Keynote Speakers

Dr. Don Kulasiri, Professor

Centre for Advanced Computational Solutions (C-fACS), Ag and Life Science Faculty, Lincoln University, Christchurch, New Zealand

Biography: Dr. Don Kulasiri is a Professor in Centre for Advanced Computational Solutions (C-fACS), Ag and Life Science Faculty, Lincoln University, Christchurch, New Zealand. He is an internationally recognised researcher in computational and mathematical biology, environmental modelling, and the mathematical and physical sciences. His multidisciplinary work focuses on understanding the mathematical basis of biological and environmental phenomena, with applications ranging from modelling memory formation and Alzheimer’s disease to developing AI-driven technologies such as WaphHound? for plant disease detection. A Fellow of the Modelling and Simulation Society of Australia and New Zealand, he has led major government-funded research programmes in New Zealand and abroad, including projects on water quality, food innovation, wine production, and urban agriculture. He has held visiting professorships at the University of Oxford, Princeton University, Stanford University, and Peking University, supervised over 60 PhD students, and continues to advance research at the interface of stochastic mathematics, computational biology, and environmental systems.

Topic: Systems Biology Research in Alzheimer’s Disease & Model Reduction Using Machine Learning

Abstract: In this talk, an overview of systems biology research related to Alzheimer's disease in the Centre for Advanced Computational Solutions (C-fACS) at Lincoln University, New Zealand, is presented. The Second part of the talk is about reducing large pathways models to simpler ones using machine learning. We have selected the neurobiological models for this exercise. Mathematical details are kept to minimum and we explain the insights obtained by our research.

Dr. Sandhya Samarasinghe, Professor

Centre for Geospatial and Computing Technologies, Lincoln University, Christchurch, New Zealand

Biography: Dr. Sandhya Samarasinghe is a Professor in Computational Systems Biology and AI at Lincoln University, New Zealand. She holds a PhD and MSc (Engineering) from Virginia Tech, USA, and MSc (Engineering) from Peoples’ Friendship University in Russia. Her research interests include AI and Machine Learning to understand genomics data and model protein interaction networks to understand biological function and disease mechanisms. She has been invited as a Visiting Scientist at Oxford University, UK, and Princeton and Stanford University in the USA. She has published over 200 research publications including books, book chapters, research articles and conference papers.

Topic: AI Modelling of Protein Networks – Mammalian Cell Cycle

Abstract: Proteins are vital to life as they carry out all biological functions. Proteins form networks or pathways to accomplish these tasks. However, these networks are complex due to many proteins interacting in complex ways making it a challenge to understand how they function and how they succumb to diseases. AI and Machine Learning have emerged as contenders to model complexity of protein-protein interaction (PPI) networks and understand their behaviour. In this talk, a Neural Networks based AI model of the core PPI network underlying the operation of the mammalian cell cycle is presented highlighting model’s ability to accurately mimic the temporal behaviour of all proteins in the network over the course of cell cycle. The success of the model suggests its potential to apply to other PPI networks and other contexts.