Research Interests: Motivated by the promise of precision medicine and focused on methodology for uncovering meaningful patterns from complex data, which often contain heterogeneous samples with conflicting patterns. Currently, I'm working on designing methods to interpret medical models and to allow model parameters to change between samples.
List of Publications
Possibly more updated lists can be found on Google Scholar, Semantic Scholar, or DBLP.
Journal Article and Conference Proceedings
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models
Learning Sample-Specific Models with Low-Rank Personalized Regression
Precision Lasso: Accounting for Correlations and Linear Dependencies in High-Dimensional Genomic Data
Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations
Personalized Regression Enables Sample-Specific Pan-Cancer Analysis
Opportunities And Obstacles For Deep Learning In Biology And Medicine
Journal of the Royal Society Interface, 2018
Experimental and Computational Mutagenesis To Investigate the Positioning of a General Base within an Enzyme Active Site
Disentangling Increased Testing from Covid-19 Epidemic Spread
On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks
Discriminative Subtyping of Lung Cancers from Histopathology Images via Contextual Deep Learning
How Interpretable and Trustworthy are GAMs?
Differential Principal Components reveal patterns of differentiation in case/control studies
Hybrid Subspace Learning for High-Dimensional Genomic Data