# Junhan Ouyang

> Reliable High Performance Real Time Service

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/junhan

## Work Experience
### Site Reliability Engineer @ Verkada
Jan 2026 – Present | San Mateo, California, United States
High Availability Infra

### Software Engineer II (Infra/application) @ DataVisor
Jan 2024 – Jan 2026
- Owned the end-to-end design and deployment of the AML Compliance eFiling module in Java Spring Boot, building a dynamic validation framework with annotations and AOP that streamlined complex compliance workflows and reduced maintenance overhead.
- Optimized large-scale databases (Yugabyte, ClickHouse, MySQL) powering fraud detection pipelines at 500+ QPS, improving query latency and reliability under production load.
- Implemented dynamic scaling strategies for Spark and Flink clusters, reducing compute costs by ~30% while maintaining high throughput for UML batch pipelines.
- Enhanced observability by integrating OpenTelemetry with DeepFlow (eBPF-based), enabling distributed tracing and reducing incident mean-time-to-resolution (MTTR).

### Software Engineer (Infra) @ DataVisor
Jan 2022 – Jan 2024 | Mountain View, California, United States

### Undergraduate Research Assistant @ Intelligent Dynamics Lab
Jan 2021 – Jan 2023 | Irvine, California, United States
Using machine learning to generate circuit design given properties requirement

### Undergraduate Deep Learning Research @ UC Irvine School of Medicine
Jan 2021 – Jan 2023
Train machine learning models to predict glaucoma surgery outcomes
Implement U-Net to do semantic segmentation and different types of CNN architecture like ResNet, CapsNet to assist with the prediction
Use transfer learning, hyperparameter tuning, cross validation to check and improve model performance
Establish a modular, scalable training pipeline including data labeling, data preprocessing, model training and model evaluation

### Undergraduate Data Science Research @ UC Irvine
Jan 2021 – Jan 2022
Build open-source data pipelines (including ETL, data wrangling, feature engineering, etc.) for learning management system (Canvas LMS) 
Use statistical analysis, clustering, multiple regression analysis to predict and analyze student course performance


## Education
### Bachelor's degree in Computer Science
UC Irvine
Jan 2018 – Jan 2022

### Bachelor's degree in Economics
UC Irvine
Jan 2018 – Jan 2022


## Contact & Social
- LinkedIn: https://linkedin.com/in/junhan-ouyang-136094199

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Source: https://flows.cv/junhan
JSON Resume: https://flows.cv/junhan/resume.json
Last updated: 2026-03-20