The UTNS research group at the University of Texas at Austin works on foundational systems and networking problems that arise in supporting big data analytics, distributed machine learning, and large-scale distributed applications. Our work explores both theoretical underpinnings and system design/implementation, and builds on ideas from adjacent areas such as game theory, optimization, and formal methods.
News
Copper Wire got accepted at ASPLOS 2025!
Read-ME got accepted at NeurIPS 2024!
MOSEL and FFN-SKipLLM got accepted at EMNLP 2024!
The Transcraft project, which focuses on developing an end-to-end framework for the design and implementation of network transport stacks, has won an NSF Award!
The Learning Directed Operating System (LDOS) team has been awarded an NSF Expeditions Award!
Jiaxin Lin won 2023 Google PhD Fellowship!
Darwin and Slingshot got accepted at SIGCOMM 2023!
Network Traffic Characteristics of Data Centers in the Wild (IMC, 2010) received SIGCOMM Test-of-Time Award!
Read-ME got accepted at NeurIPS 2024!
MOSEL and FFN-SKipLLM got accepted at EMNLP 2024!
The Transcraft project, which focuses on developing an end-to-end framework for the design and implementation of network transport stacks, has won an NSF Award!
The Learning Directed Operating System (LDOS) team has been awarded an NSF Expeditions Award!
Jiaxin Lin won 2023 Google PhD Fellowship!
Darwin and Slingshot got accepted at SIGCOMM 2023!
Network Traffic Characteristics of Data Centers in the Wild (IMC, 2010) received SIGCOMM Test-of-Time Award!
Featured projects
Featured publications
MTP: Transport for In-Network Computing
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NSDI, 2025.
Expressive and Efficient Service Mesh Policies
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ASPLOS, 2025.
Resilient Baseband Processing in Virtualized RANs with Slingshot
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SIGCOMM, 2023.
Darwin: Flexible Learning-based CDN Caching
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SIGCOMM, 2023.
Lowering the Pre-training Tax for Gradient-based Subset Training: A Lightweight Distributed Pre-Training Toolkit
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ICML, 2023.