Publications

(2017). Comprehensive statistical inference of the clonal structure of cancer from multiple biopsies. In Scientific Reports.

PDF Code Project Cancer Genomics Dynamic Graphical Models

(2016). Structure-leveraged Methods in Breast Cancer Risk Prediction. In JMLR.

PDF Project

(2016). Discriminatory power of common genetic variants in personalized breast cancer diagnosis. In SPIE Medical Imaging conference.

Preprint

(2016). Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy. In Acad Radiol.

Preprint Project

(2015). Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. In AMIA Symposium.

PDF

(2015). Developing a Utility Decision Framework to Evaluate Predictive Models in Breast Cancer Risk Estimation. In J. of Medical Imaging.

PDF

(2015). Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. In AMIA Joint Summits.

PDF Project

(2015). Developing a Clinical Utility Framework to Evaluate Prediction Models in Radiogenomics. In SPIE Medical Imaging conference.

Preprint

(2014). Comparing the Value of Mammographic Features and Genetic Variants in Breast Cancer Risk Prediction. In AMIA Symposium.

PDF Project

(2014). Learning Heterogeneous Hidden Markov Random Fields. In AISTATS.

PDF

(2014). New Genetic Variants Improve Personalized Breast Cancer Diagnosis. In AMIA-TBI.

PDF Project Marco Ramoni Distinguished Paper Award

(2013). Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. In AMIA Symposium.

PDF Project

(2012). High-Dimensional Structured Feature Screening Using Binary Markov Random Fields. In AISTAT.

PDF Code Project

(2012). A Collective Ranking Method for Genome-wide Association Studies. In ACM-BCB.

Project

(2009). Cross-Sectional Stock Return Analysis Using Support Vector Regression. In Applied Economics Letters.

PDF

(2008). Meta-prediction of Phosphorylation Sites with Weighted Voting and Restricted Grid Search Parameter Selection. In Nucleic Acids Res.

PDF

(2007). Meta-prediction of Protein Subcellular Localization with Reduced Voting. In Nucleic Acids Res.

PDF

Projects

Multiple Testing Under Dependence

A graphical model based multiple testing procedure which captures dependence among the hypotheses.

Personalized Breast Cancer Diagnosis

Our results show that radiologists can potentially use genetic variants (SNPs) to improve personalized breast cancer diagnosis.

Tumor Heterogeneity Anaysis

Comprehensive statistical inference of the clonal structure of cancer from multiple biopsies.

Service

Journal Referee

Journal of the American Statistical Association, Data Mining and Knowledge Discovery, Machine Learning, Genome Research, Cell Systems, Bioinformatics, Pattern Recognition Letters, Journal of Digital Imaging, Economic Modelling

Conference Program Committee

ICML 2018, RECOMB 2018, ICLR 2018, AMIA 2018 Informatics Summit, NIPS-MLCB 2017, NIPS 2017, AMIA 2017, AMIA-TBI/CRI 2017, AAAI 2017, NIPS 2016, AMIA 2016, AAAI 2016, AMIA-TBI/CRI 2016, ACMBCB 2016, MLSB 2016, NIPS 2015, IJCAI 2015, AMIA 2015, AMIA-TBI/CRI 2015, AISTATS 2015, WABI2015, NIPS 2014, UAI 2014, AAAI 2014, AMIA 2014, IJCAI 2013, AMIA 2013, GENSIPS 2012

Awards

  • (2015) Washington Research Foundation Innovation Postdoctoral Fellowship
  • (2014) AMIA Marco Ramoni Distinguished Paper Award
  • (2014) Moore/Sloan Data Science Postdoctoral Fellowship

Teaching

Courses

  • Guest instructor, CS 760 Machine Learning, UW-Madison, 2014 Spring.
  • Guest instructor, STAT 992 Large-scale inference, UW-Madison, 2013 Spring.
  • Teaching assistant, Introduction to Artificial Intelligence, Peking University, 2005 Spring.

Mentees

  • John T Halloran, PhD student, Department of Electrical Engineering, University of Washington
  • Charles Kwong, PhD student, Department of Computer Sciences, UW-Madison
  • Sinong Geng, Graduate student, Department of Statistics, UW-Madison

Contact

  • liu6@uw.edu
  • South Foege Building, S-220, 3720 15th Ave NE, Seattle WA 98195