Developer and maintainer of• Presto router (https://github.com/prestodb/presto/tree/master/presto-router)• Presto-Iceberg connector (https://github.com/prestodb/presto/tree/master/presto-iceberg)• Presto ML-based query predictor (https://github.com/prestodb/presto-query-predictor)

• Identified traffic patterns and proposed cache strategies for data analytics (SQL) and machine learning workloads. Our talk at Data + AI Summit 2023: https://youtu.be/wgr5Kdqa52Y• Led a unified cloud-native data access solution with Alluxio for end-to-end machine learning pipelines, which overcomes I/O challenges and improves GPU utilization to 90%+ in enterprise-grade ML workloads.- Led the collaboration with Uber on the adoption of caching to improve data analytics (Presto) & machine learning training (Ray) performance and cost efficiency.

Tech lead of Twitter's Presto and Zeppelin, helping evolve Twitter's SQL federation system into a world-class large-scale system that processes ~10 PB of data daily. Also led and contributed to other cross-team or cross-functional projects, spanning a wide range of data systems, including BigQuery, Druid, and Spark/Neo4j for graph analytics.Presto• Led Twitter's Presto federation (10+ Presto clusters with 3000+ nodes, processing ~10 PBs of data daily).• Drove the project of creating an end-to-end machine learning pipeline learning from request logs to forecast resource usages (92%+ accuracy) of SQL queries of Presto and storing data exploration jobs in JupyterLab. • Contributed to the router and scheduler to improve system performance (P99 query queued time decreased by 90%).BigQuery• Worked on the low-code ML project to advocate using BigQuery ML to simplify ML pipelines on multiple components such as model training and feature store. Helped re-build Twitter's notification ML models and reduce the dislike rate by 2+%.Zeppelin• Led Twitter's Zeppelin notebook service (~400 weekly active users).• Drove the migration of on-premises Twitter's Zeppelin, to Kubernetes in the cloud (GCP) in a move-and-improve strategy.Druid• Worked on a unified ingestion web service for Apache Druid, a real-time analytics database, to manage data ingestion jobs.Graph Analytics• Contributed to the company-wide graph analytics project and evaluated a hybrid architectural design with Spark and Neo4j for next-generation large-scale graph analytics.

• Participated in designing Huawei large scale mobile-edge-cloud synchronization and collaboration data platform.• Implemented an MBaaS (Mobile backend as a service) layer on top of heterogeneous data stores (table store, object store, etc.) to enforce the strong consistency of CURD operations on composite data objects.

Google Summer of Code at Jitsi• Developed face recognition/tracking feature for Jitsi-Meet, a simple and scalable video conferencing web application, implemented in React and Redux.• Integrated Google Calendar feature in Jitsi-Meet Electron application.