Jeffrey Chan
YOU?
Author Swipe
View article: Temporal-Aware User Behaviour Simulation with Large Language Models for Recommender Systems
Temporal-Aware User Behaviour Simulation with Large Language Models for Recommender Systems Open
Large Language Models (LLMs) demonstrate human-like capabilities in language understanding, reasoning, and generation, driving interest in using LLM-based agents to simulate human feedback in recommender systems. However, most existing app…
View article: A Review on the Applications of GANs for 3D Medical Image Analysis
A Review on the Applications of GANs for 3D Medical Image Analysis Open
Three-dimensional medical images, such as those obtained from MRI scans, offer a comprehensive view that aids in understanding complex shapes and abnormalities better than 2D images, such as X-ray, mammogram, ultrasound, and 2D CT slices. …
View article: "Nuisance is Better Than Nothing?": Exploring How Pedestrians and Cyclists Perceive Automated E-Scooter Alerts in Shared Spaces MHCI023
"Nuisance is Better Than Nothing?": Exploring How Pedestrians and Cyclists Perceive Automated E-Scooter Alerts in Shared Spaces MHCI023 Open
Electric scooters (e-scooters) offer flexible urban mobility but raise safety concerns in shared spaces. This study investigates how e-scooters can better communicate their presence to pedestrians and cyclists in shared active mobility env…
View article: Diverse Negative Sampling for Implicit Collaborative Filtering
Diverse Negative Sampling for Implicit Collaborative Filtering Open
Implicit collaborative filtering recommenders are usually trained to learn user positive preferences. Negative sampling, which selects informative negative items to form negative training data, plays a crucial role in this process. Since i…
View article: FairDRL-ST: Disentangled Representation Learning for Fair Spatio-Temporal Mobility Prediction
FairDRL-ST: Disentangled Representation Learning for Fair Spatio-Temporal Mobility Prediction Open
As deep spatio-temporal neural networks are increasingly utilised in urban computing contexts, the deployment of such methods can have a direct impact on users of critical urban infrastructure, such as public transport, emergency services,…
View article: Real-time fuel leakage detection via online change point detection
Real-time fuel leakage detection via online change point detection Open
Early detection of fuel leakage at service stations with underground petroleum storage systems is a crucial task to prevent catastrophic hazards. Current data-driven fuel leakage detection methods employ offline statistical inventory recon…
View article: PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation
PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation Open
Traditional offline evaluation methods for recommender systems struggle to capture the complexity of modern platforms due to sparse behavioural signals, noisy data, and limited modelling of user personality traits. While simulation framewo…
View article: Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse
Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse Open
Algorithmic recourse suggests actions to individuals who have been adversely affected by automated decision-making, helping them to achieve the desired outcome. Knowing the recourse, however, does not guarantee that users can implement it …
View article: How robust is your fair model? Exploring the robustness of prominent fairness strategies
How robust is your fair model? Exploring the robustness of prominent fairness strategies Open
With the introduction of machine learning in high stakes decision-making, ensuring algorithmic fairness has become an increasingly important task. To this end, many mathematical definitions of fairness have been proposed, and a variety of …
View article: Leveraging machine learning in nursing: innovations, challenges, and ethical insights
Leveraging machine learning in nursing: innovations, challenges, and ethical insights Open
Aim/objective This review aims to provide a comprehensive analysis of the integration of machine learning (ML) (1) in nursing by exploring its implications on patient care, nursing practices, and healthcare delivery. It highlights current …
View article: BOIDS: High-Dimensional Bayesian Optimization via Incumbent-Guided Direction Lines and Subspace Embeddings
BOIDS: High-Dimensional Bayesian Optimization via Incumbent-Guided Direction Lines and Subspace Embeddings Open
When it comes to expensive black-box optimization problems, Bayesian Optimization (BO) is a well-known and powerful solution. Many real-world applications involve a large number of dimensions, hence scaling BO to high dimension is of much …
View article: An effective approach for early fuel leakage detection with enhanced explainability
An effective approach for early fuel leakage detection with enhanced explainability Open
Leakage detection at service stations with underground storage tanks containing hazardous products, such as fuel, is a critical task. Early detection is important to halt the spread of leaks, which can pose significant economic and ecologi…
View article: Watch Out! E-scooter Coming Through!: Multimodal Sensing of Mixed Traffic Use and Conflicts Through Riders' Ego-centric Views
