The Team

Current Students/Researchers

• Zihang Luo (Supervision; PhD from SUTD, 09/2025-Present) Enhancing Generative Recommendation via Long-Term Value Alignment

• Lee Yueh Ern Shannon (Supervision; PhD from SUTD, 01/2025-Present) Trustworthy LLMs for Recommendation in Law

• Lingfeng Huang (RA; 08/2025-Present) Multi-agent LLMs for User Behavior Simulation in Recommendation

• Zhuoxuan Huang (Visiting Ph.D. from Central South Univ. 09/2025-Present) LLMs for Next-Point-of-Interest Recommendation

• Zongqiang Wu (Visiting Ph.D. from University of Electronic Science and Technology of China, 07/2025-Present) Improving LLMs through Test Time Scaling 

• Kaidong Feng (Visiting Ph.D. from Yanshan Univ., 11/2024-Present) Personalized Bundle Recommendation

• Max Xiao (Co-Supervision; Master from MQ, 01/2025-Present) Prompting LLMs to Effectively Incorporate User-Item Interactions in Recommender Systems

• Samal Mukhtar (Co-Supervision; Ph.D. from Univ. of Manchester, 10/2024 - Present) Exploiting LLMs for Recommendation for Software Development

• Hongyang Liu (Co-Supervision; Ph.D. from MQ, 12/2023 - Present) Recommender System Environment Simulation for Effective Evaluation

Former Students/Researchers

• Jiajie Zhu (Co-Supervision; Ph.D. from MQ, 2021 - 2025) Cross Domain Recommender Systems [Now Research Fellow at Macquarie University]

• Youchen Sun (Co-Supervision; Ph.D. from NTU, 2022 - 2025) Leveraging Social Networks for Robust Recommendation [Now Research Scientist at TikTok]

• Yatong Sun (Supervision; Ph.D. from MQ, 2020 - 2024) Eliminating Unreliable Data for More Robust Sequential Recommendation [Now Distinguished Associate Research Fellow at Northeastern University, China]

• Syed M Zaheen (Intern from NTU Singapore, 06/2023-08/2023) DaisyRec: Towards Reliable Recommender Systems

• Zhang Jixiao (Intern from SUSTech China, 03/2023-08/2023) Explainable Next Point-of-Interest Recommendation with Neural-Symbolic Reasoning

• Jinze Wang (Master from MQ, 2020-2021) Meta-learning Enhanced Next POI Recommendation by Leveraging Check-ins from Auxiliary Cities [Now PhD Candidate at Swinburne University of Technology]

• Meshari Algethami (Undergraduate from MQ, 2021) User Co-consumption Behavior Mining for Explainable Bundle Recommender Systems

• Joshua Dodanduwa (Undergraduate from MQ, 2021) Incorporating Music Theory in Music Playlist Generation

• Yefan Li (Undergraduate from MQ, 2021) Personalized Bundle Recommendation Systems