About Me

I am an applied statistician working in interpretable machine learning and the bioinformatics analysis of genomic data, with a focus on deep models and AI. I am an Associate Professor in the Faculty of Computer Science at HSE University. Previously I was a bioinformatics scientist at ETH Zurich, a postdoctoral researcher in computational biology at McGill University, and a research fellow at Harvard Medical School. I hold a PhD in Quantitative Psychology from The Ohio State University, where my work centered on latent variable modeling, along with master's degrees in Mathematical Statistics and Psychometrics. This site collects my blog posts, code, and other resources from my graduate years.

My CV can be accessed here.
A list of my publications can be found here.
An example of my teaching philosophy and approach can be accessed here.

Blog Posts

Jan 2017 Identification and quantification of circular RNA from RNA-Seq data

Aug 2016 ALTRE: A Workflow for Identifying ALTered Regulatory Elements using Chromatin Accessibility Data

Written Candidacy Examination

Jun 2016 Statistical Modeling of fMRI Data; Dirichlet Process Models

fMRI Data Simulation

May 2016 Simulation of an fMRI Timecourse BOLD Response for a Single Voxel

Particle Filter

Feb 2016 Julia Code for a Particle Filter implementation of the Dirichlet Mixture Model

Nov 2015 Sparse Bayesian Group Factor Analysis

Oct 2015 Across-Subject Predictive Modeling of fMRI BOLD Responses to Faces

Bioconductor Main Classes Overview

May 2015 A quick summary of commonly used Bioconductor classes

Model Identification

May 2015 Identification Constraints in Factor Analysis Models

Bayesian Factor Analysis

Apr 2015 Fitting a Bayesian Factor Analysis Model in Stan

Model Identification

Apr 2015 An Overview of Model Identifiability in IRT and Factor Analysis Models

Apr 2015 Fitting a Multi-dimensional Item Response Theory Model in Stan

Mar 2015 Fitting a 2PL IRT Model in Stan