Lin Ma

Lin Ma is currently an Assistant Professor at the University of Michigan, Ann Arbor in the Department of Electrical Engineering and Computer Science (College of Engineering). Previously, they served as a Post Doctoral Fellow at Carnegie Mellon University (2021-2022) and as a Software Engineer at Databricks, Inc. (2022-2023).

Research Interests focus on the intersection of database systems and machine learning, particularly in developing self-driving database management systems. Key areas include workload forecasting, automated index optimization, query execution acceleration, and machine learning integration for database automation. Their work explores GPU-accelerated analytics, memory optimization, and transactional consistency models.

Academic Contributions span 15+ publications in top venues like VKDB, SIGMOD, and CIDR, including recent 2025 papers on Vortex (GPU memory optimization) and Scompression (workload compression). Earlier work introduced QueryBot 5000, a workload forecasting framework, and explored anti-caching for storage optimization in OLTP systems.

Teaching includes courses like EECS 584: Advanced Database Management Systems and EECS 484: Database Management Systems at the University of Michigan (2023-2025), and 15-445/645 Database Systems at Carnegie Mellon University.

Service involves program committee roles for SIGMOD (2023-2025), VLDB (2022-2025), and CIDR (2024-2025). They also served on admissions and search committees at both institutions.

Advising includes supervising PhD and MS students: Siyuan (Doug) Dong, Zhongwei Xu, and Haotian (Jack) Gong (co-advised with Barzan Mozafari), among others.