Portrait of Audrey Cheng

accheng@berkeley.edu

I am an incoming Assistant Professor of Computer Science at Stanford University, starting in Fall 2027. Currently, I am a visiting researcher at OpenAI. Previously, I was a PhD student in Computer Science at UC Berkeley in the Sky Computing Lab, advised by Ion Stoica and Natacha Crooks. My research focuses on optimizing performance for database systems. Recently, I have been co-leading an initiative on AI-Driven Research for Systems (ADRS) and run a blog series on these efforts. Please reach out if you are interested in featuring your work!

My research has been supported by an NSF Graduate Research Fellowship, a Meta PhD Research Fellowship, and a Berkeley Chancellor's Fellowship. I have been named a Rising Star in EECS. My research has also received a VLDB Best Industry Paper Award and invitations to the Best of VLDB journal. Previously, I graduated with a BSE from Princeton University.

I am looking for PhD students to join my group starting in Fall 2027! If you are interested, please reach out or mention my name on your application to the Stanford CS PhD program.

Publications

Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems
Shubham Agarwal*, Alexander Krentsel*, Shu Liu*, Mert Cemri*, Audrey Cheng, Rui Meng, Tomas Pfister, Chun-Liang Li, Sylvia Ratnasamy, Aditya Parameswaran, Matei Zaharia, Ion Stoica, Mohsen Lesani
Under submission PDF
AI-Driven Research for Databases
Audrey Cheng, Harald Ng, Aaron Kabcenell, Peter Bailis, Matei Zaharia, Lin Ma, Xiao Shi, Ion Stoica
Under submission PDF
AdaEvolve: Adaptive LLM Driven Zeroth-Order Optimization
Mert Cemri*, Shubham Agrawal*, Akshat Gupta, Shu Liu, Audrey Cheng, Qiuyang Mang, Ashwin Naren, Lutfi Eren Erdogan, Koushik Sen, Matei Zaharia, Alex Dimakis, Ion Stoica
Under submission PDF Code
EvoX: Meta-Evolution for Automated Discovery
Shu Liu, Shubham Agarwal, Monishwaran Maheswaran, Mert Cemri, Zhifei Li, Qiuyang Mang, Ashwin Naren, Ethan Boneh, Audrey Cheng, Melissa Z. Pan, Alexander Du, Kurt Keutzer, Alexandros G. Dimakis, Koushik Sen, Matei Zaharia, Ion Stoica
Under submission PDF Code
Let the Barbarians In: How AI Can Accelerate Systems Performance Research
Audrey Cheng*, Shu Liu*, Melissa Pan*, Zhifei Li, Shubham Agarwal, Mert Cemri, Bowen Wang, Alexander Krentsel, Tian Xia, Jongseok Park, Shuo Yang, Jeff Chen, Lakshya Agrawal, Ashwin Naren, Shulu Li, Ruiying Ma, Aditya Desai, Jiarong Xing, Koushik Sen, Matei Zaharia, Ion Stoica
Under submission PDF Code SIGOPS Blog Post
Barbarians at the Gate: How AI is Upending Systems Research
Audrey Cheng*, Shu Liu*, Melissa Pan*, Zhifei Li, Bowen Wang, Alex Krentsel, Tian Xia, Mert Cemri, Jongseok Park, Shuo Yang, Jeff Chen, Aditya Desai, Jiarong Xing, Koushik Sen, Matei Zaharia, Ion Stoica
Under submission PDF Code SIGOPS Blog Post
Fair Transaction Processing for Multi-Tenant Databases
Audrey Cheng, Aaron Kabcenell, Xiao Shi, Jolene Huey, Peter Bailis, Natacha Crooks, Ion Stoica
VLDB 2025, Invited to VLDB Journal on "Best of VLDB 2025" PDF Code
SkyStore: Cost-Optimized Object Storage Across Regions and Clouds
Shu Liu, Xiangxi Mo, Moshik Hershcovitch, Henric Zhang, Audrey Cheng, Guy Girmonsky, Gil Vernik, Michael Factor, Tiemo Bang, Soujanya Ponnapalli, Natacha Crooks, Joseph E. Gonzalez, Danny Harnik, Ion Stoica
VLDB 2025, Invited to VLDB Journal on "Best of VLDB 2025" PDF Code
Optimizing LLM Queries in Relational Workloads
Shu Liu, Asim Biswal, Amog Kamsetty, Audrey Cheng, Luis Gaspar Schroeder, Liana Patel, Shiyi Cao, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Matei Zaharia
MLSys 2025 PDF
Towards Optimal Transaction Scheduling
Audrey Cheng, Aaron Kabcenell, Jason Chan, Xiao Shi, Peter Bailis, Natacha Crooks, Ion Stoica
VLDB 2024 PDF Code
Mammoths are Slow: The Overlooked Transactions of Graph Data
Audrey Cheng, Jack Waudby, Hugo Firth, Natacha Crooks, Ion Stoica
VLDB 2024 PDF Code
Take Out the TraChe: Maximizing (Tra)nsactional Ca(che) Hit Rate
Audrey Cheng, David Chu, Terrance Li, Jason Chan, Natacha Crooks, Joseph M. Hellerstein, Ion Stoica, Xiangyao Yu
OSDI 2023, Meta Next-Generation Data Infrastructure Research Award PDF Code
TAOBench: An End-to-End Benchmark for Social Network Workloads
Audrey Cheng, Xiao Shi, Aaron Kabcenell, Shilpa Lawande, Hamza Qadeer, Jason Chan, Harrison Tin, Ryan Zhao, Peter Bailis, Mahesh Balakrishnan, Nathan Bronson, Natacha Crooks, Ion Stoica
VLDB 2022 PDF Code Meta Blog Post
RAMP-TAO: Layering Atomic Transactions on Facebook's Online TAO Data Store
Audrey Cheng, Xiao Shi, Lu Pan, Anthony Simpson, Neil Wheaton, Shilpa Lawande, Nathan Bronson, Peter Bailis, Natacha Crooks, Ion Stoica
VLDB 2021, Best Industry Paper Award PDF Talk Meta Blog Post
Ownership: A Distributed Futures System for Fine-Grained Dynamic Tasks
Stephanie Wang, Eric Liang, Edward Oakes, Benjamin Hindman, Frank Sifei Luan, Audrey Cheng, Ion Stoica
NSDI 2021 PDF
Gryff: Unifying Consensus and Shared Registers
Matthew Burke, Audrey Cheng, Wyatt Lloyd
NSDI 2020 PDF Code

