Alekh has spent his career blended in academia and industry, propelling award-winning ideas from conception to adoption. His work includes the first MapReduce implementation with performance matching that of parallel DBMSs during his PhD, efficient graph analytics on column stores that outperforms specialized graph systems during his rese

Alekh has spent his career blended in academia and industry, propelling award-winning ideas from conception to adoption. His work includes the first MapReduce implementation with performance matching that of parallel DBMSs during his PhD, efficient graph analytics on column stores that outperforms specialized graph systems during his research at MIT, and learning-based workload optimization for cloud query engines at Microsoft, where he was also driving workload optimization work stream in Azure Data. Most recently he was founding Chief Architect, CTO, and board member at Keebo, where he built a data learning service for cloud data warehouses and helped the company go from 1 to n. Alekh has co-authored 80+ papers, filed 15 patents, and won 4 best paper awards. He has served on the program committee of several leading database conferences.

Shi has spent the last decade building advanced data processing engines that are efficient and performant. He received his PhD from Case Western working on graph analytics. Later he joined Microsoft where he has a track record of building and shipping several industry firsts in the broader area of workload optimization, including automati

Shi has spent the last decade building advanced data processing engines that are efficient and performant. He received his PhD from Case Western working on graph analytics. Later he joined Microsoft where he has a track record of building and shipping several industry firsts in the broader area of workload optimization, including automatic query subexpression reuse, learned cardinality estimation, petabyte scale data shuffle, predictive resource allocation, and predictive query planning. Shi’s work has helped Microsoft save millions of dollars of operational cost. He has a rich experience in applying AI/ML for system problems and in making learning-based automations practical for a cloud environment. Most recently, Shi was the Head of Engines at Keebo, building the next generation platform-agnostic query processing capabilities.