Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet.

Intelligent Information Systems, Language Technologies Institute, School of Computer ScienceCoursework: • Machine Learning • Machine Learning with Large Dataset • Language & Statistics • Introduction to Computer Systems • Deep Reinforcement Learning & Control • Machine Translation • Parallel Computer Architecture & Programming • Computer Vision • Neural Networks for NLP

Carnegie Mellon University

Shanghai Jiao Tong University

Wuhan University

Software Engineer

• Design, implement and operate the internal infrastructure for machine learning.

• Led the architecture and implementation of an in-house machine learning platform that streamlined the entire end-to-end process, including data ingestion and pre-processing, model training and optimization, performance evaluation, and continuous model deployment.
• Developed and implemented image similarity models for retail items using semi-supervised learning techniques to overcome noisy labels, resulting in a 12% improvement in F1 score compared to competitor's classification approach.
• Optimized input pipelines for large datasets by leveraging Bigtable, achieving a 2x speedup for model training.

Senior Software Engineer

• Designed and implemented rstream, a stream processing library that supports automatic state persistence and failure recovery with reference counting
• Enhanced in-house tracing infrastructure around gRPC and Kafka, making profiling and debugging more accessible across services
• Developed event-sourced microservices for data ingestion and aggregation
• Developed and maintained CI/CD pipelines on Azure DevOps for production services
• Implemented libraries and development tools to support remote debugging for production services (written in Node.js or Python) on Kubernetes, and significantly shorten troubleshooting time for several production issues

• Built a system detecting landing page cloaking (showing reviewers benign pages, but redirecting users to other malicious pages), and the system enforced 130K+ Ads within the first week of its release with a 0.04% false positives rate 
• Developed a time-windowed counter service processing 12K log events sampled from mobile clients in real-time and aggregated the events to high-level features for cloaking detection

Software Engineer Intern

• Worked on mining aligned code and natural language pairs from Stack Overflow posts with hand-crafted features and attention-based neural machine translation models
• Built a Flask-based website assisting professional programmers to annotate parallel data from Stack Overflow posts for model evaluation purposes

Research Assistant

• Developed Cosmos pipelines analyzing large scale (TB-level) semi-structured transactional logs from Microsoft Azure and Office 365, and helped the product teams caught several system failures in their early stage
• Analyzed performance characteristics of distributed jobs for log analysis, identified performance bottlenecks caused by poor data locality and redundant computation, and performed optimization archiving 10x speedup
• Designed an extendable log analysis framework and integrated several existing log-analysis algorithms into the framework

Research Intern

• Ran recitations and office hours for Foundation of Algorithm course
• Developed a productivity tool to retrieve hand-out submissions from e-mail based on their content

Teaching Assistant

• Developed a debugger for XAML Workflow (a domain-specific language for business logic modeling) with breakpoints, variable inspection, and execution history, making the development and troubleshooting of XAML Workflow more efficient
• Ported several administrative interfaces of Exchange 14 to the new MVVM framework of Exchange 15

• Reverse-engineered the private protocol of Sina Weibo from its Mobile Client
• Implemented a distributed crawling system for Sina Weibo based on the private protocol
• Developed a task scheduler using Redis to support incremental crawling and real-time updating