ÌÇÐÄvlog

Education

• BS, Beijing University of Aeronautics and Astronautics
• MA, Brandeis University
• PhD, Northeastern University

Research

Reinforcement learning and its applications to control and multi-agent systems where my doctoral studies originated. In general terms, reinforcement learning is concerned with computational approaches to learning from reward. Here I consider how a learning agent can learn as quickly as possible from limited interaction with other agents and its environment.

Image retrieval, in particular content-based retrieval where I consider indexing schemes that allow flexible retrieval metrics to be created on the fly so that very large databases can be accessed efficiently and accurately.

Classification and data mining, where I am particularly interested in adaptive metric nearest-neighbor techniques and compact subspace representation for building robust classifiers from limited training data.