Haolai Che
Haolai Che
I am a Ph.D. candidate in Computer Science at Case Western Reserve University, advised by Prof. Yinghui Wu.
My research lies in Data Provenance, Graph Learning, Explainable AI (XAI), and Agentic Workflow.
Before joining CWRU, I received my B.S. in Electrical Engineering from China Agricultural University, where I also worked on computer vision for agriculture and intelligent autonomous systems.
Outside of research, I enjoy playing in a rock & roll band (vocals and guitar), drawing, and bodybuilding.
News
News
I'm happy to share that our Paper Training-free Counterfactual Explanation for Temporal Graph Model Inference. has been accepted to ICLR 2026.
I'm happy to share that our Paper Interpreting Graph Inference with Skyline Explanations. has been accepted to ICDE 2026.
I'm delighted to announce that I have accepted an internship offer from Ant Group! Next summer, I'll be joining the Ant 🐜 Group Research Institute as a Research Scientist Intern, where I'll be working with the OceanBase team.
Publications
Publications
Mingjian Lu, Haolai Che, Yangxin Fan, Qu Liu, Fei Shao, Tingjian Ge, Xusheng Xiao, Yinghui Wu. Training-free Counterfactual Explanation for Temporal Graph Model Inference [ICLR 2026]
2.Dazhuo Qiu♪, Haolai Che♪, Arijit Khan, Yinghui Wu. Interpreting Graph Inference with Skyline Explanations. [ICDE 2026]
3. Yangxin Fan♪, Haolai Che♪, Yinghui Wu. Inference-friendly Graph Compression for Graph Neural Networks, International Conference on Very Large Data Bases(VLDB), 2025
♪ Equal contribution
4. Yangxin Fan♪, Haolai Che♪, Mingjian Lu♪, Yinghui Wu. Graph Compression for Interpretable Graph Neural Network Inference
at Scale. International Conference on Very Large Data Bases(VLDB)(Demo Track), 2025
5. M. Wang, H. Ma, S. Guan, Y. Bian, Haolai Che, A. Daundkar, A. Sehirlioglu, Yinghui Wu. ModsNet: Performance-Aware Top-k
Model Search Using Exemplar Datasets. International Conference on Very Large Data Bases(VLDB)(Demo Track), 2024
6. M. Wang, S. Guan, H. Ma, Y. Bian, Haolai Che, A. Daundkar, A. Sehirlioglu, Yinghui Wu. Selecting Top-k Data Science Models by
Example Dataset. The 32nd ACM International Conference on Information and Knowledge Management(CIKM), 2023
In Submission
In Submission
1. Training-free Counterfactual Explanation for Temporal Graph Model Inference [Submitted to ICLR 2026]
2. Scaling Graph Inference by Serving Models as Views [Submitted to SIGMOD 2026]
3. Grounding Provenance for Graph Inference with Data Constraints [Submitted to VLDB 2026]
Teaching
Teaching
I serve as a TEACHING ASSISTANT from Fall 2022 to Fall 2024(5 semesters) at Case Western Reserve University:
• I assisted in the High Performance Data and Computing (CSDS438), Database Systems (CSDS433), Structured and Unstructured Data(CSDS 234), and Introduction to Data Science Systems(CSDS 312) courses.
• I provided valuable academic support to students with diverse backgrounds, offering office hours, developing assignments, and grading their work.
Projects
Projects
CRUXpider Open-source Academic paper analysis Platform.
Web Server / Web Client/ Packet Trace [implemented in C]
Licenses
Licenses
NVIDIA [Issued Nov 2024]
FUNDAMENTALS OF ACCELERATED COMPUTING WITH CUDA C/C++
• Credential ID: 8cmkGpoPT-iWhf2hH4QRnA
Skillsets
Skillsets
Programming Languages: Python, C/C++, Java, SQL, JavaScript, HTML, Prompt Engineering
Frameworks & Tools: PyTorch, PyG, DGL, Scikit-Learn, NetworkX, Git, HPC, Linux, LLM
Languages Chinese: (Native), English (Proficient; IELTS 7.5)
miscellaneous
miscellaneous
My Erdős Number is 5.
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