Associate Professor Jeffrey Chan
Assistant Associate Dean, Data Science & Artificial Intelligence
Details
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College: School of Computing Technologies
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Department: School of Computing Technologies
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Campus: City Campus Australia
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jeffrey.chan@rmit.edu.au
Open to
- Masters Research or PhD student supervision
About
Jeffrey is an Associate Professor in the School of Computing Technologies. His research interests lie in machine learning, recommender systems, responsible AI, data-driven optimisation and interdisciplinary research that combines these fields to solve social and industry-based applications. He has worked with industry and non-profit partners in retail, sustainability, energy, manufacturing and health.
Research fields
- 460501 Data engineering and data science
- 460510 Recommender systems
- 460805 Fairness, accountability, transparency, trust and ethics of computer systems
- 460210 Satisfiability and optimisation
- 460506 Graph, social and multimedia data
- 461103 Deep learning
UN sustainable development goals
- 10 Reduced Inequalities
- 5 Gender Equality
- 3 Good Health and Well Being
- 16 Peace, Justice and Strong Institutions
Supervisor projects
- Fostering Creativity to Enhance Critical Problem-Solving Skills of Future Engineering Managers in Australia
- 16 Sep 2024
- AI in Medical Image Analysis
- 3 Jun 2024
- An Improvement in Intelligent Incident Management for Software-Intensive Systems with Large Language Models
- 26 Feb 2024
- Fair influence diffusion
- 16 Feb 2024
- Bayesian Optimisation
- 13 Dec 2023
- Prescriptive Analytics: Big Data and Machine Learning for Decision Making
- 23 Oct 2023
- Design and Implementation of an energy-efficient recommendation system and enhance data security through Blockchain in the cloud server.
- 23 Oct 2023
- 3D model construction for a target class using XAI
- 23 Aug 2023
- Developing AI-driven circular economy approaches for sustainable food and waste management systems
- 27 Jul 2023
- Automated Monitoring of Online Communities
- 27 Mar 2023
- High-dimensional Bayesian Optimization via Evolutionary Computation
- 26 Sep 2022
- Developing Machine Learning and Data Mining Techniques for Fuel Loss Detection at Service Stations
- 31 Aug 2022
- Multi-stimuli thin films for tomorrows electronics and optics
- 18 Aug 2022
- Fairness-Aware and Privacy-Preserving Recommender System
- 25 Jul 2022
- Bias and Fairness in ADM for time-series and sequential data
- 1 Apr 2022
- Disentangled Representation Learning for Spatio-temporal Data
- 31 Mar 2022
- Topic-sentiment mixture analysis
- 10 Dec 2021
- Systems for Automated Decision-Making
- 8 Nov 2021
- Developing Machine Learning and Data Mining Techniques for Fuel Loss Detection at Service Stations
- 15 Jun 2021
- Fairness and Privacy-Preserving for Navigation Systems
- 7 Apr 2021
- Detecting Early Health Deterioration in Aged Care
- 27 Apr 2020
- Integrating Social Network Diffusion Into Bdi-Based Simulations: Application Focus on Large-Scale Evacuations
- 8 Feb 2019
- Blockchain-based AI-enabled Data Protection for the Internet of Things
- 3 Sep 2018
- Itinerary Recommendation based on Deep Learning
- 1 Aug 2018
- Learning to Optimise Routing Problems using Deep Neural Networks
- 2 Jul 2018
- Preference Learning for Multi-objective Optimisation Problems
- 1 May 2018
- Investigation of Blood Fluke Infection in Bluefin Tuna With Glycoinformatics
- 1 Feb 2018
- Scalable Parallel Evolutionary Optimisation based on High Performance Computing
- 17 Mar 2017
- Improving Intelligent Public Transport Systems for Smart Cities
- 1 Mar 2017
- Towards An Efficient Unsupervised Feature Selection Methods for High-Dimensional Data
- 5 Oct 2016
- Learning spatiotemporal patterns for monitoring smart cities and infrastructure
- 4 Oct 2016
- Mining User-Generated Texts via Neural Classification
- 18 Jul 2016
- Spam Detection and Aggregation of Reviews Using Minimal Supervision
- 5 Jul 2016
Teaching interests
Jeffrey is an experienced and passionate educator, and has more than 10 years teaching at the tertiary level. He has taught and developed fundamental computer science courses such as Algorithms & Analysis, an introductory algorithms and data structure course, Social Media and Network Analytics and Machine Learning. He has also engaged with industry partners and students when coordinating the WIL course Data Science Projects. Jeffrey's teaching philosophy is to guide and help students to learn and gain confidence to become independent learners and practitioners.
Research interests
Jeffrey's high level research interest lie in Artificial Intelligence, Machine learning and Data Science.
He focuses on Responsible AI, Recommender Systems, Data-driven Optimisation.
