We have two new papers in JMLR on estimation of undirected and directed graphical models:
- The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks (link)
- Generalized Score Matching for Non-Negative Data (link)
I received a new R01 grant from the NIH-NHLBI to use systems biology and network-based methods to integrate data from TOPMed project and identify genetic and epigenetic factors associated with cardiac arrhythmia. This new grant is in collaboration with Nona Sotoodehnia and Dan Arking and gives me an oppourtunity to expands on some of the methods work that I started during my K01 grant. I am excited to start this new collaboration and and explore the unique data from the TOPMed project!
CONGRATULATIONS to Arjun Sondhi for successfully defending his PhD dissertation. Arjun will be using his diverse skills at FlatIron Health to address importnat problems in biology and medicine. Well done, Arjun!
We have two new papers in Biometrika:
- Nonparametric Regression with Adaptive Truncation via a Convex Hierarchical Penalty (link), a new method for high-dimensional non-parametric regression implemented in the R-package HierBasis - Identifiability and Estimation of Structural Vector Autoregressive Models for Subsampled and Mixed-Frequency Time Series (link)
Excited to have Yue Wang join Jing Ma and I for a postdoctoral fellowship. Welcome to the group, Yue!
CONGRATULATIONS to Aaron Hudson for receiving an NSF Predoctoral Fellowship!
CONGRATULATIONS to (now former PhD student!) Asad Haris for successfully defending his PhD thesis titled Towards Flexible Methods in High Dimensions. Well done, Dr H!
CONGRATULATIONS to Arjun Sondhi for receiving a Best Student Paper Award from the ASA Biopharmaceutical Section for his paper The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks.
Alex Tank's talk, titled An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Serie was selected as the Best Talk at NIPS Time Series Workshop. CONGRATULATIONS, Alex!
I received a new grant from the NSF/DMS program on Computational and Data-Enabled Science and Engineering in Mathematical and Statistical Sciences (CDSE-MSS) to develop machine learning methods for emerging high-dimensional time series data in neuroscience.
CONGRATULATIONS to Lina Lin for successfully defending her PhD dissertaion — nice job Dr. Lin! Lina will be the second member of the lab jointing Google.
We have a new manuscript on arxiv that provides a general theoretical framework for analyzing multivariate Hawkes processes.
Our new paper titled Nearly Assumptionless Screening for the Mutually-Exciting Multivariate Hawkes Process has been accepted for publication at the Electronic Journal of Statistics, and is available here.
Our new paper on Network Reconstruction from High-Dimensional ODEs has been accepted for publication at the Journal of American Statistical Association, and is available on
arxiv.
Our recent Nature Communications paper, where we proposed a new network-based data integration framework, has been featured in ScienceDaily.
I received a grant from the DMS-NIGMS joint program to develop statistical methods for differential network analysis with applications to aging. This is an exciting new area of research and I look forward to collaborating with Mathias Drton and Daniel Promislow in this project.