CV

PU JIAO

jiaopujp@gmail.com
Lexington, KY, US

Summary

Ph.D. candidate in Computer Science at the University of Kentucky. Research focuses on high-performance computing, scientific data management and reduction, and deep learning for scientific data compression.

Education

  • Ph.D. in Computer Science
    2026
    University of Kentucky
  • M.S. in Civil Engineering
    2021
    Missouri University of Science and Technology
  • M.Eng. in Structural Engineering
    Institute of Engineering Mechanics, China Earthquake Administration
  • B.Eng. in Civil Engineering
    Xi'an Jiaotong University

Work Experience

  • Research Assistant
    2022-08-01 - 2024-12-01
    University of Kentucky
    Research in HPC and error-controlled lossy compression (QoI preservation, adaptive quantization).
    • Publications at VLDB, IPDPS, and HiPC
    • Collaborated with Argonne National Laboratory
    • Developed QoI-preserving compression frameworks
  • Teaching Assistant
    2025-01-01
    University of Kentucky
    Teaching Assistant for CS216: Intro to Software Engineering Techniques.
    • Led lab sessions and office hours
    • Received "Excellent" TA ratings; student evaluations 4.1–4.4/5
  • Research Assistant, Computer Science Department
    2022-01-01 - 2022-07-31
    Missouri University of Science and Technology
    Developed QoI compression algorithms based on SZ3 and benchmarking tools.
  • Research Assistant, Civil Engineering Department
    2019-09-01 - 2021-12-31
    Missouri University of Science and Technology
    CFD analysis of UAV ceiling effects; bridge inspection and data processing; seismic modeling with OpenSees.

Skills

Programming Languages

  • C++
  • Python
  • JavaScript
  • SQL
  • R
  • MATLAB

High-Performance Computing

  • MPI
  • OpenMP
  • CUDA
  • Parallel algorithms
  • Scientific computing

Build Systems & Tools

  • CMake
  • Spack
  • Git
  • Linux/Unix

Data Science & Analysis

  • NumPy
  • Pandas
  • SciPy
  • Matplotlib
  • scikit-learn

Databases

  • MongoDB
  • MySQL
  • SQLite

Compression Technologies

  • SZ2.1
  • SZ3
  • SZx
  • FPZIP
  • ZFP
  • Lossy compression algorithms

Simulation Software

  • OpenSees
  • CFD
  • ANSYS
  • Structural analysis tools

Research Methodologies

  • Algorithm design
  • Performance optimization
  • Artifact detection
  • Experimental validation

Publications

  • QPET: A Versatile and Portable Quantity-of-Interest-Preservation Framework for Error-Bounded Lossy Compression
    2025
    Proceedings of the VLDB Endowment
    To appear.
  • Improving the Efficiency of Interpolation-Based Scientific Data Compressors with Adaptive Quantization Index Prediction
    2025
    2025 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
    To appear.
  • Characterization and Detection of Artifacts for Error-Controlled Lossy Compressors
    2023
    HiPC 2023
    Detecting and characterizing artifacts introduced by error-controlled lossy compressors.
  • Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data
    2022
    Proceedings of the VLDB Endowment
    QoI-preserving lossy compression for scientific data.
  • Enabling Efficient Error-controlled Lossy Compression for Unstructured Scientific Data
    2025
    2025 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • TspSZ: An Efficient Parallel Error-Bounded Lossy Compressor for Topological Skeleton Preservation
    2025
    2025 IEEE 41st International Conference on Data Engineering (ICDE)
  • Preserving Topological Feature with Sign-of-Determinant Predicates in Lossy Compression: A Case Study of Vector Field Critical Points
    2024
    2024 IEEE 40th International Conference on Data Engineering (ICDE)
  • Coating Condition Detection and Assessment on the Steel Girder of a Bridge through Hyperspectral Imaging
    2023
  • A neural network-based multivariate seismic classifier for simultaneous post-earthquake fragility estimation and damage classification
    2022
    Engineering Structures
  • Encoding time-series ground motions as images for convolutional neural networks-based seismic damage evaluation
    2021
    Frontiers in Built Environment

Teaching

  • CS216: Intro to Software Engineering Techniques
    2025
    University of Kentucky
    Role: Teaching Assistant
    Led lab sessions; office hours; highly rated TA.

Languages

  • English
    Fluent
  • Chinese
    Native

Interests

  • High-performance computing
  • Scientific data compression
  • UAV technology
  • Structural engineering