• Experience in back end features and services implementation • Experience in data cleaning, data mining, and data visualization • Experience in multiple machine learning models development • Experience in giant company, unicorn, and early stage starups

Experience

2019 — NowUberSoftware Engineer (Intelligence Dispatch)

2019 — Now

San Francisco, CA

Algorithm Optimization for Continuous Dynamic Driver-Rider Matching:

Develop scanning service to identify sub-optimal decisions for headroom analysis and possible better matching plan update.

Optimize dispatching mechanism by switching entity supplies

injection strategy leading to 2% fulfillment rate increasing.

Geo-Data Shadow Payload Environment Development for Staging Test:

Establish shadow environment by injecting dynamic percent replicated production traffic payload into shadow pod.

Intercept 97% production deployment issues by collecting code commits and streaming with shadow payload regularly.

2018 — 2019AppleSoftware Engineer (Location / Motion)

2018 — 2019

Cupertino, CA

Automation of Massive Spatiotemporal Data Enrichment and Visualization:

Enriched surrounding info based on spatiotemporal data from JSON format Google Earth KML files for following visualization. • Implemented screenshot feature to visualize aggregated target GPS data in Google Earth through keyboard/mouse simulation.

Error Aggregation Summary with Integrated Verification Data Pipeline:

Integrated multiple verification data pipelines including sensor fusion, motion gestures, and fitness tracking to a single one.

Developed automated GPS statistics visualization modules for integrated Geo-error analysis report with 95% time saving.

2017 — 2018HuaweiSoftware Engineer (Competence Center)

2017 — 2018

Santa Clara, CA

Simulated Cloud Deployment Optimization by Machine Learning Models:

Developed simulated Huawei Cloud modules and database schema based on hardware resources for deployment test.

Optimized system resources allocation via Gradient Boosting Tree and Random Forest models with 25% price reduction.

2015 — 2016E-Joule TechnologySoftware Engineer (Data Process Division)

2015 — 2016

Fremont, CA

Testing Data Prediction of Recipe through Machine Learning Algorithms:

Predicted batteries properties based on recipe formula with Polynomial Regression methods for following experiments.

Validate materials composition with 90% error reduction via K-Means Clustering and K Nearest Neighbors approaches.

Education

2015

Washington University in St. Louis

Master's degree

2015

Harbin Institute of Technology

Experience

Education

Master's degree

Bachelor's degree