I’m Qinghe Gao, a PhD student in the Process Intellgence Research at the Delft University of Technology supervised by Artur Schweidtmann. My research focuses on artificial intelligence in chemical enginnering 🛠️🤖, but I am also interested in generative modeling⚛️, reinforcement learning 🕹, AI4Science 🧪. Besides that, I like bouldering and climbing 🧗‍♂️.

• 📚Modeling category-selective cortical regions with topographic variational autoencoders - Best paper award: NeurIPS 2021 Workshop SVRHM : We leverage the newly introduced Topographic Variational Autoencoder to model of the emergence of such localized category-selectivity in an unsupervised manner.
• 📚Flowsheet synthesis through hierarchical reinforcement learning and graph neural networks - AICHE: We propose to use reinforcement learning for chemical process design based ona state-of-the-art actor-critic logic.
• 📚Graph neural networks for the prediction of molecular structure-property relationships - Royal Society Chemistry - Book chapter: We describe the fundamentals of GNNs and demonstrate the application of GNNs via two examples for molecular property prediction.