Jie Li

Research Assistant Professor · HPC · AI Infrastructure · AI Agents for HPC

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I am a Research Assistant Professor in the Department of Computer Science at Texas Tech University and the Assistant Director of the Texas Tech site of the NSF Cloud and Autonomic Computing Center (CAC IUCRC). I earned my Ph.D. in Computer Science from Texas Tech University in May 2024, advised by Dr. Yong Chen, and then served as a postdoctoral researcher and technical lead of the Data-Intensive Scalable Computing Laboratory (DISCL).

My research focuses on High-Performance Computing (HPC) and AI Infrastructure, with an emphasis on observability, resource management, and energy efficiency. Building on this systems foundation, my research agenda extends to AI agents for HPC operations, the security of agents acting within HPC environments, and the integration of HPC with quantum computing.

I co-designed and built the NSF REPACSS cluster (a $12.25M award project), which now serves as a production testbed for my work on AI agents that operate and manage HPC systems. I also developed the MonSTer HPC monitoring framework, which has been adopted by Dell’s Omnia project. Previously, I spent three summers (2021–2023) as a Graduate Student Intern at Lawrence Berkeley National Laboratory (LBNL), where I built telemetry pipelines for NERSC’s Cori and Perlmutter supercomputers and led development of the Disaggregation-Aware Scheduler for memory-disaggregated systems.

I am on the 2026–27 academic job market, seeking tenure-track Assistant Professor positions in Computer Science. Feel free to reach out.

News

Sep 25, 2026 Our paper OCEAN: Open-Source CXL Emulation for Hyperscale Architecture and Networking has been accepted to SC’26.
Jul 01, 2026 I started as a Research Assistant Professor in the Department of Computer Science at Texas Tech University.
Jan 01, 2026 I became the Assistant Director of the Texas Tech site of the NSF Cloud and Autonomic Computing Center (CAC IUCRC).

Selected publications

  1. AAAI’26
    TokenPowerBench: Benchmarking the Power Consumption of LLM Inference
    Chenxu Niu, Wei Zhang, Jie Li, Yongjian Zhao, Tongyang Wang, Xi Wang, and Yong Chen
    In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI’26), 2026
    (Acceptance Rate: 4,167/23,680=17.6%)
    DOI arXiv
    44 Google Scholar citations
  2. CLUSTER’24
    Job Scheduling in High Performance Computing Systems with Disaggregated Memory Resources
    Jie Li, George Michelogiannakis, Samuel Maloney, Brandon Cook, Estela Suarez, John Shalf, and Yong Chen
    In 2024 IEEE International Conference on Cluster Computing (CLUSTER’24), 2024
    DOI
    8 Google Scholar citations
  3. ISC’23
    Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter
    Jie Li, George Michelogiannakis, Brandon Cook, Dulanya Cooray, and Yong Chen
    In International Conference on High Performance Computing (ISC’23), 2023
    (Acceptance Rate: 21/78=26.9%)
    DOI
    72 Google Scholar citations
  4. CLUSTER’20
    MonSTer: An Out-of-the-Box Monitoring Tool for High Performance Computing Systems
    Jie Li, Ghazanfar Ali, Ngan Nguyen, Jon Hass, Alan Sill, Tommy Dang, and Yong Chen
    In 2020 IEEE International Conference on Cluster Computing (CLUSTER’20), 2020
    (Acceptance Rate: 27/132=20.5%)
    DOI
    37 Google Scholar citations