I am focusing on how to optimize core monetization products, including systems and models, to maximize ads value to advertisers on Meta platforms and applications. Working on a system at Meta scale is always challenging but fun. It's super meaningful to support 3 billion users and millions of advertisers.

Building super scalable and efficient AI/ML platforms and tools that support large scale model training, model serving/inferencing, and ML Ops.

Worked on some of the most challenging engineering and data science projects in social networking with 3 ExaBytes hugely valuable data. Proud to lead efforts in building top tier super scalable AI and data infrastructure.

Built a scalable data streaming and transformation platform, leveraging Kafka, Spark and HDFS, that processes 1T events daily and that generates 2K core data assets for ML and Analytics.

Founded and grew Data Integration Library open source project (https://github.com/linkedin/data-integration-library) for LinkedIn's large scale external data integration demand. Data Integration Library (DIL) replaces connectors with flexible integration components; it is much more efficient in addressing the variety challenge of Big Data ecosystem and provides dramatically reduced TTM (Time to market) to business needs.

Built influential machine learning and predictive analytics solutions for 3 Fortune 100 companies in the Sales and Marketing operations; positively influenced sales and marketing strategies of annual $5 billion operations by providing effective marketing segmentation and targeting tools and algorithms.

Contributed core technology to Siebel Analytics in data mining and query optimization; developed Oracle BI application package for 7 industries including 30 business function areas; implemented Oracle BI applications for marketing campaign performance and sales analytics.