Rocky Chen

Dr Chen's research impact has received extensive recognitions, including:

• 2025: Brisbane Lord Mayor’s Convention Trailblazer Award (6 awardees per annum).
• 2025: Outstanding Program Committee Member, KDD’25 (CORE A* data mining conference).
• 2025: Excellent Program Committee Member, SIGIR’25 (CORE A* information retrieval conference).
• 2024: Best Student Paper Award, CIKM’24 (1/347, CORE A data science conference, principal supervisor of first author).
• 2024: World’s Top 2% Scientist in 2024, Stanford University.
• 2024: UQ Faculty of EAIT Early Career Research Leadership Award.
• 2022: ARC Discovery Early Career Researcher Award (2023).
• 2022: UQ EAIT Faculty Early Career Researcher Award.
• 2020: Best Student Paper Award, DASFAA’20 (1/162, top database conference, lead author).
• 2018: Best Paper Award Nomination, ICDM’18 (CORE A* data mining conference, first author).
• 2018: Best Paper Award as the first author in PAKDD’18 (CORE A conference) Workshop on Social Computing.
• 2017: Best Paper Award in ACM WWW’17 (CORE A* conference) Companion on Social Computing.

He has been continuously contributing to the following research areas:

• Recommender Systems and Personalisation. Dr Chen has been continuously publishing in the field of personalisation algorithms and recommender systems [SIGIR’20-25, WWW’23-25, CIKM’23-24, ICDE’19-20]. His work also features pioneering research utilizing (large) language models to build interactive, conversational systems for recommendation, retrieval, and decision support [SIGIR’25, KDD’24, TIST’23, WWW’22, SIGIR’21, TOIS’20].
• Fairness-aware and Trustworthy Machine Learning. Dr Chen leads the area of fairness-aware algorithms, represented by his work on social media analytics [ICDM’25, MM’25, WWW’25, KDD’24]. Besides, his research highlights trustworthiness, where research outcomes span areas like explainable recommendation [ICDE’23, SIGIR’21], knowledge graph reasoning [ICDE’25, TIST’24], anomaly prediction [ICDE’24, WWWJ’23], robust spatial-temporal prediction [ECML’25, CIKM’24, ICDE’24, TKDE’21], and causal inference and machine unlearning [ICML’25, KDD’25, TKDE’24, ICDM’23, ACL’23], which reflect the societal value of his research.
• Combating the Digital Divide across Individuals. The era of personalised computing calls for solutions to the unbalanced computing capacity among individuals. Dr Chen leads the area of on-device personalised recommender systems [KDD’21, WWW’21, VLDB’21, CIKM’21, WWW’20]. Supported by his DRCRA, his recent research focuses on scaling up personalised computing techniques to achieve digitalisation equity [WWW’25, SIGIR’24, WSDM’24, TKDE’24, ICDM’23, SIGIR’23, TOIS’22] and privacy [TOIS’25, CIKM’25, KDD’24, WWW’24] across individuals.