Sangbin L.

Full Stack Data Engineer at Study Hall Ltd
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Contact Information
us****@****om
(386) 825-5501
Location
London, England, United Kingdom, UK
Languages
  • English Native or bilingual proficiency
  • Korean Native or bilingual proficiency
  • Chinese Elementary proficiency
  • French Elementary proficiency

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Bio

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Credentials

  • Learn the Command Line Course
    Codecademy
    Oct, 2022
    - Nov, 2024
  • OpenCV for Python Developers
    LinkedIn
    Jun, 2022
    - Nov, 2024

Experience

    • Primary and Secondary Education
    • 1 - 100 Employee
    • Full Stack Data Engineer
      • Nov 2022 - Present

    • United Kingdom
    • Research Services
    • 700 & Above Employee
    • Student Researcher
      • Sep 2021 - Aug 2022

      Conducted a variety of the self-motivated urban & spatial research in the Bartlett Centre for Spatial Advanced Analysis Deep Learning based Human Body Size Measurement Application (Mar 2022 - Sep 2022) Conducted a pro-retail computer vision based deep learning research to develop the anthropometry (body measurement) application with a higher accuracy. Using TensorFlow and OpenCV in Python, the app based on BodyPix and COCO(Common Objects in Context) achieved 95.84% of accuracy in the experimentation of capturing the 4 body dimensions (arm length, leg length, chest girth and hip girth) for 10 volunteer subjects, which outperformed some of the previous DL research presenting 95.59% (Foysal et al., 2021) and 95.72% (Xiaohui et al., 2018). Flood AR - Am I at Risk? (Jan 2022 - May 2022) Built up an augmented reality web application that guides which flood risk zone of London the user is located in. Acquiring GPS location information from the user's smartphone, the app allows the user to interactively check the flood zone, flood alert and flood history of the locations. Aside from the AR application, I co-led the team, Delugeo, and created the webpage to raise the public's awareness the global and local flood vulnerability by visualising the related data. The project was acclaimed as one of the best projects in the programme and introduced as a sample work in the centre's promotion video. ▲ Project Website: https://nfabsikova.github.io/delugeo/ ▲ Web app: https://s-n-b-n.github.io/a/a.html Location-Based AR Property Price Marker Application (Jan 2022 - Mar 2022) The application displays 2,366 price records of London Borough of Camden and Hackney sampled from 435,272 records in UK Land Registry's Price Paid Data. Using AR, the user can check the paid price for residential transactions via smartphone camera in real time. For geocoding, pgeocode package of Python was used. ▲ Price marker app: https://s-n-b-n.github.io/CASA0003/price.html Show less

    • South Korea
    • Newspaper Publishing
    • 1 - 100 Employee
    • Staff Writer
      • Jul 2016 - Jul 2021

      Real Estate News Desk covering Housing, Real Estate Market and Urban Issues. Real Estate News Desk covering Housing, Real Estate Market and Urban Issues.

  • MNTR
    • Seoul, South Korea
    • Founder
      • Mar 2019 - Dec 2019

      Founded a startup team. Made the minimal prototype of the data-driven education and course recommendation service, MNTR. Was able to successfully secure $100k angel investment. 2nd Winner awarded by TechStars. Founded a startup team. Made the minimal prototype of the data-driven education and course recommendation service, MNTR. Was able to successfully secure $100k angel investment. 2nd Winner awarded by TechStars.

    • South Korea
    • Newspaper Publishing
    • 1 - 100 Employee
    • Staff Writer
      • Jan 2018 - Feb 2019

      Worked in RealtyGo, Real Estate Spinoff Media of the Chosunilbo, Korean largest news outlet. Worked in RealtyGo, Real Estate Spinoff Media of the Chosunilbo, Korean largest news outlet.

    • United Kingdom
    • IT Services and IT Consulting
    • 700 & Above Employee
    • Consultant
      • Jan 2016 - Mar 2016

      Contributed to ‘Life Cycle Retail Marketing Segmentation Strategy Project’ (teamed with SAS Institute Inc.) of Woori Bank (KOSPI:000030) HQ in Seoul, Korea by collaborating with data scientists to extrapolate meaningful data that produced results for Woori Bank. Contributed to ‘Life Cycle Retail Marketing Segmentation Strategy Project’ (teamed with SAS Institute Inc.) of Woori Bank (KOSPI:000030) HQ in Seoul, Korea by collaborating with data scientists to extrapolate meaningful data that produced results for Woori Bank.

    • Defense and Space Manufacturing
    • 200 - 300 Employee
    • 1st. Lieutenant
      • Dec 2012 - Nov 2015

      Executive Officer Executive Officer

    • South Korea
    • Higher Education
    • 700 & Above Employee
    • Resident Assistant
      • Jun 2011 - Feb 2012

Education

  • UCL
    Master of Science - MS, Spatial Data Science and Visualisation
    2021 - 2022
  • Korea University
    Bachelor of Science - BS, Brain and Cognitive Engineering
    2008 - 2012
  • Korea University
    Bachelor of Arts (B.A.), Psychology
    2008 - 2012
  • Myungduk Foreign Language High School
    Math, Physics, Biology, Law, Computer Science, English, Chinese
    2004 - 2007

Community

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