During my undergraduate studies, I have worked at System Research Group of Microsoft Research Asia (MSRA), RISE Lab at UC Berkeley, Shanghai Qi Zhi Institute, and Nanyang Technological University. I had industry internships at Moonshot AI and Wish.
My research interests lie in the intersection of machine learning and data-intensive systems.
- [SIGMOD 2024] Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads. Dingheng Mo, Fanchao Chen, Siqiang Luo, Caihua Shan.
- [ICDE 2023] Eﬃcient and Compact Spreadsheet Formula Graphs. Dixin Tang, Fanchao Chen, Christopher De Leon, Tana Wattanawaroon, Jeaseok Yun, Srinivasan Seshadri, Aditya G Parameswaran.
- [VLDB Demo 2023] Visualizing Spreadsheet Formula Graphs Compactly. Fanchao Chen, Dixin Tang, Haotian Li, Aditya G Parameswaran.
- Rethinking the Development of Large Language Models from the Causal Perspective: A Legal Text Prediction Case Study.
- Robust and Eﬃcient Learning-based Virtual NUMA Placement for Large-Scale Production Clusters.