Associate Dean, Data Science and AI Discipline
School of Computing Technologies
RMIT University

Building 14
Level 8, Room 15
City Campus, RMIT University

Phone: +613 992 55270
Email: [first name] dot [last name] at rmit dot edu dot au
OrcID, LinkedIn, Google Scholar, RMIT Homepage

Hi! Welcome to my webpage. I am a researcher in machine learning and data science, with a focus on responsible AI and recommender systems. I also have interests in the areas of social network analysis and integrated optimisation-machine learning approaches, and applications in health, AI for good, Industry 5.0, transportation and agriculture.

Contact me if you cannot access a paper or interested in doing research with me. Always happy to discuss and looking for opportunities to supervise or/and collaborate.

Recruiting Students

I’m recruiting PhD and Honours students. If you are are interested in working with me in one of my areas (see research projects and publications ) and have excellent results, please don’t hesitate in contacting me. There are a number of scholarships (APA, IPRS, RPIS, RPS, VCPS) and funded places available.

Quick Links

Code and datasets are available here.

Supervision

Current Students:

Edward Small (PhD) – Fair and Explainable AI
Tung Lam Ngo (PhD) – Bayesian Optimisation
Bjeorn Kommannder (PhD) – Social Network Analysis
Imesh Ekanayake (PhD) – Fair and Private Machine Learning
Md Faisal Ahmed (PhD) – User Simulations in Recommender Systems
Zoha Usama (PhD) – Medical Image Processing
Minh Hoang Tran (PhD) – Software Debugging Baselines
Laura Gartry (PhD) – AI in Newsrooms
Wenhao Zhou (PhD) – Fair Allocation in Crowdsourcing
Xinye Wanyan (PhD) – Simulation in Recommender Systems
Jessica Kahn (PhD) – Debiasing in ML
Haoli Wang (PhD) – Smart and Fair Routing in Crowdsourcing
Thukaraka Pakeerathan (PhD) – Fair LLMs
Imalsha Sanduni Ubayawickrema (PhD) – Explainable Recommender Systems
Jiapeng Du (PhD) – Fake Review Detection
Tong Zhou (PhD) – Medical NLP

Graduated Students:

Yueqing Xuan (PhD, 2026) – Explainable and Fair Recommender Systems
Parthasarathy Nadarajan (PhD, 2026) – Smart Vehicle Navigation
Hiruni Kegalle (PhD, 2025) – Involuntary 3rd Party Effects in Automated Decision Making Systems
Ruimin Chu (PhD, 2025) – Machine Learning for Fuel-loss Detection
Yufan Kang (PhD, 2025) – Multi-party Fairness
Ying Zhi Cheong (PhD, 2025) – Chip Design Optimisation
Chao Zhu (MCS, 2024) – Event Detection from Social Media
Sichen Zhao (PhD, 2023) – Representation Learning
Servet Kocak (MCS, 2023) – Machine Learning for Fuel-loss Detection
Lachlan Coff (PhD, 2022) – Bioinformatics in Fish Management
Nasrin Sultana (PhD, 2022) – Learning to Optimise
Sajal Halder (PhD, 2022) – Itinerary Recommendation
Kendall Taylor (PhD, 2022) – Multi-objective Optimisation
Chaminda Bulumulla (PhD, 2022) – Agent-Diffussion modelling simulations
Jiaman Ma (PhD, 2021) – Smart Traffic / Smart City
Shiwei Jiang (PhD, 2020) – NLP
Yassien Shaalan (PhD, 2020) – Learning to Rank Products
Naif Almusallam (PhD, 2018) – Feature Selection in Streams
Kushani Perera (PhD, 2018) – Feature Selection
Chen Jin (PhD, 2017) – Large population Evolutionary Computing
Kwan Hui Lim (PhD, 2017) – Itinerary Recommendation
Wei Shao (PhD, 2017) – Spatio-Temporal Analysis
Yediya Juan (MIT, 2017) – Matrix Factorisation
Tanya Srinidhi (Data 61 Summer Intern, 2017)
Shyamsundar Dorairaj (MCS, 2016)
Kendall Taylor (Nicta/Data 61 Summer Intern, 2016) – BCS Honours, RMIT University
Han Yi (PhD, 2016) – Tripalocal & Post-Doctoral Researcher, University of Melbourne
You Han Xia (MCS, 2015) – PhD, RMIT University
Akshay Mahajan (MCS, 2015)
Yichen Li (MIT, 2015) – PhD, University of Melbourne
Oscar Fabian Correa Guerrero (MCS, 2014) – PhD, University of Melbourne
Kang Hu (MIT, 2014)
Zhangyue Cheng (MIT, 2014)
Bingzan (Lillian) Liang (Intern & MIT, 2013)
Tian Fang (MIT, 2013)
Samantha Lam (MPhil, 2013)
Andrey Kan (PhD, 2012) – Researcher at WEHI, Melbourne
Erik Aumayr (Intern, 2010) – PhD Candidate at INSIGHT@NUIG, Ireland