Lin Ma

Assistant Professor @UMichCSE.

[Lin Ma @Lin_Ma_]

Workload compression is crucial for database optimization—powering knob tuning, indexing, MV selection, and more. But most prior work targets OLAP with query-only methods.

In our new VLDB paper, we present SCompression, a time-sliced workload compression technique for OLTP. The key idea: don’t just choose which queries to keep—preserve concurrency and transaction context so the compressed trace still reflects real system behavior.

On a knob-tuning task across real-world and benchmark workloads, SCompression accelerates tuning up to 40× with only ~5% performance impact.
Paper: https://t.co/nghkvQaVmA

This work was led by visiting PhD student in our group, Baoqing Cai, who will present it at VLDB soon. Happy to discuss—online or in person!

[Lin Ma @Lin_Ma_]

Honored to receive a Google ML & Systems Junior Faculty Award! Grateful for @Google's support as our young lab advances AI- and GPU-driven database systems. This support and recognition will help us turn new ideas into open-source tools and a faster, smarter data infrastructure. Huge thanks to my students and collaborators—their creativity and hard work made this possible.

https://t.co/ntsCYIz21b

#GoogleResearch #MLSystems #GPUDatabases #AI

[Lin Ma @Lin_Ma_]

Thrilled to share that our project "Accelerating Large-Scale Data Analytics with Multi-GPU Resource Redistribution" in collaboration with @TalatiNishil, has been selected for the @nvidia Academic Grant Program (https://t.co/BblEAV8YNU)! 🚀

Shout-out to @NVIDIAAIDev for their generous allocation of A100 GPU hours! These resources will supercharge our research on GPU-accelerated databases and help us push the boundaries of large-scale data analytics.

#NVIDIAGrant #GPU #A100 #DataAnalytics #GPUDatabases

[Lin Ma @Lin_Ma_]

GPU memory capacity and I/O bandwidth limitations have been major bottlenecks for GPU-accelerated databases. We tackle such a challenge in our latest @VLDBconf 2025 paper: https://t.co/ATzbQgtQL6

We present a novel resource-sharing method for multi-GPU systems that enables GPU acceleration on datasets that far exceed GPU memory capacity, without relying on GPU-side data caching. The main idea is to repurpose underutilized IO resources from AI workloads to accelerate data movement for data analytics. Our approach delivers over 2x better price-performance than CPU-based solutions. This work is led by Yichao Yuan (@UMichCSE PhD student) in collaboration with @TalatiNishil.

We will be presenting this at VLDB 2025 in London later this summer. Hope to see you there!

[Andy Pavlo (@andypavlo.bsky.social) @andy_pavlo]

Buckle up because we're crashing into the new year with my annual database retrospective: License change blowbacks! @databricks vs. @SnowflakeDB gangwar! @DuckDB shotgun weddings! Buying a college quarterback with database money for your new lover! https://t.co/NnFHGElFNy

[Sudipto Das @sudiptdas]

The ⁦@SIGMODConf⁩ 2023 conference program is now posted online. We have a packed program. Early registration deadline is May 1st. Looking forward to seeing you all in person in Seattle in June. https://t.co/jGthb6BGGA

[Lin Ma @Lin_Ma_]

@anuragtiwari5 @UMichCSE Not right now, unfortunately.

[Lin Ma @Lin_Ma_]

I'm recruiting PhD students for my lab @UMichCSE on applied ML for databases, starting Fall 2023. My research and industry experience convinces me that database automation and simplification are more important than ever, and ML/AI can play a big role. Please apply and reach out!

[Lin Ma @Lin_Ma_]

@tech31842 @UMichCSE Sure! Maybe you can start with this summary blog from @andy_pavlo: https://t.co/AiuTOHlIEq
Some early and recent work from @MSFTResearch:
https://t.co/PeMNVeXgyx
https://t.co/7MDT9yjFEn
Or just reference my PhD thesis on self-driving databases:)
https://t.co/rTxZ9umiRz

[Lin Ma @Lin_Ma_]

@iDoswi1 @UMichCSE Thanks! Just the regular UMich CSE graduate admission with my name in the application: https://t.co/mmWFD1S2k3

[Lin Ma @Lin_Ma_]

@wallace_shw @UMichCSE @UMich Thanks for the pointer! I'll take a look.

[Lin Ma @Lin_Ma_]

Personal update: I'll be joining the University of Michigan, Ann Arbor in the Division of Computer Science and Engineering @UMichCSE as an Assistant Professor in Fall 2023! Thrilled to work on exciting database research with everyone at @UMich!

[Lin Ma @Lin_Ma_]

Just to add that, as part of this transition, I recently joined @databricks to work on the Delta Lake/Lakehouse. I've moved to Ann Arbor, but will visit the DB SF/SV office periodically. Look forward to hanging out and collaborating with friends both in A2 and the bay area:)

[Lin Ma @Lin_Ma_]

Personal update: I'll be joining the University of Michigan, Ann Arbor in the Division of Computer Science and Engineering @UMichCSE as an Assistant Professor in Fall 2023! Thrilled to work on exciting database research with everyone at @UMich!

[Lin Ma @Lin_Ma_]

@RyanMarcus @CIS_Penn Congrats, Ryan!

[Lin Ma @Lin_Ma_]

Thanks a lot for all the pointers! I'm keeping all options open right now, but I'm interviewing for academic positions first.

[Lin Ma @Lin_Ma_]

It's official! I'm on the job market!
My research is on the intersection of databases and machine learning. I've spent the last five years working on the NoisePage self-driving DBMS project at CMU.

Please find my C.V. and research/teaching statements at: https://t.co/57pqnXEMbJ

[Lin Ma @Lin_Ma_]

.@CMUDB Intro to Database Systems 2021 ➜ Lecture #23: Distributed OLAP Database Systems
Video: https://t.co/qW9X9zXBSS
Slides: https://t.co/ojPQGlRwMu

Execution models, query planning, and distributed join algorithms.

[Lin Ma @Lin_Ma_]

.@CMUDB Intro to Database Systems 2021 ➜ Lecture #22: Distributed OLTP Database Systems
Video: https://t.co/hGxpbEOVo2
Slides: https://t.co/ekTsK1xhoH

Commit protocol, replication, and CAP theorem.

[Lin Ma @Lin_Ma_]

.@CMUDB Intro to Database Systems 2021 ➜ Lecture #21: Introduction to Distributed Databases
Video: https://t.co/HMDOyAB0WZ
Slides: https://t.co/GKOXgDY0gT

Architecture and partitioning.

[Lin Ma @Lin_Ma_]

.@CMUDB Intro to Database Systems 2021 ➜ Lecture #20: Crash Recovery Algorithms
Video: https://t.co/7mz2cca7vc
Slides: https://t.co/OKdbg226Hf

Checkpointing and ARIES.