Siwar Badreddine, PhD

Experience

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  CNSTN (Centre National des Sciences et Technologies Nucléaires )

  Jun 2018 - Jul 2018

  Engineer Internship
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  CEA

  May 2019 - Aug 2019

  Research Internship

  Data analysis (Felix data) taken in 2018 from the Atlas experiment at Cern’s Large Hadron Collider (LHC) for proton collisions.I had recourse to computer science, statistics, signal processingand particle physics in order to test the working performances of LTDB (Liquid ArgonTrigger Digitizer Board) in the electromagnetic calorimeter developed in CEA Saclay incollaboration with international institutes and used for ATLAS experiment in LHC (theworld’s largest and highest-energy particle accelerator).I had multiple data sets from LTDB demonstrator, implemented in the detector to test inreal-time LTDB prototypes. With a lot of analysis and modeling work, I tried to identifyelectronic noise characteristics, check the credibility of physics data and extract functionality problems of the board that need to be considered.Within the framework of the internship, I used statistical techniques to identify types ofproblems found in the data, I used also algorithms to spot anomalous structures whileanalyzing the electronic noise signal, I introduced sorting methods and developed simulationcodes in order to select the interesting data by sorting between real and anomalous events. Show less

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  Inria

  Mar 2020 - Feb 2024

  Project: ERC Synergy EMC2 project at Inria and Sorbonne University.Subject: Low-rank approximation of the high dimensional two-electron integral tensor and its application in quantum chemistry.Description: -Evaluation of the high-dimensional, two-electron integral tensors (fourth-order tensors) that are vital in large-scale applications of accurate electronic-structure methods in quantum chemistry.-Hartree-Fock approximation.-Development of a novel numerical approximation method based on Chebyshev’s interpolation method and Gaussian quadrature rule for numerical integration to get a faster and more accurate solution to the two-electron integrals (six-dimensional integrals).-Compression of the fourth-order tensor by using Low-rank decomposition methods which is useful for electronic structure calculations: truncated singular value decomposition (TSVD), truncated randomized singular value decomposition (TRSVD), QR decomposition (QR) and interpolative decomposition (ID). This approach has the potential to reduce the computational effort and storage requirements. Show less

  • Engineer-PhD student

    Sept 2020 - Feb 2024

  • Student Intern (Graduation project)

    Mar 2020 - Aug 2020
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  University of California, Berkeley

  Jan 2023 - Mar 2023

  Visiting Scholar
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  Sorbonne University

  Apr 2024 - Oct 2024

  Research Engineer
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  Qubit Pharmaceuticals

  Oct 2024 - now

  Research Scientist

  Research Scientist in Quantum technologies