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Dr Kate Han's Outputs (13)

DEFEG: Deep Ensemble with Weighted Feature Generation (2023)
Journal Article
Vu Luong, A., Tien Nguyen, T., Han, K., Hieu Vu, T., McCall, J., & Wee-Chung Liew, A. (2023). DEFEG: Deep Ensemble with Weighted Feature Generation. Knowledge-Based Systems, 275, Article 110691. https://doi.org/10.1016/j.knosys.2023.110691

With the significant breakthrough of Deep Neural Networks in recent years, multi-layer architecture has influenced other sub-fields of machine learning including ensemble learning. In 2017, Zhou and Feng introduced a deep random forest called gcFores... Read More about DEFEG: Deep Ensemble with Weighted Feature Generation.

Optimising Public Transport Through the Integration of Micro and Macro-level Simulations (2025)
Presentation / Conference Contribution

The European Commission and the UK aim for net zero emissions in transportation by 2050. This work explores the potential of connected and autonomous vehicles (CAVs) to support this goal by enhancing public transport (PT) via strategic deployment wit... Read More about Optimising Public Transport Through the Integration of Micro and Macro-level Simulations.

Automating Business Process to Enhance Organisational Efficiency and Productivity: Using Academic Intervention at Salford Business School as a Case Study (2025)
Presentation / Conference Contribution

Organisations, particularly large ones with multiple stakeholders involved in their business processes, frequently face challenges related to process efficiency and productivity, leading to wasted resources, time, and effort, ultimately reducing over... Read More about Automating Business Process to Enhance Organisational Efficiency and Productivity: Using Academic Intervention at Salford Business School as a Case Study.

Digital Transformation in High Education Institutions (HEs) in the Post-Pandemic Era: Investigation of Students’ Study Behaviour at Salford Business School (2024)
Presentation / Conference
Ubah-Nwoha, D., Chen, Y., & Han, K. (2024, September). Digital Transformation in High Education Institutions (HEs) in the Post-Pandemic Era: Investigation of Students’ Study Behaviour at Salford Business School. Paper presented at BERA (British Educational Research Associate) Conference, Manchester

This study examines Digital Transformation (DT) in High Education Institutions (HEIs) and how the pandemic has enabled the reimagination of the education system (Quilter-Pinner & Ambrose, 2020). The pace at which digital technologies have evolved ove... Read More about Digital Transformation in High Education Institutions (HEs) in the Post-Pandemic Era: Investigation of Students’ Study Behaviour at Salford Business School.

A Novel Surrogate Model for Variable-Length Encoding and its Application in Optimising Deep Learning Architecture (2024)
Presentation / Conference Contribution

Deep neural networks (DNN) has achieved great successes across multiple domains. In recent years, a number of approaches have emerged on automatically finding the optimal DNN configurations. A technique among these approaches which show great promise... Read More about A Novel Surrogate Model for Variable-Length Encoding and its Application in Optimising Deep Learning Architecture.

VISTA: A Variable Length Genetic Algorithm and LSTM-Based Surrogate Assisted Ensemble Selection algorithm in Multiple Layers Ensemble System (2024)
Presentation / Conference Contribution

We proposed a novel ensemble selection method called VISTA for multiple layers ensemble systems (MLES). Our ensemble model consists of multiple layers of ensemble of classifiers (EoC) in which the EoC in each layer is trained on the data generated by... Read More about VISTA: A Variable Length Genetic Algorithm and LSTM-Based Surrogate Assisted Ensemble Selection algorithm in Multiple Layers Ensemble System.

Generative AI assisted Life-long Learning in Higher Education: A Case Study of Coding Learning for Business Students at Salford Business School (2024)
Book Chapter
Han, K. (2024). Generative AI assisted Life-long Learning in Higher Education: A Case Study of Coding Learning for Business Students at Salford Business School. In Leading Global Excellence in Pedagogy: Augmenting Teaching Excellence: Embracing the future of Education with AI and Emerging Technologies. ‎ IFNTF Publishing

In today's evolving business landscape, professionals are required to possess a broad skill set, encompassing fundamental business knowledge and digital proficiencies. This heightened demand for diverse technical skills has raised the learning bar fo... Read More about Generative AI assisted Life-long Learning in Higher Education: A Case Study of Coding Learning for Business Students at Salford Business School.

On Discovering Optimal Trade-Offs When Introducing New Routes in Existing Multi-modal Public Transport Systems (2023)
Presentation / Conference Contribution

While self-driving technology is still being perfected, public transport authorities are increasingly interested in the ability to model and optimise the benefits of adding connected and autonomous vehicles (CAVs) to existing multi-modal transport sy... Read More about On Discovering Optimal Trade-Offs When Introducing New Routes in Existing Multi-modal Public Transport Systems.

Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms (2021)
Presentation / Conference Contribution

The past five years have seen a rapid development of plans and test pilots aimed at introducing connected and autonomous vehicles (CAVs) in public transport systems around the world. Using a real-world scenario from the Leeds Metropolitan Area as a c... Read More about Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms.

VEGAS: A Variable Length-Based Genetic Algorithm for Ensemble Selection in Deep Ensemble Learning (2021)
Presentation / Conference Contribution

In this study, we introduce an ensemble selection method for deep ensemble systems called VEGAS. The deep ensemble models include multiple layers of the ensemble of classifiers (EoC). At each layer, we train the EoC and generates training data for th... Read More about VEGAS: A Variable Length-Based Genetic Algorithm for Ensemble Selection in Deep Ensemble Learning.