Curriculum Vitae

Education

• Ph.D. in Computer Science, University of Minnesota-Twin Cities, 2025 - Present
• M.S. in Computer Science, Nankai University, Tianjin, 2022 - 2025
• B.S. in Computer Science, Nankai University, Tianjin, 2018 - 2022

Research Interests

• GPU programming and memory management
• High-efficiency CUDA kernel design
• CPU-GPU heterogeneous computing
• LLM training/inference optimization
• Agentic MLSys and agentic EDA frameworks

Publications

1. PagePilot: Synergizing Heterogeneous Backend Devices with Reusability-Aware Page Offloading X. Liu, J. Dong, X. Liu, L. Wang, S. Li, H. Li, X. Gong, J. Zhang, P.-C. Yew. ACM Transactions on Architecture and Code Optimization (TACO), 2026.

2. SparseDitto: An Agentic Sparse Compilation Framework through Architecture-Aware Synthesis on GPUs S. Li, G. Sun, J. Tang, Y. Wang, M. Hong, C. Ding. arXiv:2608.05033, 2026.

3. GSR-GNN: Training Acceleration and Memory-Saving Framework of Deep GNNs on Circuit Graph Y. Luo, S. Li, Y. Feng, V. Kancharla, S. Huang, C. Ding. DAC ‘26, 2026.

4. StitchCUDA: An Automated Multi-Agents End-to-End GPU Programming Framework with Rubric-based Agentic Reinforcement Learning S. Li, Z. Zhang, W. Chen, Y. Luo, M. Hong, C. Ding. International Conference on Machine Learning (ICML 2026), accepted.

5. CUDABeaver: Benchmarking LLM-Based Automated CUDA Debugging S. Li*, H. Chen*, M. Fazzini, C. Ding. arXiv:2605.08455, 2026.

6. CUDAHercules: Benchmarking Hardware-Aware Expert-level CUDA Optimization for LLMs S. Li, Z. Zhang, G. Sun, Y. Luo, W. Chen, Y. Wang, M. Hong, C. Ding. arXiv:2605.08467, 2026.

7. FPTC: A Fast Parallel Transform-based Codec for Efficient Asymmetric Signal Compression B. Mechels, R. Billmeyer, A. Chen, S. Li, C. Ding. arXiv:2605.01086, 2026.

8. XuanJia: A Comprehensive Virtualization-Based Code Obfuscator for Binary Protection X. Zou, X. Gong, J. Zhang, S. Li, P.-C. Yew. arXiv:2601.10261, 2026.

9. CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization Z. Zhang, R. Wang, S. Li, Y. Luo, M. Hong, C. Ding. arXiv:2511.01884, 2025.

10. DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs Y. Luo, S. Li, J. Tao, K. G. Thorat, X. Xie, H. Peng, N. Xu, C. Ding, S. Huang. ICS ‘25, 2025.

11. Liberator: A Data Reuse Framework for Out-of-Memory Graph Computing on GPUs S. Li, R. Tang, J. Zhu, Z. Zhao, X. Gong, W. Wang, J. Zhang, P.-C. Yew. IEEE TPDS 34.6 (2023): 1954-1967.

12. OneGraph: A Cross-Architecture Framework for Large-Scale Graph Computing on GPUs Based on oneAPI S. Li, J. Zhu, J. Han, Y. Peng, Z. Wang, X. Gong, G. Wang, J. Zhang, X. Wang. CCF-THPC 6.2 (2024): 179-191.

Work Experience

• Jul. 2021 - Sept. 2021: System Engineer Intern
  • Alibaba Cloud, Shanghai
  • Developed Linux kernel modules with Rust for security containers
  • Rewrote the PCIe device registry process in Hypervisor
  • Implemented PCIe device passthrough and hot-plug support for NVIDIA GPUs in security containers

Teaching

• Computer Architecture (CSCI 4203), Fall 2025, University of Minnesota-Twin Cities
• Introduction to Parallel Programming, Spring 2022, Nankai University
• Principles of Computer Organization, Spring 2023, Nankai University
• Operating System, Fall 2020, 2021 & 2022, Nankai University

Skills

• Programming Languages: C/C++, CUDA, Python, Rust
• Systems: Linux kernel development, GPU programming, embedded systems
• Tools: Git, LaTeX, Docker