Kezhi Lu

Kezhi Lu

PhD Candidate in Computer Science

University of Technology Sydney (UTS)
Australian Artificial Intelligence Institute (AAII)
Decision Systems & e-Service Intelligence Lab

About Me

I am a PhD candidate at the Faculty of Engineering and Information Technology, University of Technology Sydney, working under the supervision of Distinguished Professor Jie Lu and Professor Guangquan Zhang. I received my M.S. degree in Computer Technology from Beijing Jiaotong University in 2020.

My research focuses on the intersection of artificial intelligence and recommender systems, with particular emphasis on developing interpretable and trustworthy cross-domain recommendation algorithms. I am passionate about bridging the gap between complex machine learning models and human-understandable explanations.

Research Interests

Cross-Domain Recommendations

Developing algorithms that transfer knowledge across different domains to address data sparsity and cold-start problems.

Large Language Models

Exploring LLMs for enhanced recommendation systems and natural language understanding in user preferences.

Machine Learning

Advancing deep learning techniques for personalized and interpretable recommendation systems.

Natural Language Processing

Integrating NLP techniques to understand user feedback and generate human-readable explanations.

Selected Publications

Genomics-Enhanced Cancer Risk Prediction for Personalized LLMs-Driven Healthcare Recommender Systems

Kezhi Lu, Jie Lu, Guangquan Zhang, et al.

ACM Transactions on Information Systems (TOIS) 2025

AMT-CDR: A Deep Adversarial Multi-Channel Transfer Network for Cross-Domain Recommendation

Kezhi Lu, Qian Zhang, Guangquan Zhang, Jie Lu

ACM Transactions on Intelligent Systems and Technology (TIST) 2024

BERT-RS: A Neural Personalized Recommender System with BERT

Kezhi Lu, Qian Zhang, Guangquan Zhang, Jie Lu

FLINS 2022 - 15th International Conference - Best Student Paper 2023

SympGAN: a systematic knowledge integration system for symptom–gene associations network

Kezhi Lu, Kuo Yang, Xuezhong Zhou, et al.

Knowledge-Based Systems 2023

Integrated network analysis of symptom clusters across disease conditions

Kezhi Lu, Kuo Yang, Xuezhong Zhou, et al.

Journal of Biomedical Informatics 2020

AI for Women's Health: Framework and Focus Areas

Jie Lu, Angela Dawson, Kairui Guo, Deborah Fox, Fahimeh Ramezani, Susan Morton, Kathleen Baird, Zelia Soo, Kezhi Lu, Guodong Long, Debra Anderson

The ACM Web Conference 2025

Get In Touch

I'm always interested in collaborations and discussions about research opportunities.