ACM SIGMOD is pleased to present the 2021 SIGMOD Jim Gray Doctoral Dissertation Award to Huanchen Zhang.

Huanchen Zhang is an Assistant Professor in the IIIS department at Tsinghua University. He received his Ph.D. in 2020 at Carnegie Mellon University, advised by Dave Andersen and Andy Pavlo. He is broadly interested in database systems, with particular interests in indexing, data compression, and cloud databases. He is the recipient of the 2018 SIGMOD best paper award. His dissertation was titled “Memory-Efficient Search Trees for Database Management Systems”. It focuses on search trees and the growing gap between storage and memory (both in terms of cost and capacity). His work looks at methods to make tree representations and operations more efficient for space and latency. Given the current environment of continued data growth and analysts wanting to make the most of their resources, Huanchen’s work is timely and important. The work tackles critical issues facing data systems today, draws from recent trends and classical approaches, clearly outlines limitations, shows great performance improvements for target use-cases, shows theoretical limits, contains excellent optimizations, and is built in real and complex systems.

ACM SIGMOD is also pleased to recognize Erfan Zamanian, Maximilian Schleich, and Natacha Crooks for Honorable Mention for the 2021 SIGMOD Jim Gray Doctoral Dissertation Award.

Erfan Zamanian received his PhD from Brown University in Computer Science in 2019, advised by Tim Kraska for his work on high-performance transaction processing on modern networks, with Carsten Binnig from TU Darmstadt as an additional mentor and collaborator. His papers were among the best of SIGMOD. He received the ACM Research Highlight Award in 2020. He obtained a master’s degree from ETH Zurich, Switzerland, where he was granted the Excellence scholarship, and a bachelor’s degree from Sharif University of Technology, Iran. He is currently a software engineer in the platform architecture and data infrastructure team at eBay.
Maximilian Schleich is a Postdoctoral Scholar in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. He received his PhD from the University of Oxford in 2020, under the supervision of Prof. Dan Olteanu. He also spent time at RelationalAI, which now generously funds his Postdoc. His research lies at the interface of databases and machine learning. In particular, he investigates the design and implementation of novel data analytics systems from the perspective of data management, with the goal of making machine learning more practical, scalable, and transparent.
Natacha Crooks is an Assistant Professor at UC Berkeley. Her research lies at the intersection of databases, distributed systems, and more recently security. She focuses specifically on designing large-scale transactional systems with strong correctness and security properties. She was previously a PhD student at the University of Texas at Austin where she was advised by Lorenzo Alvisi for her dissertation: A client-centric approach to transactional datastores. During that time, Natacha was fortunate enough to spend significant periods of time at Cornell University, MPI-SWS and Cambridge University.