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Complex Systems, Big Data and Informatics Initiative

The Complex Systems, Big Data and Informatics Initiative at Lincoln University aims to transform the way we perceive and solve complex problems that are in the confluence of biological, agricultural, environmental, ecological, or social domains.

Complex Systems, Big Data and Informatics Initiative

The Complex Systems, Big Data and Informatics Initiative at Lincoln University aims to transform the way we perceive and solve complex problems that are in the confluence of biological, agricultural, environmental, ecological, or social domains.

Vision

The Complex Systems, Big Data and Informatics Initiative (CSBII) at Lincoln University aims to transform the way we perceive and solve complex problems through trans-disciplinary integration of advanced domain knowledge and cutting-edge complex systems, big data and informatics methodologies to provide effective and flexible solutions to evolving grand challenges.
 
These challenges include transformations in Agriculture and Biological systems; Health, Disease and Wellbeing; Sustainable Environments, Ecosystems and Societies; and Artificial Intelligence and Digital Methodology Innovations to promote these transformations.
 
The CSBII Initiative draws on over two decades of experience and expertise by internationally-recognised and accomplished academics to provide solutions to complex problems in systems biology, ecosystems, the environment, agriculture and society through the use of:
 
* Artificial Intelligence
* Geospatial systems
* Soft computing
* Neural networks
* Data mining and big data analytics
* Agent-based modelling
* Fuzzy cognitive maps
* Computational and mathematical modelling
* Dynamical systems modelling
* Systems biology and bioinformatics
* Digital and software engineering systems
* Machine learning
* Network modelling
* Conceptual/philosophical frameworks and theories of systems. 

Scope

The CSBI Initiative aspires to excel in transdisciplinary integration of complex systems, big data analytics and informatics frameworks with domain knowledge to address various challenges in:

* Disease, health and wellbeing – through understanding of biology and computational systems biology and bioinformatics
* Healthy and sustainable environments and ecosystems – through understanding of environmental/socio-ecological systems  (land, water and energy systems and human interactions) and complex systems modelling and spatial analytics   
* Making a paradigm shift in agriculture – through digital transformation of the decisions and practices in cultivation, harvest, food innovations and supply chain management that promote healthy ecosystems, using Artificial Intelligence and big data analytics
* Transformative societies – leading policy and decision-making towards societal transformation through social networks and social intelligence analytics
* Artificial Intelligence and digital methodology innovations - leading to novel paradigms in informatics, complex systems and big data analytics.

Disease, Health and Wellbeing

Computational systems biology and bioinformatics

Recent discoveries on the structure and organisation of living organisms emphasise the view of life as a dynamically existing network of interactions (regulatory networks) functioning as systems according to principles of self-organisation.

These systems display emergent properties such as stability and robustness at all levels of organisation that arise from their inherent characteristics of complexity, self-organisation and interdependence. Proper understanding of the behaviour of these systems can lead to improved health and wellbeing and eradication of diseases. 
 
A systems approach to biology requires trans-disciplinary integration of knowledge and methods from fields including biology, engineering, computing and mathematics as well as ecology and even social sciences, especially in the area of complex adaptive systems. 
 
CSBII aims to advance research in:

* Modelling structure and behaviour of regulatory pathways that control cellular processes, and their collective dynamical systems properties based on advanced integrated computational, mathematical and conceptual modelling methods
* High throughput genomic and proteomic big data analysis for reverse engineering the structure of biological networks and discovering genetic basis of various diseases such as cancer
* Investigating the principles governing biological pattern formation and regeneration.
 
Research involves dynamical systems modelling and analysis with systems and complexity theories, neural networks, fuzzy systems, intelligent computing and data mining; graph theoretic and network modelling; ordinary and partial differential equations and stochastic modelling. 

Academic staff involved

{Kulasiri Don} Mathematical and computational modelling, stochastic modelling of environmental systems, mathematics of memory formation, computational systems biology of neurodegenerative diseases, stochastic Artificial Intelligence
{Samarasinghe Sandhya} Complex systems dynamics, Artificial Intelligence, neural networks, fuzzy cognitive maps, machine learning, computational systems biology, bioinformatics
{Verwoerd Wynand} Bioinformatics
 
And the postgraduate students working in this area. Refer to staff webpages for current PhD projects and Students and staff publications.

