Nan-Hung Hsieh


Texas A&M University


My name is Nan-Hung Hsieh (謝男鴻). I'm a postdoc at Texas A&M University Toxicology Program and Superfund Research Program. My research focuses on uncertainty/variability and probabilistic modeling in quantitative systems toxicology/pharmacology.

I'm also interested in open science. I believe that science can be more transparent, so people can easily share and acquire more knowledge through these ways.

Nan-Hung Hsieh's Github chart


  • Pharmacokinetics
  • Bayesian Statistics
  • Open Source Software


  • PhD in Bioenvironmental Systems Engineering

    National Taiwan University

  • MSc in Bioenvironmental Systems Engineering

    National Taiwan University

  • BSc in Safety, Health and Environmental Engineering

    National United University


Sobol Sensitivity Analysis for Pharmacokinetic Model

Using mrgsolve package and its approach to conduct Sobol sensitivity analysis in pharmacokinetic modeling

Sensitivity Analysis for PBPK Model

Applying the Morris screening to exam the parameter sensitivity in physiological-based pharmacokinetic model

MCSim under R (Delay differentials example)

The advance exercise of use MCsim with R desolve package


Pharmacokinetic modeling of chemicals

Modern Open Source Tools for State-of-the-Art Risk Assessment Workshop



P42 ES027704

Comprehensive Tools and Models for Addressing Exposure to Mixtures During Environmental Emergency-Related Contamination Events

U01 FD005838

Enhancing the Reliability, Efficiency, and Usability of Bayesian Population PBPK Modeling


Assessing the Fine Particles-Associated Health Risks for Workers in Workplace

STAR RD83561201

Toxicogenetics of Tetrachloroethylene Metabolism and Toxicity - Using Collaborative Cross Mouse Population Approach to Address …


Assessing Health Risks for Workers in High Lead Exposed Factories


    A simulation and statistical inference tool for algebraic or differential equation systems

    An R package to apply global sensitivity analysis in physiologically based kinetic modeling