Talks

"How AI is Disrupting Systems Research"
  • KTH AI Systems Workshop (Stockholm, Sweden): Mar. 2026.
  • Meta Datacenter Optimization Team (Menlo Park, CA): Feb. 2026.
  • UCSD DSC204A Guest Lecture (Online): Nov. 2025.
  • UC Berkeley CS294-262 Guest Lecture (Berkeley, CA): Nov. 2025.
  • Snowflake AI Seminar (Online): Oct. 2025.
"Fair Transaction Processing for Multi-Tenant Databases"
  • Carnegie Mellon University Database Seminar (Online): Oct. 2025.
  • 51st International Conference on Very Large Data Bases (VLDB) '25 (London, UK): Sep. 2025.
  • Databricks Database Reading Group (Online): Jul. 2025.
  • Microsoft Gray Systems Lab (Mountain View, CA): Jan. 2025.
  • Sky Lab Summer Retreat (Santa Cruz, CA): May 2024.
  • Berkeley Database Seminar (Berkeley, CA): Apr. 2024.
"Towards Optimal Transaction Scheduling"
  • TigerBeetle DB Design Seminar (Online): Dec. 2024.
  • HTAP Summit (Palo Alto, CA): Sep. 2024.
  • 50th International Conference on Very Large Data Bases (VLDB) '24 (Guangzhou, China): Aug. 2024.
  • Berkeley NetSys Seminar (Berkeley, CA): Jan. 2024.
  • Berkeley Database Seminar (Berkeley, CA): Apr. 2023.
"Take Out the TraChe: Maximizing (Tra)nsactional Ca(che) Hit Rate"
  • 17th USENIX Symposium on Operating Systems Design and Implementation (OSDI) '23 (Boston, MA): Jul. 2023.
  • Sky Lab Winter 2023 Retreat (Monterey, CA): Jan. 2023.
  • Distributed Systems Meeting (Berkeley, CA): Nov. 2022.
  • Sky Lab Summer 2022 Retreat (Lake Tahoe, CA): Jun. 2022.
"TAOBench: An End-to-End Benchmark for Social Network Workloads"
  • Pinterest Infra Talks (Palo Alto, CA): Dec. 2022.
  • HTAP Summit (Palo Alto, CA): Nov. 2022.
  • PingCAP Meetup (Berkeley, CA and Online): Sep. 2022.
  • Fifteenth TUC Meeting @ SIGMOD 2022 (Online): Jun. 2022.
  • Berkeley Database Seminar (Berkeley, CA): Feb. 2022.
  • Berkeley Progressive Systems Seminar (Online): Dec. 2021.
  • Deep-Dive Talks @ Facebook (Online): Sep. 2021.
"RAMP-TAO: Layering Atomic Transactions on Facebook's Online TAO Data Store"
  • LinkedIn Big Data Platforms (Online): Mar. 2022.
  • Meta Core Data Tech Talks (Online): Feb. 2022.
  • RISELab Winter 2022 Retreat (Online): Jan. 2022.
  • Berkeley Databases Seminar (Online): May 2021.
  • Berkeley Progressive Systems Seminar (Online): Apr. 2021.
"Gryff: Unifying Consensus and Shared Registers"
  • DB Engineering @ Facebook (Online): Aug. 2020.
"Unifying Caching Objectives with Learning Relaxed Belady"
  • Deep-Dive Talks @ Facebook (Online): Aug. 2020.
  • Princeton Senior Thesis Oral Presentation (Online): May 2020.

Fellowships & Awards

  • DRFT paper invited to VLDB Journal on "Best of VLDB" (2025)
  • SkyStore paper invited to VLDB Journal on "Best of VLDB" (2025)
  • EECS Rising Stars (2024)
  • NSF Graduate Research Fellowship (2022)
  • Meta PhD Research Fellowship (2022)
  • VLDB Best Industry Paper Award (2021)
  • Berkeley Chancellor's Fellowship (2020)
  • Berkeley EECS Excellence Award (2020)
  • Princeton Phi Beta Kappa, Sigma Xi, Tau Beta Pi (2019, 2020)