May 2021 – Dec 2023 · 2 yrs 7 mos

• - Led fraud detection project for customer returns resulting in annual savings of $75M for FY24.

Jul 2019 – May 2021 · 1 yr 10 mos

• Deployed a Deep Learning solution for Automated Display Testing at the factory line.
• Utilized Predictive Modeling to reduce test time, resulted in $2.5M savings in cost.
• Introduced a novel testing solution: combining Augmented Reality and Deep Learning.
• Shadow Board Member @Microsoft (we update the leadership with future tech)

Jul 2019 – Present · 6 yrs 8 mos

• Define company-wide data and AI strategy
• Automate retinal image analysis using AI Agents
• Explore DR stage classification with advanced AI models
• Build end-to-end data analysis platform
• Lead AI team to register multi-wavelength retinal images using deep learning

Mar 2016 – Feb 2025 · 8 yrs 11 mos · San Francisco Bay Area · Remote

• Courses: "Intro to Data Science", "Applied AI", "Programming in Python" and "Programming in R"
• I've trained 2000+ students in the data science and machine learning field at Stanford.

Jan 2015 – Jan 2019 · 4 yrs · San Francisco Bay Area

• Deployed end to end predictive models at the factory line
• Developed gesture classification models on Apple Watch
• Finalist at Apple's IDEA competition in 2017

Sep 2014 – Dec 2014 · 3 mos · San Francisco Bay Area

• Classification of multi-dimensional sensors in wearable devices.

Jun 2014 – Sep 2014 · 3 mos · Silicon Valley

• Clustering Analysis, Predictive Modeling and Pattern Mining in Energy Disaggregation
• Prescriptive Analytics in Sales and Marketing

Mar 2014 – Jun 2014 · 3 mos · Riverside, CA

• I was the instructor for CS150, The Theory of Formal Languages and Automata.

Jun 2013 – Sep 2013 · 3 mos · New York

• Big Data analysis for Wind Turbines at the Machine Learning Lab. I analyzed different methods for predicting performance changes in wind turbines.

Oct 2012 – Dec 2013 · 1 yr 2 mos

• Data Analysis in Brain Stroke, School of Medicine

Sep 2012 – Sep 2013 · 1 yr