Lily Wang

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ORCiD:  0000-0003-1282-4413

Lily’s doctoral thesis centers around tools development in molecular dynamics (MD). Currently she is working on or thinking about five main problems:

  • Developing an easier user interface to create polymer topologies for the open-source MD software GROMACS (PolyTop)
  • Developing a library for accessible and parallelisable out-of-core analysis of software-agnostic MD data (ALPaCCA)
  • The generalisation of machine learning techniques for ab initio force-field parameters to the classical MD scale
  • Developing a library of accessible start-up Jupyter notebooks and tutorials that enable students from all backgrounds to immediately begin with interesting and useful computational chemistry without the programming, computational, or mathematic background that much of the minutia requires (eg. plotting figures in Python) (CoChLear)
  • Developing a library that elegantly unites the many disparate aspects of computational chemistry modelling — there is a multitude of software, formats, and standards for quantum mechanics (QM), ab initio molecular mechanics, hybrid QMMM, classical atomistic MD, coarse-grained MD, and predicting properties such as pKa, electrostatics interactions, etc. etc.  A standard user interface and/or pipeline will save countless research time and effort, improving accessibility to new researchers and the lives of those already in the field.

Occasionally she applies MD to real systems. Feel free to chat to her about:

  • P-glycoprotein, the membrane protein infamous for mediating multi drug resistance by transporting hundred of substrates
  • pKas of urea-derived lipid compounds
  • polymer dynamics

Lily completed her Bachelor of Philosophy (Hons) at the Australian National University in 2017, graduating with first class honours and a major in chemistry. She was the inaugural recipient of the David and Veronica Craig scholarship for students in theoretical and computational chemistry in 2018. She likes Python, long walks up mountains, and cheese.

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