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gumgo91/README.md

Hi, I'm Hyunseung Kong 👋

Ph.D. | Computational Pharmacology and AI for Drug Development

I'm a researcher working at the intersection of artificial intelligence, pharmacology, and computational biology.

My research focuses on developing computational systems that help us understand biological processes, predict drug responses, and make pharmacological research more efficient and reproducible.

I'm particularly interested in connecting machine learning with mechanistic models, from molecular interactions to whole-body physiological systems.

🔬 Research Interests

  • AI for Drug Development: Machine learning and autonomous agents for pharmacological research
  • Pharmacometrics: Population pharmacokinetics, nonlinear mixed-effects modeling, and scientific computing
  • Physiological Digital Twins: Mechanistic simulation of drug effects and biological processes
  • Computational Biology: Biological representation learning and multimodal data integration

💬 A Little More About Me

  • 🌱 I enjoy building scientific tools from scratch.
  • 🧬 I believe good computational research should be reproducible, interpretable, and useful.
  • 🌿 My favorite Pokémon is still Bulbasaur.
  • 🔗 You can find me on LinkedIn.

⚡ What Keeps Me Going

  • Inspiration
  • Curiosity
  • Someone specifically telling me not to do something

Pinned Loading

  1. PKPy2 PKPy2 Public

    PKPy2: explicit-model nonlinear mixed-effects population pharmacokinetic estimation in Python

    Python

  2. PKPy PKPy Public

    PKPy: A Python-Based Framework for Automated Population Pharmacokinetic Analysis

    Jupyter Notebook 10

  3. Dual-Encoder-Drug-Repurposing Dual-Encoder-Drug-Repurposing Public

    Official implementation of "Integrating Chemical Structure and Transcriptional Responses via Dual-Encoder Contrastive Learning for Drug Repurposing"

    Python

  4. PKAgent PKAgent Public

    PKAgent is a large language model (LLM) agent that develops population pharmacokinetic (PopPK) and PK/PD models.

    Python