Lin Ma
Assistant Professor at University of Michigan
Ann Arbor, Michigan, United States
Summary
🤩
Rockstar🎓
Top SchoolLin Ma is an assistant professor and researcher with 11 years of experience at the intersection of database systems and machine learning, focused on automating DBMS administration using ML/AI techniques. She built and evaluated autonomous DBMS architectures during her PhD at Carnegie Mellon, contributing core telemetry, metrics, and execution instrumentation to the noisepage self-driving database. Before academia she worked on Delta Lake at Databricks, improving data skipping and stats collection for a widely used open-source Lakehouse storage framework, and contributed performance and monitoring features to Peloton and H-Store. Based in Ann Arbor, she blends rigorous systems-building with practical test automation and has a track record of turning research prototypes into production-ready tooling. Her work often surfaces subtle infrastructure insights—like aligning stats schemas to table order to improve usability—that reflect a pragmatic focus on observability and long-term operability.
11 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Peking UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Carnegie Mellon University
Github Skills (27)
spark10
c-language10
delta-lake10
data-collection10
testing10
databases10
big-data10
java10
scala10
javas10
sql10
performance-optimization10
dbm10
collections10
cprogramming-language10
Programming languages (4)
Github contributions (5)
cmu-db/peloton
May 2016 - Apr 2018
The Self-Driving Database Management System
Role in this project:
Back-end Developer / Database Engineer
Back-end Developer / Database EngineerContributions:435 commits, 107 PRs, 81 pushes in 2 years
Contributions summary:Lin's commits focus on implementing and modifying database-related features within the Peloton database management system. They contributed to the registration process of the backend_stats_context to the StatsAggregator and introduced new metrics such as counter metrics. The user also worked on adding an aggregation thread to enhance the collection of database statistics, including code for throughput measurement and logging. The work demonstrates contributions to core database functionality.
management-systemrdbmsdatabase-management-systemself-drivingdatabase
cmu-db/noisepage
Mar 2020 - Jul 2021
Self-Driving Database Management System from Carnegie Mellon University
Role in this project:Back-end Developer & Database Engineer
Back-end Developer & Database EngineerContributions:196 reviews, 33 commits, 85 PRs in 1 year 4 months
Contributions summary:Lin primarily contributed to the development and optimization of the database system. Their work focused on enhancing the metrics collection and reporting infrastructure, including the addition of various counters and sampling mechanisms. They also introduced and modified code related to table generation, query execution, and the integration of execution metrics. The user's contributions demonstrate a focus on performance and monitoring within the database management system.
management-systemdbmsdatabase-management-systemcarnegie-mellon-universityself-driving
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