Watch Out! E-scooter Coming Through!: Multimodal Sensing of Mixed Traffic Use and Conflicts Through Riders' Ego-centric Views Open
E-scooters are becoming a popular means of urban transportation. However, this increased popularity brings challenges, such as road accidents and conflicts when sharing space with traditional transport modes. An in-depth understanding of e…
View article: Leveraging Complementary AI Explanations to Mitigate Misunderstanding in XAI
Leveraging Complementary AI Explanations to Mitigate Misunderstanding in XAI Open
Artificial intelligence explanations can make complex predictive models more comprehensible. To be effective, however, they should anticipate and mitigate possible misinterpretations, e.g., arising when users infer incorrect information th…
View article: Watch Out E-scooter Coming Through: Multimodal Sensing of Mixed Traffic Use and Conflicts Through Riders Ego-centric Views
Watch Out E-scooter Coming Through: Multimodal Sensing of Mixed Traffic Use and Conflicts Through Riders Ego-centric Views Open
E-scooters are becoming a popular means of urban transportation. However, this increased popularity brings challenges, such as road accidents and conflicts when sharing space with traditional transport modes. An in-depth understanding of e…
View article: Deep Learning of Dynamic POI Generation and Optimisation for Itinerary Recommendation
Deep Learning of Dynamic POI Generation and Optimisation for Itinerary Recommendation Open
Itinerary recommendation involves suggesting a sequence of Points of Interests (POIs) that users obtain maximum satisfaction under a time budget. Existing models have three challenges. First, they model user interest as non-time dependent,…
View article: BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings
BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings Open
When it comes to expensive black-box optimization problems, Bayesian Optimization (BO) is a well-known and powerful solution. Many real-world applications involve a large number of dimensions, hence scaling BO to high dimension is of much …
View article: Perception and acceptance of high seaweed content novel foods (Ulva spp. and Undaria pinnatifida) across New Zealand and Singaporean consumers
Perception and acceptance of high seaweed content novel foods (Ulva spp. and Undaria pinnatifida) across New Zealand and Singaporean consumers Open
Edible seaweeds are gaining global popularity as nutritious and sustainable food sources, extending beyond Asian into Western diets. To investigate consumer perception and acceptance of high seaweed content foods, two novel products, seawe…
View article: Learning to optimise general TSP instances
Learning to optimise general TSP instances Open
The Travelling Salesman Problem is a classical combinatorial optimisation problem (COP). In recent years, learning to optimise approaches have shown success in solving TSP problems. However, they focus on one type of TSP instance, where th…
View article: Real-time Fuel Leakage Detection via Online Change Point Detection
Real-time Fuel Leakage Detection via Online Change Point Detection Open
Early detection of fuel leakage at service stations with underground petroleum storage systems is a crucial task to prevent catastrophic hazards. Current data-driven fuel leakage detection methods employ offline statistical inventory recon…
View article: Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse
Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse Open
Algorithmic recourse suggests actions to individuals who have been adversely affected by automated decision-making, helping them to achieve the desired outcome. Knowing the recourse, however, does not guarantee that users can implement it …
View article: Healthcare worker attitudes on routine non-urological preoperative urine cultures: a qualitative assessment
Healthcare worker attitudes on routine non-urological preoperative urine cultures: a qualitative assessment Open
Objective: Many preoperative urine cultures are of low value and may even lead to patient harms. This study sought to understand practices around ordering preoperative urine cultures and prescribing antibiotic treatment. Design: Open-ended…
View article: Long-term Fairness in Ride-Hailing Platform
Long-term Fairness in Ride-Hailing Platform Open
Matching in two-sided markets such as ride-hailing has recently received significant attention. However, existing studies on ride-hailing mainly focus on optimising efficiency, and fairness issues in ride-hailing have been neglected. Fairn…
View article: A Wearable Personalised Sonification and Biofeedback Device to Enhance Movement Awareness
A Wearable Personalised Sonification and Biofeedback Device to Enhance Movement Awareness Open
Movement sonification has emerged as a promising approach for rehabilitation and motion control. Despite significant advancements in sensor technologies, challenges remain in developing cost-effective, user-friendly, and reliable systems f…
View article: Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity
Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity Open
While data-driven predictive models are a strictly technological construct, they may operate within a social context in which benign engineering choices entail implicit, indirect, and unexpected real-life consequences. Fairness of such sys…