San Francisco, California, US

Cofounder and VP Engineering
VILAS's Skills
Large-scale Data Analysis
Data Science
Artificial Intelligence
Machine Learning

Startup Experience

First time founder

Age Group



Developed scalable machine learning models using Artificial Neural Networks (CNN, RNN, LSTM), Random Forest, Gradient Boosting, Principal Components Analysis and Partial Least Squares. Use cases include natural language processing, computer vision, time series forecasting, recommendation engines, real-time process control and optimization.

Work Experience

Machine Learning Engineer

American Express

August 2018 - Today

Develop state-of-the-art machine learning algorithms for fraud detection, natural language processing, computer vision, sentiment analysis, and recommendation engines

Applications Scientist

MKS Instruments

December 2012 - July 2018

Implemented and optimized models based on Principal Components and Partial Least Squares to predict physical properties of oil and natural gas samples in real-time Proficient at model diagnostics, evaluation and hyper-parameter tuning to optimize model performance Developed data acquisition and post-processing software for real-time oil and gas analysis system Interpreted statistical methodologies and results to non-statisticians in a multidisciplinary research team/environment Significant contribution towards the growth and success of a startup company (Precisive LLC), which was acquired by the current employer

Research Assistant

North Carolina State University

December 2008 - November 2012

Implemented and optimized Principal Components Analysis based pattern recognition model to identify geographical source of a gasoline sample from its Infrared spectrum Outlier detection using Hotelling’s T2 statistic based on Mahalanobis distance Performed MANOVA analyses, Design of Experiments, variable selection in multivariate analysis/modeling, recommended applicable ML algorithms and communicated the results through generation of technical reports Cleaned and analyzed large and complex data sets Ability to rapidly understand, implement and modify state-of-the-art machine learning algorithms described in research papers

Software Engineer

Accenture Technology Pvt Ltd

June 2006 - August 2008

Write and execute test scripts to validate software requirement specifications for Siebel based customer relationship management applications Programming in C, C++, Java and SQL to support web based financial applications


North Carolina State University, Raleigh, NC


2008 - 2012