Healthy and Sustainable Environments and Ecosystems

Water resources and socio-ecological systems

Much of physical and natural systems that our life depends on is in a challenging state requiring holistic understanding and management. Global, regional and local water scarcity, quality and water conflicts as well as sustainability of the environment and ecosystems are chief among current challenges. 
 
This requires trans-disciplinary integration of knowledge and methods from fields including water resources engineering, water science, mathematics and computing, water policy and management, environmental management, ecology and social sciences.  
 
CSBII aims to address grand water, environmental and ecological challenges through advanced multidisciplinary complex systems, big data and informatics approaches. In particular, we aim to quantify water and natural resources as well as integrate diverse stakeholder perspectives into effective resource management solutions to promote sustainable supply, quality and security of resources and resolution of local and global problems and conflicts arising from these challenges.    
 
Research includes:
 
* Addressing water quality, scarcity and management incorporating multiple stakeholder perspectives, using fuzzy cognitive maps, neural networks, and integrated systems modelling
* Assessing the impact of land use change on quality and quantity of water resources, using GIS and spatial systems
* Assessing the impact of climate change on water, land and ecosystems, using GIS and network modelling
* Investigating the origin, spread and establishment of invasive species using statistical, network and agent based modelling. 
 

Academic staff involved

{Samarasinghe Sandhya} Complex systems dynamics, Artificial Intelligence, neural networks, fuzzy cognitive maps, machine learning, computational systems biology, bioinformatics
Prof Shahbaz Khan
Adjunct Professor
Director, UNESCO Pacific Region
Jakarta, Indonesia
Water systems modelling, UNESCO AGENDA 2030, global and regional water challenges
{Kulasiri Don} Mathematical and computational modelling, stochastic modelling of environmental systems, mathematics of memory formation, computational systems biology of neurodegenerative diseases, stochastic Artifical Intelligence
{Anthony Patricia} Agent and multi-agent based modelling, genetic algorithms, electronic commerce
{Doscher Crile} Engineering, hydrology, computer modelling, GIS, agent-based modelling

And the postgraduate students working in this area. Refer to staff webpages for current PhD projects and Students and staff publications.

Paradigm Shift in Agriculture

Digital agriculture and biological systems

Digital transformation of agriculture and food systems is creating a paradigm shift in agriculture brought about by the major developments in digital technology. 
 
It is the most important transformation globally, with many challenges that require the integration of a number of domains and areas of expertise into digital frameworks to improve decision-making, productivity, efficiency and environmental and ecosystem sustainability.
 
CSBII aims to accelerate and contribute to the digital transformation of agriculture and food systems through multi-disciplinary integration of context knowledge with advanced complex systems, big data analytics and informatics frameworks to address some key challenges in local and global contexts.

Research includes:
 
* Harvest optimisation through computer vision, image processing and robotics
* Robotic detection of diseases through neural networks and big data analytics
* Intelligent farm decision-making through Artificial Intelligence and big data analytics
* Smart irrigation through smart sensor networks, mobile applications.
 

Academic staff involved

{Safa Majeed} Energy systems modelling, agricultural engineering
{Anthony Patricia} Agent and multi-agent based modelling, genetic algorithms, electronic commerce
{Charters Stuart} Software engineering, visualisation
{Samarasinghe Sandhya} Complex systems dynamics, Artificial Intelligence, neural networks, fuzzy cognitive maps, machine learning, computational systems biology, bioinformatics
{Kulasiri Don} Mathematical and computational modelling, stochastic modelling of environmental systems, mathematics of memory formation, computational systems biology of neurodegenerative diseases, stochastic Artifical Intelligence

And the postgraduate students working in this area. Refer to staff webpages for current PhD projects and Students and staff publications.

Transformative Societies

Social intelligence analytics

Social transformation is the most notable impact of digital age. It affects the way we interact and express ourselves in thought, emotion, speech and action. These activities have given rise to large-scale social networks and big data containing a wealth of information that can be mined for greater societal benefit.   
 
CBSII aims to accelerate and contribute to the digital transformation of society through the multi-disciplinary integration of social dimensions with advanced complex systems, big data analytics and informatics frameworks to address key challenges.
 
The challenges range from understanding collective perceptions on various issues and events and their trends to ascertain levels of social intelligence, and how they can be effectively analysed and incorporated into decision and policy-making processes concerning important aspects of societal wellbeing. 
 
