Published in SC19, 2019
This paper is about AI-driven workflow on supercomputers
Recommended citation: Lee, Hyungro, et al. "DeepDriveMD: Deep-learning driven adaptive molecular simulations for protein folding." 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS). IEEE, 2019. https://ieeexplore.ieee.org/abstract/document/8945122
Published in arXiv, 2020
This paper is about COVID-19 research using HPC resource
Recommended citation: Lee, H., Merzky, A., Tan, L., Titov, M., Turilli, M., Alfe, D., Bhati, A., Brace, A., Clyde, A., Coveney, P. and Ma, H., 2020. Scalable HPC and AI Infrastructure for COVID-19 Therapeutics. arXiv preprint arXiv:2010.10517. https://arxiv.org/pdf/2010.10517
Published in biorXiv, 2020
This paper is about AI workflow for COVID-19 research using HPC resource
Recommended citation: Casalino, L., Dommer, A.C., Gaieb, Z., Barros, E.P., Sztain, T., Ahn, S.H., Trifan, A., Brace, A., Ma, H., Lee, H. and Turilli, M., 2020. AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. BioRxiv. https://www.biorxiv.org/content/10.1101/2020.11.19.390187v1.full-text
Advanced workflows for massive swarms of independent MD simulations and dynamic analysis protocol integrated
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations.
The Power of Many: Ensemble Toolkit for Earth Sciences
INtegrated and Scalable PredictIon of REsistance
MDFF-EnTK Adaptive simulation/analysis.
Asynchronous adaptive simulation and analysis
Python library for alchemical free energy calculations
Python library for developing and executing large-scale ensemble-based workflows
A Galaxy based system for identifying retrotransposons in genome
Machine learning for molecular dynamics.
Python library for Microsoft Azure Services including Virtual Machine (VM) to provision resources
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.