Feng Luo

Feng Luo

Ph.D. Candidate ยท RMIT University

Visiting Researcher ยท The University of Queensland

About Me

I am a Ph.D. candidate in Computer Science at RMIT University, advised by Prof. Zhifeng Bao, Prof. J. Shane Culpepper, and Dr. Hui Luo. I am also a Visiting Researcher at The University of Queensland.

My research focuses on tabular data intelligence โ€” building LLM-powered systems that can effectively discover, complete, and query complex tabular data at scale. I am particularly interested in the real-world challenges this entails: retrieving relevant tables from large-scale data lakes, recovering missing values from incomplete datasets, and answering complex numerical questions over semi-structured tables โ€” all under practical cost and efficiency constraints.

I also have prior experience in AI for healthcare, developing deep learning systems for medical question answering, patient similarity search, and clinical representation learning from electronic health records.

Research Interests
Tabular Data Discovery Numerical Question Answering Missing Value Imputation LLM-based Reasoning AI for Healthcare

News

Jun 2026
๐Ÿ†
Award Received the People's Choice Award at the 2026 UQ AI HDR Showcase (UQ AI Research Network) for the presentation "Data discovery for reliable AI over complex tabular data".

Selected Publications

ICDE 2026
Decomposition-Driven Multi-Table Retrieval and Reasoning for Numerical Question Answering
Feng Luo, Hai Lan, Hui Luo, Zhifeng Bao, Xiaoli Wang, J. Shane Culpepper, Shazia Sadiq
IEEE International Conference on Data Engineering (ICDE), 2026
VLDB J. 2026
Missing Value Imputation in Tabular Data Lakes Unleashed: A Hybrid Approach
Feng Luo, Hai Lan, Hui Luo, Zhifeng Bao, J. Shane Culpepper, Shazia Sadiq, Xiaoli Wang
The VLDB Journal, 2026

โ†’ View full publication list