Experimental Particle Physics at Kyung hee University

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People

20210815_profile_jhgoh.jpeg

  • PI: Junghwan Goh (Space21-607, Kyung Hee University / jhgoh -at- khu.ac.kr)
    • 2022-present: Associate professor / Department of Physics, Kyung Hee University
      • 2021-present: Science Information Convergence, Kyung Hee University
      • 2020-present: Department of Big Data Analytics, Kyung Hee University
      • 2018-2022: Assistant professor / Department of Physics, Kyung Hee University
    • 2016-2018: Research Professor at Hanyang University
      • 2017-present CMS RPC Detector Performance Group coordinator, CERN/LHC
      • 2016-2017 CMS RPC Upgrade coordinator (deputy), CERN/LHC
    • 2014-2016: Postdoc at SungKyunKwan University / Korea CMS at CERN
    • 2014: Ph.D Physics at SungKyunKwan University

  • Students (Space21-904, Kyung Hee University)
    • Ph.D: C. Yoo, W. Hwang, J. Shin
    • Master: S. Lee, H. Park, H. Jeong
    • Undergraduate internship: J. Oh
  • Alumni
    • Researcher: R. Rabadan(2021)
    • Undergrad: D. Bae(-2020)
  • Required skills
    • Research: Experimental particle physics, Particle detectors, Machine Learning, Deep Learning
    • Software & computing: C++, python, ROOT, Geant4, numpy, pytorch, tensorflow, CUDA, FPGA, HLS, bash, html, javascript, php
    • System administration: Linux, Grid / HTC, HPC, condor, pbs(torque), kubernetes, docker, singularity

Research topics

  • LHC/CMS experiment
    • Top quark reconstruction using Deep Learning
    • Search for Flavour Changing Neutral Currents
    • RPC detector efficiency measurement, Data quality monitoring
    • RPC software release validation
  • J-Parc/JSNS2 experiment
    • Search for sterile neutrinos at JSNS2 experiment using Machine Learning
    • Pulse shape discrimination using Deep Learning
  • Computing/Deep Learning

Data Analysis Facillities

* Local servers ([[https://hep.khu.ac.kr/monitoring/d/CbKreiMnk/system-overview?orgId=1|Monitoring page]]): * Main server: Xeon Silver 4210R (k8s master & file server & auth.) * High perf nodes: EPYC 7702, EPYC 7302 (Alveo U200 FPGA) * GPU: Ryzen Threadripper 399X (GPUx4), Xeon E5-1650v4 (legacy GPU) * Networking * Kreonet (1G KISTI Seoul - KHU Dept. of Physics) * Internal networks (Dell EMC X4012 12 SFP/10G, HP 1420-24g/1G) * External computing resources * CMS: CERN (lxplus), KISTI GSDC, etc * JSNS: KEK (kekcc) * KISTI supercomputing center


개인정보 처리방침


start.1686641823.txt.gz · Last modified: 2023/06/13 07:37 by Junghwan Goh