Jiale Shi is a postdoctoral researcher specializing in AI-driven polymer science, currently at Boston University after a postdoc at MIT and a PhD in Chemical Engineering from the University of Notre Dame. Over nine years of research experience, Jiale blends machine learning, molecular simulation, statistical physics, and chemical informatics to map free energy landscapes and accelerate inverse design of sustainable and functional polymeric materials. Their work spans polymer-surface adhesion, liquid crystal mechanics, and metal cluster isomerization, and has produced multiple first-author publications and awards for outstanding research. Notably, Jiale builds digital infrastructure for polymer databases, aiming to make polymer data FAIR and directly usable for materials discovery. Trained in chemistry (BS, Peking University) with a CS minor, they bridge theory, computation, and data engineering to turn complex simulation insights into practical materials design tools.
9 years of coding experience
10 years of employment as a software developer
High School, High School Certificate of Competence Program, High School, High School Certificate of Competence Program at Xiaoshan High School, Zhejiang Province(浙江省萧山中学)
Bachelor of Science - BS, Chemistry, 3.68/4, Bachelor of Science - BS, Chemistry, 3.68/4 at Peking University
Doctor of Philosophy - PhD, Chemical Engineering, Doctor of Philosophy - PhD, Chemical Engineering at University of Notre Dame
In Silico Measurement of Elastic Moduli of Nematic Liquid Crystals
Contributions:18 pushes in 5 years
elasticliquidcrystalsin-silicomeasurement
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