Cunliang has a bachelor and master degree in life science from Shandong University (China), and a PhD degree in computational structural biology from Utrecht University (Netherlands).

During his master, he mainly studied molecular modelling and simulations and conducted a project to study the processivity of cellobiohydrolase using molecular dynamic simulations.

Cunliang started his PhD in 2014 and became interested in machine learning and data analysis. His research generated two peer-reviewed machine learning-based methods (iScore and iSEE), which facilitate fast and reliable scoring and binding affinity prediction of protein-protein interactions. He has also been active in the grand challenges of CAPRI (www.capri-docking.org) and D3R (www.drugdesigndata.org) that aim to test computational algorithms in blind predictions of protein-protein and protein-ligand poses and affinity rankings.

Cunliang joined eScience Center as a research engineer in July 2019.

Key skills

  • Machine Learning
  • Computational biology
  • Molecular Simulations
  • Python
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