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In an era where interdisciplinary research drives innovation, international collaboration plays a vital role in expanding knowledge and fostering new ideas. The School of Mathematical Sciences, ºìÐÓÊÓƵ University, had the distinct honor of welcoming esteemed faculty members from the School of Mathematical and Physical Sciences, University of Technology Sydney (UTS)—Professor James Brown, Dr Hanyu Gu, and Dr Matias Quiroz—for an engaging research exchange.

This visit provided a unique platform for the school and students to delve into the latest advancements in artificial intelligence, statistics, and graph theory while also strengthening academic ties between the two institutions. Through thought-provoking presentations, stimulating discussions, and knowledge-sharing sessions, participants explored cutting-edge research that is shaping the future of data science and mathematical sciences.

The event served as a testament to the power of collaboration in addressing complex challenges and driving impactful research. Below are the highlights of the presentations delivered during this enriching exchange.

Day 1: Showcasing innovative research in statistical data science and its applications from academics and researchers
 

The two-day symposium kicks off with an exciting lineup of presentations from the School of Mathematical Sciences faculty, showcasing innovative research in statistical data science and its applications. Day 1 began with Dr. Varun Kumar Ravikumar Shashikala, who presented Scientific Machine Learning Through Physics-Informed Neural Networks for Solving Heat Transfer Problems, demonstrating how AI-driven models can enhance computational efficiency in solving complex physical systems.

Following this, Associate Prof. Dr. Jason Ng Wei Jian delved into Data-driven Estimation of Subjective Thresholds: Methodology, Challenges, and Expanding Applications, exploring advanced statistical techniques for defining subjective limits in various domains. The session continues with Associate Prof. Dr. Jane K. L. Teh, who unveils the power of Principal Component Analysis (PCA) in her talk, Unmasking Patterns: Unveiling Insights Through Principal Component Analysis, illustrating how PCA can be leveraged to extract meaningful insights from high-dimensional data. It was then followed by Dr. Kai An Sim delved into graph theory with her talk on On the Burning Number of Some Families of Graphs, shedding light on mathematical techniques used to analyse the spread of information or influence in network structures.

These presentations set the stage for an engaging and thought-provoking symposium, highlighting cutting-edge research and fostering discussions on the evolving landscape of statistical data science and machine learning.

In the afternoon session of Day 1, esteemed researchers from the University of Technology Sydney (UTS) took the stage to present their latest findings, offering fresh perspectives on statistical modeling, graph theory, and industrial applications.

The session commenced with Dr. Matias Quiroz, who explored Traceable Bayesian Inference for Complex Models and Large-Scale Data, presenting innovative approaches to improving computational efficiency and accuracy in Bayesian analysis. 

Continuing the discussions, Dr. Hanyu Gu introduced practical applications of optimization techniques in his talk, Large Scale Combinatorial Optimisation for Industrial Applications, highlighting how advanced mathematical models drive efficiency in real-world industrial settings. Rounding off the session, Professor James Brown provided an insightful presentation on Collaboration with National Statistics Organisations – History and Future Potential, discussing the evolving role of academic research in shaping national statistical methodologies and policies.

The afternoon presentations sparked engaging discussions, reinforcing the value of cross-institutional collaboration in tackling complex challenges in data science, statistics, and applied mathematics.

Day 2: Showcasing Emerging Research from Postgraduate Students

The second day of the symposium was dedicated to the next generation of researchers, featuring presentations from postgraduate students pursuing the Master of Science in Actuarial Science, Master of Science in Mathematical Sciences and PhD in Mathematical Sciences at the School of Mathematical Sciences, ºìÐÓÊÓƵ University. This session highlighted their innovative research across diverse domains, from medical diagnostics to financial analytics and mathematical modeling.

The session began with Jing Xuan Lee, who presented on Epilepsy Seizure Detection and Prediction Using a Moth-Flame Optimisation Based One-dimensional Convolutional Neural Network, showcasing an AI-driven approach to enhancing epilepsy prediction for improved healthcare outcomes. Following this, Yan Mun Lau discussed the Impact of Climate Factors on Hand, Foot, and Mouth Disease in Malaysia: A Generalised Linear Model Approach, offering valuable insights into the relationship between environmental factors and disease transmission.

Shifting towards finance and sustainability, Shahmalarani Chandran explored The Impact of ESG Practices on Financial Performance of Malaysian Firms: A GMM Analysis, demonstrating how generalised method of moment (GMM) can be leveraged to analyze the role of Environmental, Social, and Governance (ESG) factors in corporate performance. Next, Indranil Ghosh introduced a novel approach in mathematical modeling with his talk on A Gradient-based Discrete Time-Delayed Optimisation Algorithm for Fractional Order Infectious Disease Models with Caputo-Fabrizio Fractional Derivative, contributing to the field of epidemiological modeling.

The session concluded with Jourdan D’orville, who presented on The Regularity of Nonlinear Equations, delving into advanced mathematical theories that enhance our understanding of nonlinear systems and their applications.
This PGR session provided a valuable platform for young researchers to share their findings, engage in academic discussions, and receive feedback from peers and experts, further enriching the collaborative spirit of the symposium.

This event underscored the importance of cross-institutional collaboration in advancing research and fostering innovation. By exchanging knowledge and expertise, researchers from ºìÐÓÊÓƵ University and UTS continue to push the boundaries of statistical data science, artificial intelligence, and mathematical applications.
 

Dr Ang Siew Ling and Dr Cheong Huey Tyng
School of Mathematical Sciences
@email  and @email