies, data analytics and high-luminosity LHC detector and software upgrades.

Audience: Professors, students and other researchers from Lithuanian universities, other Baltic countries and Finland (remote connection an option), as well as local industry partners interested in advanced software engineering, data science and computing techniques that may be applied to high-energy physics research.  

Keywords:

  • Machine learning
  • Data analytics
  • FPGA programming
  • Advanced detector development
  • Extremely fast pattern recognition techniques
  • Cloud computing 
  • Low power architectures
  • Multicore software architectures
  • High luminosity LHC (HL-LHC)
  • Big data processing and visualization
  • Workflow management and Expert systems

 

Registration
Registration
Participants
  • Adomas Jelinskas
  • Algimantas Juozapavicius
  • Ališer Haidari
  • Anders Ryd
  • Andrius Bernotas
  • Andrius Juodagalvis
  • Andrius Puzas
  • Antanas Sinica
  • Anton Kuncinas
  • Archana Sharma
  • Arturas Plukis
  • Audrius Mecionis
  • Audronė Jakaitienė
  • Augustas Vaitkevičius
  • Aurelijus Rinkevicius
  • Birutė Gricienė
  • Daniele Bonacorsi
  • Darius Germanas
  • David Abdurachmanov
  • David Lange
  • Dovilė Kuznecovaitė
  • Dovilė Meškauskaitė
  • Džiugas Jagminas
  • Emilis Antanas Rupeika
  • Eugenijus Gaubas
  • Gintautas Tamulaitis
  • Gytautas Balevičius
  • Jelena Tamuliene
  • Jevgenij Pavlov
  • Juozas Vaitkus
  • Juozas Vyšniauskas
  • Laimis Juzeliunas
  • Laimonas Deveikis
  • Mantas Briliauskas
  • Mantas Stankevicius
  • Marijus Ambrozas
  • Monika Venčkauskaitė
  • Rokas Maciulaitis
  • Saidinesh Paka
  • Simonas Draukšas
  • Thomas Gajdosik
  • Tomas Ceponis
  • Tomas Kajokas
  • Tomas Krilavicius
  • Valdas Rapsevicius
  • Vidas Raudonis
  • Virginijus Marcinkevičius
  • Vytautas Barzdaitis
  • Vytautas Rumbauskas