Anastasiia Chaikova

Student Assistant at Technical University of Munich
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Contact Information
us****@****om
(386) 825-5501
Location
Bremen, Bremen, Germany, DE
Languages
  • English Professional working proficiency
  • Russian Native or bilingual proficiency
  • German Elementary proficiency

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Bio

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Credentials

  • OxML23 Attendance Certificate
    AI for Global Goals

Experience

  • Technical University of Munich
    • Germany
    • Research Services
    • 700 & Above Employee
    • Student Assistant
      • Oct 2023 - Present

  • JetBrains
    • Czechia
    • Software Development
    • 700 & Above Employee
    • Working Student
      • Nov 2022 - Aug 2023

      Investigated the potential of large language models for extracting information from astronomical reports. Through our approach, we have surpassed GPT-3 in the task of NER. A pipeline was developed that achieved a success rate of over 95% in extracting certain entities. The findings from the research were published in a paper. Investigated the potential of large language models for extracting information from astronomical reports. Through our approach, we have surpassed GPT-3 in the task of NER. A pipeline was developed that achieved a success rate of over 95% in extracting certain entities. The findings from the research were published in a paper.

  • JetBrains
    • Czechia
    • Software Development
    • 700 & Above Employee
    • Research Intern
      • Oct 2021 - Jan 2022

      Analyzed data from the first CHIME/FRB catalog in the Astroparticle Physics Lab with the aim of testing hypotheses that had not yet been explored in the community. Through my work, I developed a method for classifying bursts based on morphology, which provided new insights into the nature of FRBs and published a paper with the results of work. Analyzed data from the first CHIME/FRB catalog in the Astroparticle Physics Lab with the aim of testing hypotheses that had not yet been explored in the community. Through my work, I developed a method for classifying bursts based on morphology, which provided new insights into the nature of FRBs and published a paper with the results of work.

Education

  • Technical University of Munich
    Master's degree, Mathematics in Data Science
    2023 -
  • Constructor University
    Bachelor of Science - BS, Computer Science
    2022 - 2023
  • Higher School of Economics
    Bachelor's degree, Applied Mathematics and Information Science
    2019 - 2022

Community

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