My research interests are
machine learning, statistical
computation, and their applications.
My Google scholar page can be
My statistics and machine
learning research group at HKUST
investigates the fundamental theory of machine learning.
Based on theoretical understanding, we also design effective machine learning algorithms for practical problems.
We also apply machine learning methods to various applications such
as computer vision and natural language processing.
Our core machine learning research currently focuses on the following topics.
Theoretical Foundation of Machine Learning
This research topic is to study the
mathematical models and
statistical convergence behavior of
machine learning algorithms. For example, the
mathematical models for deep neural networks, and
statistical analysis of various learning algorithms.
This research topic is concerned with convex and nonconvex optimization, large scalde
and distributed training, automatic tuning of machine learning
models and efficient deployment.
Robust and Adaptive Algorithms
This research topic is concerned with the generalization of machine learning
procedures to new scenarios, and related robustness issues, such as
adversarial examples, noise tolerance, adaptation of ML models to new
domains, unsupervised pretraining, and learning with limited resources.
Tools and Applications
This research topic is to develop tools and apply learning
algorithms to various applications such as
natural language processing, computer vision, and games etc.