Jian HUANG: Statistical Deep Learning with Applications to Biomedical Data Analysis
On Oct 20, 2022, Prof. Jian HUANG from the Department of Applied Mathematics, The Hong Kong Polytechnic University was invited to the 87th Science Lecture of College of Science, SUSTech. He gave a lecture themed “Statistical Deep Learning with Applications to Biomedical Data Analysis”, which was chaired by Prof. Qi-man SHAO and Prof. Guoliang TIAN of the Department of Statistics and Data Science, SUSTech. More than 200 audience participated in this lecture online.
Raymond Chan: Sparsity—The Beauty of Less is More
On September 8, 2022, Prof. Raymond Chan from Department of Mathematics, City University of Hong Kong was invited to the 83th Science Lecture of College of Science, SUSTech. He gave a lecture themed “Sparsity—The Beauty of Less is More”, which was chaired by Prof. Qiman Shao, head of Department of Statistics and Data Science, Southern University of Science and Technology.
The 2022 Southern University of Science and Technology Statistics and Data Science Symposium
The 2022 Southern University of Science and Technology (SUSTech) Statistics and Data Science Academic Symposium had been successfully held by SUSTech International Center for Mathematics and SUSTech Department of Statistics and Data Science from 21st to 22nd May at College of Science conference hall. The symposium attracted renowned experts and scholars from Peking University, Tsinghua University, Fudan University, Zhejiang University, Shanghai Jiao Tong University, University of Science and Technology of China, Renmin University of China, University of Hong Kong, Hong Kong University of Science and Technology and Chinese University of Hong Kong, to meet online and in person, updating their scientific research in the field of statistics and data science.
Proposing new percolation model with an indirect influence mechanism – the induced percolation
Percolation is one of the important research directions of statistical physics. Over the past 20 years, scientists have continuously used percolation models to study propagation problems in complex networked systems. Almost all percolation theories focus on modeling influence mechanisms between direct neighbors to the best of our knowledge. However, growing evidence in social and ecological systems suggests that indirect influence is pervasive in the dynamical behaviors of the system.