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My research develops systems and algorithms to address data management challenges throughout the data analytics lifecycle. Focus areas include: (1) data analytics over dirty, unstructured data; and (2) data infrastructure and system support for GenAI-powered analytics. My work bridges data management systems, artificial intelligence, and human-computer interaction, with the goal of helping users extract meaningful insights from data more effectively.
My teaching focuses on bridging foundational database principles with emerging technologies that are reshaping the field. In CS 6400 (Database Systems Concepts and Design), I provide an advanced introduction to relational databases, covering data models, schema design, query processing and optimization, concurrency control, transactions, and failure recovery. CS 4440 (Emerging Database Technologies) enables students to assess the current database landscape by examining how foundational concepts are being reworked in light of new technologies and applications. Across both courses, I emphasize critical thinking about how core principles adapt to evolving technological demands and real-world challenges.
- Zhong, H., Lentz, M., Narodytska, N., Szekeres, A., & Rong, K. (2025). HoneyBee: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning. arXiv preprint arXiv:2505.01538.
- Wu, R., Chunduri, P., Payani, A., Chu, X., Arulraj, J., & Rong, K. (2024). SketchQL: Video Moment Querying with a Visual Query Interface. Proceedings of the ACM on Management of Data, 2(4), 1-27.
- Bachkaniwala, R., Lanka, H., Rong, K., & Gavrilovska, A. (2024, September). Lotus: Characterization of Machine Learning Preprocessing Pipelines via Framework and Hardware Profiling. In 2024 IEEE International Symposium on Workload Characterization (IISWC) (pp. 30-43). IEEE.
- Agrawal, A., Reddy, S., Bhattamishra, S., Nookala, V. P. S., Vashishth, V., Rong, K., & Tumanov, A. (2024, November). Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization. In Proceedings of the 2024 ACM Symposium on Cloud Computing (pp. 1012-1031).
- Rong, K., Liu, P., Sonje, S. A., & Charikar, M. (2024, May). Dynamic Data Layout Optimization with Worst-case Guarantees. In 2024 IEEE 40th International Conference on Data Engineering (ICDE) (pp. 4288-4301). IEEE.
- Li, P., Chen, Z., Chu, X., & Rong, K. (2023). Diffprep: Differentiable data preprocessing pipeline search for learning over tabular data. Proceedings of the ACM on Management of Data, 1(2), 1-26.
- Rong, K., Budiu, M., Skiadopoulos, A., Suresh, L., & Tai, A. (2023). Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques. Proceedings of the VLDB Endowment, 16(10), 2618-2631.