9月6日
研讨会, 演讲, 讲座
Mathematics Colloquium - On Euler characteristic, hyperbolicity,and fundamental groups
We will investigate various notions of hyperbolicity in Riemannian and complex geometries, with a focus on some conjectures (due to Hopf, Singer, etc.) on Euler characteristic of compact aspherical manifolds.
9月4日
研讨会, 演讲, 讲座
PhD Student Seminar - Fully decoupled schemes for incompressible fluid/thin-walled structure interaction
Based on Van Kan’s projection scheme, some fully decoupled schemes for incompressible fluid/thin-walled structure interaction were proposed. They show better accuracy than Fernandez’s schemes in 2D linear test case. 3D non-linear test case has not finished yet.
9月3日
研讨会, 演讲, 讲座
Seminar on PDE - Some Liouville type theorems onRiemannian manifolds
In this talk, I introduce a sharp gradient estimate for linear heat equation on complete non-compact Riemannian manifolds which can be considered as an extension of Hamilton’s gradient estimate. Moreover, I also give Liouville results for some nonlinear equations involving p-Laplacian.
9月2日
会议, 座谈会, 论坛
POSTPONED: HKUST – Kyoto University Joint Symposium on Informatics 
8月30日
研讨会, 演讲, 讲座
Seminar on Pure Mathematics - Correlators for finite conformal field theories
Correlators of a rational conformal field theory (RCFT) can be described as specific elements in spaces of conformal blocks.
8月28日
研讨会, 演讲, 讲座
CHEM - PhD Student Seminar - Apply Integral Equation Theory to Molecular Recognition
Student: Mr. Yeqing YU Department: Department of Chemistry, HKUST Supervisor: Professor Xuhui HUANG
8月28日
研讨会, 演讲, 讲座
CHEM - PhD Student Seminar - Application of Neural Network for the Development of Coarse Grained Model
Student: Miss Xiaowei WANG Department: Department of Chemistry, HKUST Supervisor: Professor Xuhui HUANG
8月28日
研讨会, 演讲, 讲座
PhD Student Seminar - Deep Learning Techniques for Music Generation
Can machines generate music? Recent deep learning-driven systems have made breakthroughs on this topic. Some famous among them are Coconet, DeepBach, GLSR-VAE, C-RNN-GAN, etc. However the generated music is still not satisfying based on the feedbacks from different music communities.