Data Scientist with Advanced Degrees. Extensive experience in Programming and Statistical Data Analysis using R, Matlab, SPSS and Python. Led complex data-analytic projects from problem definition to dissemination. Track record of Publications with over 100 citations. Speaker at numerous large International Conferences. Passionate about Statistical Data Analysis, Modeling and Visualization combined with ability to clearly and effectively tell a data-driven story that can be easily understood. 



Machine Learning

Linear regression, logistic regression, reinforcement learning, regularization, k-means clustering, bootstrapping, cross-validation, model selection/validation, simulations

Statistical Data Analysis

Exploratory data analysis, parametric and non-parametric statistics, factorial and multivariate statistics

Programming (R, Matlab, Python, Javascript, C)

Strong programming skills. Also experience with IPython, Interactive Data Language, SQL, Shell Scripting and Perl

Data Visualization and Presentation

R, ggplot2, Matlab, Illustrator, Photoshop, Keynote and PowerPoint

Data-driven Problem Solving

Define problem, learn knowns, design experiment, collect and analyze data, use models and common sense to find best answers


Published Author, Conference Presenter, Competent Communicator (Toastmasters),  Visual Story-teller, Listener

Work History

Work History

Research Associate

Apr 2015 - Present
Stanford University
  • Achievements: Discovered previously undetected biases in human decision making by applying novel probabilistic models. Pioneered understanding how humans adapt their unconscious decision biases. Presented data analysis results at Stanford and published in international journals.
  • Led project to build probabilistic models to predict human behavior and correct for their decision making errors
  • Used regularized logistic regression (L1 & L2) for variable selection and overfitting prevention  
  • Employed multivariate linear regression for performance assessment
  • Utilized unsupervised learning (k-means) to cluster response times
  • Validated and selected models using log-likelihood testing, cross-validation and information-theoretic approach
  • Extensively used parametric and non-parametric statistics
  • Wrote R package for modeling, simulation and data analysis of human decision making errors (
  • Wrote Matlab scripts for data collection and analysis
  • Learnt Javascript and Python to program experiments for Amazon's Mechanical Turk (
  • Led and collaborated on complex projects with teams located in three different countries

Postdoctoral Researcher

Jun 2012 - Mar 2015
RIKEN Brain Science Institute, Japan
  • Achievements: Discovered how human decision speeds are affected by their expectations. Used reinforcement learning and probabilistic models to analyze human unconscious decision making. Developed software for data collection and analysis in the brain scanner.  Published research findings and presented results at five large conferences.
  • Led project to model and analyze human decision making
  • Fitted reinforcement learning models (Q-Learning) to predict human choices (
  • Fitted and tested various regularized probabilistic choice models
  • Built complex experiments in Matlab for accurate data collection and processing (
  • Used R Markdown for reproducible data analysis (

Postdoctoral Research Associate

Jun 2008 - May 2012
University of Sydney, Australia
  • Achievements: Pioneered a novel method for boosting the human vision through brain stimulation. Created a new data-driven methodology and software for accurate brain stimulation. Published three research papers in flagship international journals and presented research results at eight large conferences.
  • Built Matlab GUI based toolbox that used Bayesian model and information theory for accurate data-driven brain stimulation (
  • Developed Matlab toolbox to control brain stimulator via serial port (
  • Used linear and quadratic regressions for statistical analysis and inference
  • Conducted exploratory data analysis in R
  • Played a lead role in establishing a research laboratory for data collection and analysis (

Software Developer

Mar 2000 - Oct 2003
RIKEN Brain Science Institute, Japan
  • Achievements: Developed data analysis software for research scientists to enable novel, powerful and in-depth data analysis. Those methods resulted in novel findings and publications with higher impact. Administered computer and network systems for effective access and analysis of large volumes of data enabling scientists to analyze previously impossible volumes of data. 
  • Designed and implemented software for data analysis of multi-variate time series using cutting-edge methods such as mountain clustering, information discrepancy and wavelet analysis 
  • Developed data analysis software for processing of biometric time series using Interactive Data Language
  • Wrote Perl scripts for processing and manipulating large data files (
  • Extensively used shell script for handling large number of big data files
  • Administered small network of Unix and Windows based computers
  • Installed, configured and maintained Unix servers with large storage capabilities to store big data



Ph.D. in Experimental Psychology

Western Sydney University

Brain and Behavioral Studies of Emotion and Attention Interaction

M.S. in Applied Mathematics 

Yerevan State University

Thesis Passed with High Distinction

Additional information

  • List of publications and presentations is available upon request