# Juong-Sik Lee, Ph.D.

> Video, Search Ads, Big Data, RTB, Header Bidding, Auction, Game Theory, Bid, Yield, Floor Optimization, Mechanism Design, Marketplace Design, ML, Data Science, Deep Learning, Reinforcement Learning, AI, LLM, AI Agents.

Location: Palo Alto, California, United States
Profile: https://flows.cv/juongsik

- LLM, AI, AI Agent, Machine Learning, Deep Learning, Reinforcement Learning, Data Science
- CTV Advertising, Video Advertising, Display Advertising, Search Advertising
- Demand Side Platform (DSP), Supply Side Platform (SSP), Audience Platform, 
- Programmatic System, RTB (Real Time Bidding), Bidding Optimization and Optimal Winner Selection Mechanism.
- Auction Theory, Game Theory, Mechanism Design, Incentive Mechanism
- Marketplace Design
- Automated and Dynamic Pricing
- Mobile Services and Applications
- Mobile Sensing and Crowdsourcing
- Mobile Marketplaces and Ecosystem
- Location based Applications and Services

## Work Experience
### Staff Software Engineer @ Coupang
Jan 2018 – Present | Mountain View, California, United States
Leading projects and develop e-commerce related Ad Platforms and Audience Platforms.

- Developed centralized Audience Data Platform to ingest and process high-volume e-commerce event streams, creating a unified "single source of truth" for user behavior.
- Developed applications that leveraged audience telemetry to drive precision ad targeting, real-time
ranking, and personalized user experiences and recommendations.
- Developed a real-time bidding (RTB) engine for search and display advertising, leveraging Reinforcement Learning (RL) to optimize bid strategies in dynamic market environments.

### Senior Software Engineer @ YuMe by RhythmOne
Jan 2014 – Jan 2018 | Redwood City, CA
Led projects and develop end-to-end CTV and Video advertising platforms for high scale Supply Side
Platform (SSP) and Demand Side Platform (DSP) integrating Auction Theory, Game Theory, Simulation
based Optimization, and Machine Learning (Reinforcement Learning).

- Bidding Engine with Reinforcement Learning
- Auction Engine with multi attribute winner selection mechanism
- Header Bidding 
- Optimal Floor Price Recommendation System
- Yield Optimization System
- Bidding and Pacing Optimization
- Auction Simulator to verify auction strategy, bidding optimization and etc.
- Traffic Simulator (Ad request traffic and Bid request traffic) for n-to-n test of SSP (Supply Side Platform) and DSP (Demand Side Platform).
- Whitebox Test Framework for testing Bidding Engine, Pacing Engine and etc.

### Software Engineer II @ Microsoft
Jan 2012 – Jan 2014
Develop location based services for mobile devices (including mobile phones and tablets).

### Senior Researcher @ Nokia Research Center
Jan 2008 – Jan 2012 | Palo Alto CA
- Research and development innovative mobile solutions, services and applications for social network and applications, mobile collaboration, unified communications, location based services, mobile entertainment, mobile sensing and crowdsourcing, mobile commerce and ecosystem  using platform independent mobile web technologies and various mobile platforms.

- Creating project idea, developing robust mobile system, conducting pilot, field test and user study, creating intellectual property, publishing research results in major conferences and journals and technology transfer to business unit.


## Education
### Ph.D. in Computer Science
Rensselaer Polytechnic Institute

### Master of Science in Computer Science
Stevens Institute of Technology

### Bachelor of Engineering (B.E.) in Computer Science
Chung-Ang University


## Contact & Social
- LinkedIn: https://linkedin.com/in/juongsik

---
Source: https://flows.cv/juongsik
JSON Resume: https://flows.cv/juongsik/resume.json
Last updated: 2026-04-12