Introduction

With the recent advances in artificial intelligence (AI) or machine learning (ML) techniques, we have seen a rise in the application of ML in various fields of science. But, on the other hand, many chemists are still wondering if using this powerful ML in a black box manner will help their research or not. In this workshop, we aim to shed some light on this.

In the morning, we will open with Prof. William Green of MIT giving a talk on “Quantitative Machine Learning for Chemical Sciences”. Then, we will have Prof. Yi-Pei Li (NTU) and Tzuhsiung Yang (NTHU) give us an idea of the basic background behind ML and what it can and can not do. In addition, we will have hands-on use of ML techniques for material property prediction, generating molecular structure for desired property, and organic chemistry predictive retrosynthesis. Lastly, we will have some lab members demo and share their experience using ML for their research.

We invite interested PIs to please join us to learn more about ML techniques and their possible application in chemical problems. Since we will have hands-on, please bring your laptop computers, and 1 lab member can also join you at the workshop.