2022 SIGMOD Jim Gray Doctoral Dissertation Award

Chenggang Wu is Co-founder and CTO at Aqueduct, a SaaS startup building machine learning prediction infrastructure. He received his Ph.D. in 2020 from UC Berkeley, advised by Joseph M. Hellerstein. He is the recipient of best-of-conference citations for research appearing in both VLDB 2019 and ICDE 2018. He frequently serves as a PC member and a reviewer for conferences and journals such as SIGMOD, ICDE, VLDBJ, and TKDE. Chenggang’s Ph.D. dissertation develops design principles for building serverless infrastructure that can achieve excellent performance, seamless scalability, and rich consistency guarantees. The dissertation proposes two key ideas that are fundamental to achieving the combination of these goals: lattice-based coordination-free consistency, and LDPC (logical disaggregation with physical colocation). These ideas are validated via formal guarantees for consistency, and via performance and scaling results from implementations in the Anna key-value store and the Cloudburst serverless computing system. The dissertation also demonstrates applications to fields such as machine learning model serving, social networking, and robotics. This work tackles timely and challenging problems in distributed data management, and with lessons for both researchers and practitioners.

Kexin Rong is a postdoctoral researcher in the VMware Research Group and an incoming assistant professor in the School of Computer Science at Georgia Institute of Technology. Her research focuses on improving the efficiency and usability of large-scale data analytics, supporting applications including scientific analysis, infrastructure monitoring, and analytical queries on big data clusters. She received a best-of-conference citation at SIGMOD and was selected as a Rising Star in EECS by UC Berkeley. She received her Ph.D. in Computer Science from Stanford University in 2021, advised by Peter Bailis and Philp Levis.

Pingcheng Ruan received his Ph.D. in 2022 at School of Computing, National University of Singapore. Advised by Beng Chin Ooi, Pingcheng is broadly interested in blockchains, databases, and all data processing systems. Through his Ph.D. study, he devotes his efforts to transitioning database techniques to improve blockchains. His dissertation “Blockchains: Novel Data Systems and Beyond” is the culmination of his 5-year Ph.D. work. Pingcheng’s works have received vast recognition from the database community. He is the winner of the VLDB 2019 Best Paper Award and the SIGMOD 2020 Research Highlight
Award.