Abstract: |
In recent years, generative AI has gained significant traction as a tool for designing novel molecules for therapeutic purposes. Advanced deep learning techniques have been increasingly adapted for drug design, yielding varying levels of success. In this seminar, I will provide an overview of this emerging field, highlighting the key challenges in applying generative AI to drug design and presenting our proposed solutions. Specifically, we combine principles from physics and chemistry with deep learning methods to discover more realistic drug candidates within the vast chemical space. Our results are supported by benchmark studies and validated through experimental wet lab testing. |
Biography: |
| Dr. Chang-Yu (Kim) Hsieh is the QiuShi Engineering Professor at the College of Pharmaceutical Sciences, Zhejiang University. Before joining Zhejiang University, he led the Theory Division at Tencent Quantum Lab in Shenzhen, focusing on AI and quantum simulation for drug and material discovery. Prior to that, he was a postdoctoral researcher in the Department of Chemistry at MIT. His primary research interests lie in leveraging advanced computing technologies, including AI and quantum computing, to simulate and model material and molecular properties. |