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.
Efficient Computational Algorithms
This research topic is concerned with
efficient convex and nonconvex optimization, large scale
and distributed training, automatic tuning of machine learning
Robust and Adaptive Methods
This research topic is concerned with the generalization of machine learning
procedures to new scenarios, and related
issues of distribution shift. We consider
problems such as effective adaptation of ML models to new
domains, unsupervised pretraining and
fine-tuning, and exploration issues in
This research topic is to develop tools
and algorithms in applications such
as natural language processing, computer
vision, and science. We are especially
interested in statistically effective models, computationally efficient
algorithms, and robust procedures under distribution shift.