teaching

Teaching and Mentoring Experiences

Courses (SNU)

  1. Teaching Assistant: Machine Learning in Bioinformatics, 2025 Spring, Computer Science & Engineering Dept., Seoul National University (English lecture)
    • Bioinformatics, Data & Machine Learning Algorithms for Cancer Type Classification
    • Multi-Layer Perceptron and Deep Learning with PyTorch and CoLab
  2. Teaching Assistant: Algorithm, 2024 Fall, Computer Science & Engineering Dept., Seoul National University
    • Efficient string matching for whole-genome k-mer counting and sorting
  3. Teaching Assistant: Machine Learning in Bioinformatics, 2024 Spring, Computer Science & Engineering Dept., Seoul National University (English lecture)
    • Bioinformatics, Data & Machine Learning Algorithms for Cancer Type Classification
    • Multi-Layer Perceptron and Deep Learning with PyTorch and CoLab
  4. Guest lecturer: AI-BIO, 2023 Fall, Artificial Intelligence Institute (AIIS), Seoul National University
    • Introduction to Cheminformatics and databases
    • Network representation learning with word2vec
  5. Teaching Assistant: Computer Convergence & Applications, 2023 Fall, Computer Science & Engineering Dept., Seoul National University (English lecture)
    • Introduction to AI drug discovery: Navigating the chemical space with AI technologies
  6. Guest lecturer: AI-BIO, 2022 Fall, Artificial Intelligence Institute (AIIS), Seoul National University
    • Disease networks and drug repurposing
  7. Teaching Assistant: Machine Learning in Bioinformatics, 2023 Spring, Computer Science & Engineering Dept., Seoul National University (English lecture)
    • Practical implementation of HMM for exon finding
    • Molecule representation learning & property prediction with Deep Learning
  8. Teaching Assistant: Machine Learning in Bioinformatics, 2022 Spring, Computer Science & Engineering Dept., Seoul National University (English lecture)
    • Practical implementation of HMM for exon finding

Mentorship

  1. Mentor: Creative & Integrative Design Internship Course, Computer Science & Engineering Dept., Seoul National university (2022 - 2025)
    • Spring, 2025: Development of RAG-Based AI Tool Selection and Interaction Platform for Drug Discovery
    • Fall, 2024: Real-time Ensemble Framework for Compound Activity from User Data Input
    • Spring, 2024: Integrating ADME data through multi-task learning for defining drug-likeness 2
    • Fall, 2023: Integrating ADME data through multi-task learning for defining drug-likeness 1
    • Spring, 2023: ATP-binding site prediction using protein Language Models and 3D structure.
    • Fall, 2022: ATP-binding site prediction using 3D structure.
  2. Mentor: Research Internship Program, Interdisciplinary Major in Artificial Intelligence, Seoul National University (2022-2023)
    • Project 1: Contrastive Learning Strategies for Molecular Property Prediction (2022)
    • Project 2: Biological Prior Knowledge-integrated Pocket-based Drug Design (2023)