Yueqing Xuan

About Me

I am a research fellow in the School of Computing Technologies at RMIT University and member of Australian Research Council (ARC) Centre of Excellence for Automated Decision-Making and Society (ADM+S). I completed my PhD in Feb 2026. I work alongside my supervisors Prof Jeffrey Chan, Prof Mark Sanderson and Dr Kacper Sokol on explainability and fairness in Machine Learning and Recommender Systems. Specifically, my research aims at advancing fairness and explainability of machine learning systems by explicitly integrating user diversity into both system design and evaluation.

I have recently completed a master's degree in Information Technology at the University of Melbourne, with specialisation in Artificial Intelligence (AI). I have completed a research project and finished my master's thesis that is concerned with NLP. Specifically, we proposed a multi-modal Entity Linker that automatically recognises the object(s) of interest in the natural language commands. It is also capable of linking the textual mentions of entities to visual mentions of entities that correspond to the same real-world entities. I received a grade of 91 (First Class Honours / H1) for the research project. More details about my work are described here.

Upon finishing my research project, I continued working on the (parent) research project Humanoid robotic arm control through verbal commands as a casual research assistant at UniMelb. This project intends to develop a framework allowing people living with upper-limb disabilities to manipulate a robotic arm to perform various reaching and grasping movements. My work included deploying an off-the-shelf voice activation engine and an Automatic Speech Recognition (ASR) system for the robotic arm framework. I have further integrated the framework with a humanoid robot - Reachy robot, for real-time control using voice commands. I was also responsible for controlling and interacting with Reachy to carry out various verbal commands in the lab environment.

Education

• Supervised by Prof Jeffrey Chan, Prof Mark Sanderson, and Dr Kacper Sokol.
• PhD Scholarship recipient of the ARC Centre for Automated Decision-Making and Society (ADM+S).
• Research focuses on explainability and fairness in Machine Learning and Recommender Systems.

Specialised in Artificial Intelligence

• WAM: 84.50
• Relevant Coursework: Research Project, Natural Language Processing, Computer Vision, Statistical Machine Learning, etc.
• Achievements: Recognised on the Dean's Honours List 2021 at the University of Melbourne for top 5% students. Awarded Melbourne Graduate Scholarship 2022.

Major in Accounting and Information Systems

• WAM: 74.50
• Relevant Coursework: Database Management and Big Data, Information System in Business, Business System Analysis, Programming for Business, etc.
• Achievements: High Distinction (HD) average in programming subjects, Distinction (D) average in accounting subjects, Second place in COMP1531 (Software Engineering Fundamentals).

Publications

Conference and Journal Papers

• Yueqing Xuan, Kacper Sokol, Mark Sanderson, and Jeffrey Chan. "Diversity-Augmented Negative Sampling for Implicit Collaborative Filtering". ACM Web Conference 2026 (WWW '26), 2026, https://doi.org/10.1145/3774904.3792346.
• Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan. "Evaluating and Addressing Fairness Across User Groups in Negative Sampling for Recommender Systems". Conference on Information and Knowledge Management (CIKM), 2025, pp. 3720-3729, https://doi.org/10.1145/3746252.3761263.
• Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan. "Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse". Machine Learning, 114, no.8 (2025): 187, https://link.springer.com/article/10.1007/s10994-025-06821-1
• Kacper Sokol*, Edward Small*, Yueqing Xuan*. "Navigating explanatory multiverse through counterfactual path geometry". Machine Learning, 114, no.6 (2025): 1-33, https://link.springer.com/article/10.1007/s10994-025-06769-2. *Equal contribution.
• Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan, "Leveraging Complementary AI Explanations to Mitigate Misunderstanding in XAI". 2025 IEEE Swiss Conference on Data Science (SDS), 2025, pp. 174-177, https://doi.org/10.1109/SDS66131.2025.00034.
• Yueqing Xuan, Edward Small, Kacper Sokol, Danula Hettiachchi, Mark Sanderson. "Comprehension Is a Double-Edged Sword: Over-Interpreting Unspecified Information in Intelligible Machine Learning Explanations". International Journal of Human-Computer Studies (IJHCS), 2024, 103376, ISSN 1071-5819, https://doi.org/10.1016/j.ijhcs.2024.103376.

Workshop Papers

• Edward Small*, Yueqing Xuan*, Danula Hettiachchi* and Kacper Sokol*. "Helpful, Misleading or Confusing: How Humans Perceive Fundamental Building Blocks of Artificial Intelligence Explanations". In: Human-Centered Explainable AI (HCXAI) Workshop at CHI. 2023. [Slides]
• Kacper Sokol*, Edward Small*, Yueqing Xuan*. "Navigating Explanatory Multiverse Through Counterfactual Path Geometry". In: ICML (International Conference on Machine Learning) Workshop on Counterfactuals in Minds and Machines. 2023.

Professional Activities

Visiting Scholar

• University of Amsterdam.
• USI Lugano.

Paper Reviewing

• DMKD(2026), WSDM (2026), SIGIR (2025), SIGIR (2023).

Organisation

• Organiser, RMIT Recommender and Responsible AI(R2AI)ReadingGroup.

Funding

• ADM+S Travel Grant.
• RACE Computing Recourse.
• AMSI scholarship recipient

Work Experience

RMIT University, Melbourne

• COSC1285 Algorithm and Analysis: 1st year M.Sc. course at School of Computing Technologies.

RMIT University, Melbourne

• COSC2123 Algorithm and Analysis: 2rd year B.Sc. course at School of Computing Technologies.

The University of Melbourne, Melbourne

• Worked on the research project: Humanoid robotic arm control through verbal commands.
• Successfully integrated the Porcupine wake word engine and IBM Watson speech recognition system into the robotic arm control framework, and integrated the framework with the anthropomorphic robotic limb.
• Controlled and interacted with the humanoid robot for real-time control using verbal (natural language) commands.
• Demos of the experiments conducted in the lab environment can be found here.

The Altius Group, Sydney

• Effectively managed, configured, and troubleshoot a range of IT-related systems.
• Responsibly implemented and administrated database documentation, guidelines, policies, and procedures.
• Performed application and hardware configuration deployment and troubleshooting.

Shanghai Institute of Technical Physics of the Chinese Academy of Sciences, Shanghai

• Worked effectively in the Big Data team to analyse Geographic Information System (GIS) data by utilising the ContextCapture software.
• Designed and maintained database architecture, data structures, tables, dictionaries, and naming conventions to ensure the accuracy and completeness of all data master files.
• Performed the operational establishment and preventive maintenance of backups, recovery procedures, and enforced security and integrity controls.

Skills

Technical Skills

• Python libraries for machine learning: Frequently use PyTorch, Keras, OpenCV, Scikit-learn, NumPy, and Pandas.
• Programming Languages: Proficient in Python. Confident in JavaScript and Java. Familiar with C, SQL, and NetLogo.
• Business Intelligence Software: Familiar with SAP Lumir, SAS, and Power BI.

Language

• English: Pearson Test of English (Academic) - achieved 90 overall (IELTS Equivalent: Band 9), at least 83 for each of the 4 test components.
• Mandarin: Native speaker.

Personal

• Strong teamwork skills: Working smoothly and effectively as a team member through collaboration, effective communication, and providing assistance in a positive manner.
• Problem-solving skills: Developing both creative and practical solutions to solve identified issues and discrepancies, and contributing to effective outcomes.
• Time management skills: Managing time effectively through prioritising and making judgments about what is urgent or important, and coordinating different tasks to meet deadlines.