I joined the department of Computer Science of the University of Houston as a tenure-track assistant professor in Fall 2024, and am seeking for PhD students that start their study from Spring 2026 or later. My research fields include scientific computing, data compression, and AI for science. I have solid connections with national labs such as Argonne National Lab, and students have a good chance to collaborate with scientists in the national labs in their research and do internships in the national labs during their PhD studies.

About UH (University of Houston): UH is a Carnegie R1 (highest research activity) institution and among the top doctoral research universities in the US, and has a strong department of Computer Science. According to CSRankings, in 2024 UH is ranked at top 100 in Computer Science and ranked 23 in High-performance Computing (my field). According to Shanghai Ranking, in 2023 UH CS is ranked at top 70 in US. Located at The downtown Houston, the 4-th largest city in the US, students in UH can also live a convenient and enjoyable life.

About me: Jinyang Liu (full CV) acquired his Ph. D. degree in Computer Science from University of California, Riverside in the summer of 2024. Prior to that, he has got the Master's degree the Bachelor's degree from Peking University. Jinyang has been working on the topics of scientific data lossy compression and several other High-performance Computing and Scientific Computing topics. He has presented publications in various highly prestigious conferences and journals such as ACM SIGMOD, VLDB, IEEE/ACM SC, IEEE ICDE, ACM ICS, ACM HPDC, IEEE IPDPS, IEEE Cluster, IEEE TPDS, etc. He has received the Dissertation Year Fellowship (DYP) award from UCR and Best Paper Nominations from ICS 23 and HPDC 25. He has also developed several different scientific data error-bounded lossy compressors, such as SZ3, QoZ, and cuSZ.

About the prospective students: Several opening positions are availble in my labs for Ph. D. students starting from spring 2026 or later. The research topics includes but are not limited to:

• Scientific data compression.
• High-performance scientific data computing and management systems.
• Deep-Learning-based data compression techniques.
• AI for Science.

Basic requirements for the prospective students would be:

• Interests and visions in Computer Science research.
• Academic experiences in important Mathematics topics (e.g. Probability and Statistics, Linear Algebra) and Computer Science topics (e.g. C/C++ programming, Computer Architecture).

I am also looking forward to some of your additional abilities, examples are:

• Knowledge in scientific computing or numerical analysis.
• Knowledge about parallel programming on CPU or GPU platforms (e.g. OPENMP, MPI, CUDA).
• Knowledge about Deep Learning and its coding frameworks (e.g. PyTorch, Tensorflow, JAX).

For students interested in this position, please send your brief self introduction, CV and transcripts to jliu217@central.uh.edu.