Soumeya Belabbas| Artificial Intelligence| Best Researcher Award

Soumeya Belabbas| Artificial Intelligence| Best Researcher Award

Soumeya Belabbas,

Dr.Chunhui Li, PhDΒ (πŸ“§Β chunhuili@lbl.govΒ | 🌐 LinkedInΒ | 🐱 GitHub) is a post-doctoral fellow at Lawrence Berkeley National Laboratory, specializing in deep learning and molecular dynamics simulations. Dr. Li’s research focuses on developing machine learning models for rapid predictions in geoscience and battery applications, with significant speed improvements over conventional methods.

Publication Profile

Education and Experience πŸŽ“

Dr.Chunhui Li earned a Doctor of Philosophy in Mechanical Engineering (πŸŽ“ Washington State University, July 2019) with a dissertation on simulation studies of protein-particle interactions in battery applications, advised by Prof. Jin Liu. He also holds a Master of Engineering in Mechanical Engineering (πŸŽ“ Harbin Institute of Technology, July 2013) with a thesis on grinding trajectories of SiC Aspherical, advised by Prof. Feihu Zhang, and a Bachelor of Engineering in Manufacturing Engineering (πŸŽ“ Harbin Institute of Technology, July 2011). Since July 2020, Dr. Li has been working at Lawrence Berkeley National Laboratory, focusing on rapid prediction of liquid structure using deep learning and developing machine learning surrogates for Geoscience Models.

Professional Development

Dr.Chunhui Li has honed technical skills in molecular dynamics simulationΒ (πŸ–₯️ GROMACS, LAMMPS, VASP),Β machine learning/deep learning/data scienceΒ (🧠 PyTorch, TensorFlow, Scikit-Learn, Pandas, Numpy), andΒ programming languagesΒ (πŸ’»Β Python, Java, C/C++, Shell script, MATLAB, Perl). He has designed and managed high-throughput molecular dynamics simulations, curated extensive datasets, and developed efficient AI models, showcasing impressive speed improvements over traditional methods.

Research Focus

Dr. Li’s research focuses on the application ofΒ machine learningΒ andΒ molecular dynamicsΒ to geoscience and battery applications. His notable work includes developing deep learning models for rapid prediction of time-averaged structural properties, creating AI-based surrogates for geochemistry models, and improving the ion conductivity of solid polymer electrolytes through protein-coated nanofillers. Dr.Li’s collaborative efforts with experimental researchers have led to significant advancements in computational physics and material science.

PublicationsΒ πŸ“šπŸ“

ChunhuiLi | Molecular Dynamics | Best Researcher Award

ChunhuiLi | Molecular Dynamics | Best Researcher Award

Dr. ChunhuiLi , lawrence berkeley national laboratory, United States.

Dr.Chunhui Li, PhDΒ (πŸ“§Β chunhuili@lbl.govΒ | 🌐 LinkedInΒ | 🐱 GitHub) is a post-doctoral fellow at Lawrence Berkeley National Laboratory, specializing in deep learning and molecular dynamics simulations. Dr. Li’s research focuses on developing machine learning models for rapid predictions in geoscience and battery applications, with significant speed improvements over conventional methods.

Publication Profile

Education and Experience πŸŽ“

Dr.Chunhui Li earned a Doctor of Philosophy in Mechanical Engineering (πŸŽ“ Washington State University, July 2019) with a dissertation on simulation studies of protein-particle interactions in battery applications, advised by Prof. Jin Liu. He also holds a Master of Engineering in Mechanical Engineering (πŸŽ“ Harbin Institute of Technology, July 2013) with a thesis on grinding trajectories of SiC Aspherical, advised by Prof. Feihu Zhang, and a Bachelor of Engineering in Manufacturing Engineering (πŸŽ“ Harbin Institute of Technology, July 2011). Since July 2020, Dr. Li has been working at Lawrence Berkeley National Laboratory, focusing on rapid prediction of liquid structure using deep learning and developing machine learning surrogates for Geoscience Models.

Professional Development

Dr.Chunhui Li has honed technical skills in molecular dynamics simulationΒ (πŸ–₯️ GROMACS, LAMMPS, VASP),Β machine learning/deep learning/data scienceΒ (🧠 PyTorch, TensorFlow, Scikit-Learn, Pandas, Numpy), andΒ programming languagesΒ (πŸ’»Β Python, Java, C/C++, Shell script, MATLAB, Perl). He has designed and managed high-throughput molecular dynamics simulations, curated extensive datasets, and developed efficient AI models, showcasing impressive speed improvements over traditional methods.

Research Focus

Dr. Li’s research focuses on the application ofΒ machine learningΒ andΒ molecular dynamicsΒ to geoscience and battery applications. His notable work includes developing deep learning models for rapid prediction of time-averaged structural properties, creating AI-based surrogates for geochemistry models, and improving the ion conductivity of solid polymer electrolytes through protein-coated nanofillers. Dr.Li’s collaborative efforts with experimental researchers have led to significant advancements in computational physics and material science.

PublicationsΒ πŸ“šπŸ“