Promise Shittu

Promise Shittu

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Full Stack Developer at QuickCheck
Lagos, Nigeria

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Jobs verified_user 0% verified
  • OrditAI
    Senior Backend Engineer
    OrditAI
    Nov 2024 - May 2025 (7 months)
  • Sparklehood
    Software Engineer
    Sparklehood
    Jul 2023 - Oct 2024 (1 year 4 months)
  • Quickcheck
    Full Stack Developer
    Quickcheck
    Aug 2022 - Current (3 years 10 months)
  • Dowstrademus Investment Limited
    Software Engineer
    Dowstrademus Investment Limited
    Mar 2020 - May 2023 (3 years 3 months)
  • GemMine
    Mentor, Core Team Member
    GemMine
    Jan 2020 - Jun 2021 (1 year 6 months)
    Leading a lovely team determined to help students to become better in Mind and Skills.
  • Powersoft Integrated Solutions Ltd
    Software Engineer Intern
    Powersoft Integrated Solutions Ltd
    Jan 2020 - Mar 2020 (3 months)
  • Pine Analytical
    Data Analyst
    Pine Analytical
    Nov 2019 - Jan 2020 (3 months)
Education verified_user 0% verified
  • WorldQuant University
    Appllied Data Science
    WorldQuant University
    Jan 2019 - Dec 2020 (2 years)
    WorldQuant University (WQU) Scientific Computing and Python for Data Science Unit, a unique tuition-free online offering.
  • Obafemi Awolowo University
    Bachelor's degree, Computer Science with Mathematics, Computer Science
    Obafemi Awolowo University
    Jan 2016 - Dec 2021 (6 years)
Publications verified_user 0% verified
  • Obafemi Awolowo University
    Optimizing E-Library Engagement with Hybrid Recommender System
    Obafemi Awolowo University
    Aug 2025
    https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Xh1Ey48AAAAJ&citation_for_view=Xh1Ey48AAAAJ:u5HHmVD_uO8C With growing reliance on digital libraries, personalized recommendation systems have become essential for enhancing user experience and resource accessibility. This study presents a hybrid recommender model designed to optimize e-library engagement among university students by providing tailored book suggestions based on user preferences and activity patterns. The model integrates Cosine Similarity and Term Frequency-Inverse Document Frequency (TF-IDF) to enhance the accuracy and relevance of recommendations. The system was developed using Python with Django framework for backend and JavaScript with the React frame