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Vincent Liu 
News
[Nov 2025]
Happy to welcome Daphne Liu (class of 2044) to the group!
[Sep 2025]
Position paper on network-attached AI Accelerator disaggregation accepted to HotNets 2025.
[Sep 2025]
ParaFlex paper on multiplexed pipeline parallel LLMs accepted to SoCC 2025.
[Aug 2025]
CCEval was accepted into NSDI 2026.
[May 2025]
Congrats to Dr. Xinyi Chen and Dr. Kelvin Ng for completing their PhDs! They will be joining Meta and AWS, respectively, where they will both be working on software-hardware co-design for AI accelerators.
[Dec 2024]
Invisiflow and Multiverse LLM training simulation papers were accepted into NSDI 2025.
[Dec 2024]
CausalMesh was selected for the SIGMOD Research Highlight Award!
About Me
I am an associate professor in the Department of Computer and Information Science at the University of Pennsylvania, where I am the director of the Distributed Systems Lab (DSL) and also lead the PennNetworks group. My work has been recognized by an NSF CAREER Award, a VMWare Early Career Faculty Award, a Facebook Faculty Research Award, a Google Research Award, a SIGMOD Research Highlights Award, and several best paper awards at SIGCOMM and NSDI. Prior to Penn, I received my Ph.D. from the University of Washington working (primarily) with Tom Anderson and Arvind Krishnamurthy. Prior to that, my undergraduate research at the University of Texas at Austin was in the area of compilers and parallel systems.
My research interests are in the broad areas of distributed systems and networking, and my projects have touched on nearly every aspect of systems and networks. In each, my focus is on solving important, long-standing problems by introducing creative new approaches and bridging disciplines. Recent projects include, but are not limited to:
All of this research is made possible by my fantastic students:
My research interests are in the broad areas of distributed systems and networking, and my projects have touched on nearly every aspect of systems and networks. In each, my focus is on solving important, long-standing problems by introducing creative new approaches and bridging disciplines. Recent projects include, but are not limited to:
The exponential growth of large-scale ML models has created a fundamental mismatch between the granularity of hardware allocation and the increasingly dynamic requirements of inference and training workloads. Our work has made progress in improving the orchestration of resource provisioning (AlpaServe, OSDI '23; ParaFlex, SoCC '25), kernel dispatch (Paella, SOSP '23; Genie, HotNets '25), and collective communication (TE-CCL, SIGCOMM '24).
In principle, serverless computing offers the promise of infinite scalability and pay-per-use billing, all behind a simpler interface for users. In practice, however, modern serverless offerings can introduce subtle issues with correctness (c.f., Beldi, OSDI '20; μ2sls, POPL '23), performance (Mucache, NSDI '24), and pricing (λ-trim, ASPLOS '25).
As datacenter networks grow in complexity and AI training clusters reach scales of tens or hundreds of thousands of GPUs, the tools used to design and evaluate these networks have become a bottleneck. Our research explores techniques to increase the tractability of large cluster performance estimation by multiple orders of magnitude, using ML (MimicNet, SIGCOMM '21), Data-Oriented Design principles (DONS, SIGCOMM '23), GPU acceleration (Multiverse, NSDI '25), and statistical techniques (CCEval, NSDI '26).
While most modern applications can saturate increasingly high bandwidth links during peak periods (e.g., an AllReduce operation), the vast majority of network capacity remains underutilized during normal operation. Our work has explored creative ways to leverage programmable network hardware to reclaim this "wasted" capacity for the benefit of applications and network operators. Efforts in this space include Mantis (SIGCOMM '20), OrbWeaver (NSDI '22), PrintQueue (SIGCOMM '22), Cebinae (SIGCOMM '22), Cowbird (SIGCOMM '23), Beaver (OSDI '24), and InvisiFlow (NSDI '25).
Students
- Tao Luo (with Boon Thau Loo)
- Yinda Zhang
- Spyros Pavlatos
- Xuting Liu
- Jiaheng Lu
Graduated Students
- Xinyi Chen
- Research Scientist at Meta (2025).
- Kelvin K.W. Ng
- Applied Scientist at AWS (2025).
- Liangcheng Yu
- Senior Researcher at Microsoft Research Redmond and the Office of the CTO, Azure for Operators (2024).
- Winner of the 2024 Rubinoff award for best Computer Science thesis at the University of Pennsylvania.
- Winner of the 2021 Penn Presidential Ph.D. Fellowship.
- Haoran Zhang (with Sebastian Angel)
- Research Scientist at Meta (2024).
- Nominated for VLDB 2025 Best Paper Award.
- Qizhen Zhang (with Boon Thau Loo)
- Assistant Professor at University of Toronto (2023).
- Gap-year Postdoc at Microsoft Research (2022).
- Winner of the 2022 Rubinoff award for best Computer Science thesis at the University of Pennsylvania.
- Winner of the 2019 Jonathan M. Smith Fellowship.
- Nofel Yaseen
- Research Scientist at Meta (2022).
- Winner of the 2020 Facebook Fellowship in Networking and Connectivity.