Research
synopsis: My principal research interests lie
in the development of machine learning and statistical methodology;
especially for solving problems involving automated learning,
reasoning, and decision-making in high-dimensional, multimodal, and
dynamic possible worlds; and for building quantitative models and
predictive understandings of the evolutionary mechanism, regulatory
circuitry, and
developmental processes of biological systems.
Currently the following themes are studied in my group:
- Foundations
of Statistical Learning, including :
1) Theory and algorithms for estimating time/space varying-coefficient
models with evolving strcutures; 2) Learning sparse structured
input/output models in very high-dimensional space; 3) Nonparametric
techniques for infinite-dimensional models; 4) Active learning.
- Computational
Biology, including: 1) Comparative genomic analysis of
regulatory evolution; 2) Systems
biology investigation of time-varying gene regulation circuity; 3)
Statistical genetic analysis of
population variation, demography and evolution; 4) Structured inference
of
genome-transcriptome-phenome association in complex diseases.
- Applications
of Statistical Learning, in social/bio network analysis,
text/image data mining, computer vision, and machine translation.
Rescent
Activities:
I am teaching Machine
Learning
(10701) in Spring 2010.
Previously I
taught Probabilistic Graphical
Models
(10708) in Fall 2009;
and I taught Computational
Genomics
(10810) in Spring 2009.
The Dragon Star Lectures: Advanced Machine Learning, @ Peking/Tsinghua Univ., Beijing, Summer 2009.
I gave
a keynote talk on "Recent Advances in Learning Sparse Structured
Input/Output Model: Models, Algorithms, and Applications" at
the NIPS
2008 Workshop on "Structured Input, Structured Output".
I gave
a talk on "Time-Varying
Networks: Reconstructing Temporally/Spatially Rewiring Gene Interactions"
at the RECOMB Regulatory Genomics workshop.
I
co-organized NIPS
2008 Workshop on "Analyzing Graphs: Theories and Applications".
I
co-organized ICML
2007 Workshop on Learning in Structured Output Spaces.
I
co-organized NIPS
2007 Workshop on Statistical Models of Networks.
I gave
a keynote talk on "Graphical
models and algorithms for integrative bioinformatics at the 6th annual Graybill
Conference.
I gave
a keynote talk on
"Probabilistic graphical models --- theory, algorithm, and application"
at ICMLA'07.
|