Tingfeng Lan
Computer Science Research Lover at DS2 Lab, University of Virginia.
I am a PhD student in computer science at \(Ds^2 Lab\) of the University of Virginia under Prof. Yue Cheng.
Generally, I aim to develop high-performance, scalable systems for emerging ML applications. Currently I am working on building better (computing and storage) systems for (distributed) ML applications. For example, rethinking the potential of multi-tier parallel processing within heterogeneous computing environments like CPU-GPU collaborative computing.
Before joining UVA, I earned my bachelor’s degree from Sichuan University, where I had the privilege of being guided by Prof. Mingjie Tang and Prof. Hui Lu from UTA, focusing on optimizing large-scale recommendation model training systems. I was also fortunate to be advised by Prof. Jianguo Wang from Purdue University, with a focus on utilizing machine learning techniques to optimize graph algorithms’ performance.
I am open to other opportunities and new research, so please feel free to reach me at my email erc8gx _AT_ virginia.edu
news
| Jan 27, 2026 | 🎉🎉 Our work “MorphServe” and “λScale” are accepted by MLSys’26! |
|---|---|
| Dec 09, 2025 | 💡💡 Honored to serve on the Artifact Evaluation Program Committee for NSDI’26! |
| Sep 30, 2025 | 💡💡 Honored to serve on the Shadow Program Committee for EuroSys’26! |
| Sep 18, 2025 | 💡💡 Thrilled to receive a grant from Modal for Academics — big thanks to Modal! |
| Sep 02, 2025 | 💡💡 Honored to serve on the Artifact Evaluation Program Committee for EuroSys’26! |
selected publications
- preprintZenFlow: Enabling Stall-Free Offloading Training via Asynchronous Updates2025
- NSDI’26ZipLLM: Efficient LLM Storage via Model-Aware Synergistic Data Deduplication and Compression2025
- VLDB’25mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs2024
- VLDB’24DLRover-RM: Resource Optimization for Deep Recommendation Models Training in the CloudProceedings of the VLDB Endowment, 2024