Research includes:
 
* Understanding community resilience and adaptation to disasters such as earthquakes through emotion identification and analysis using Artifical Intelligence and agent-based modelling
* Decision and policy-making based on collective stakeholder perceptions using fuzzy cognitive maps and neural networks
* Intelligent social decision-making based on social networks, Artificial Intelligence and big data analytics.
 

Academic staff involved  

{Anthony Patricia} Agent and multi-agent based modelling, genetic algorithms, electronic commerce
{Samarasinghe Sandhya} Complex systems dynamics, Artificial Intelligence, neural networks, fuzzy cognitive maps, machine learning, computational systems biology, bioinformatics
 
And the postgraduate students working in this area. Refer to staff webpages for current PhD projects and Students and staff publications.

Artifical Intelligence and Digital Innovations

Artifical Intelligence and digital innovations underpin all activities of CSBII. Our academic team is involved in developing new methodologies for complex systems, big data and informatics of the future.
 
CBSII aims to develop new methodologies in all areas of expertise including:
 
* Artificial Intelligence, soft computing, neural networks, fuzzy cognitive maps
* Geospatial systems
* Data mining and big data analytics, machine learning, data visualisation
* Computational and mathematical modelling, dynamical systems modelling, agent-based modelling
* Systems biology and bioinformatics, network modelling
* Digital and software engineering systems.
 
Please refer to the CSBII team for specific areas of expertise.

The CSBII Team

Lincoln University 

{Samarasinghe Sandhya}  Head of the CSBII Team
Complex systems dynamics, Artificial Intelligence, neural networks, fuzzy cognitive maps, machine learning, computational systems biology, bioinformatics
{Kulasiri Don} Mathematical and computational modelling, stochastic modelling of environmental systems, mathematics of memory formation, computational systems biology of neurodegenerative diseases, stochastic Artifical Intelligence
Prof Shahbaz Khan
Adjunct Professor
Director UNESCO Pacific Region
Jakarta, Indonesia
Water systems modelling, UNESCO AGENDA 2030, global and regional water challenges
{Anthony Patricia} Agent and multi-agent based modelling, genetic algorithms, electronic commerce
{Safa Majeed} Energy systems modelling, agricultural engineering
{Doscher Crile} Engineering, hydrology, computer modelling, GIS, agent-based modelling
{Charters Stuart} Software engineering, visualisation
Glen Rains
Professor of Entomology and Agricultural Engineering
University of Georgia
Application of engineering science to develop sensor technologies and strategies for applications in precision agriculture and insect ecology
{Long Sharon} Programming, GIS
 

Adjunct members (New Zealand and international)

Dr Hong Ling
Livestock Improvement Corporation, Hamilton, New Zealand
Biological systems modelling, computational systems biology, bioinformatics, data mining
Dr Ralf Wieland
Leibniz Centre for Landscape Systems Research, Germany
Systems modelling, software engineering,
Dr Graham Strickert
Institute for Global Water Security, University of Saskatchewan, Canada
Socio-ecological systems, social hydrology, fuzzy cognitive maps
Dr Amphun Chaiboonchoe
Center for Science and Engineering, New York University, Abu Dhabi, UAE
Computational systems biology, bioinformatics
Dr Jacob Stolk, Director
Dione Complex Systems Research Ltd
Complex system modelling, big data analytics
Dr Mario Lopez
DE Laval Inc., USA
Robotic milking systems
 

International partners

Prof Philip Maini, Director
Centre for Mathematical Biology, University of Oxford, UK
Mathematical biology
Prof Helen Byrne
Centre for Mathematical Biology, University of Oxford, UK
Mathematical biology
Prof Hermann Matthies
Braunschweig Technical University, Germany
Scientific computing, mathematics
Prof Irene Hudson
Swinburne Institute of Technology
Melbourne, Australia
Biostatistics, neural networks, data mining
 

CSBII-affiliated research centres

Current Postgradute Projects

PhD

Student Discipline Thesis title Supervisors
Thai Tran Neural Networks, biological systems Self-repair networks   Sandhya Samarasinghe
Don Kulasiri
Mike Levin (Tufts University, USA)
Pooja Pawar
Bioinformatics Computational vaccinology: New approach to universal vaccine design Sandhya Samarasinghe
Don Kulasiri
Mohammad Alsharaiah
Systems modelling Fuzzy systems for cell signalling networks Sandhya Samarasinghe
Don Kulasiri
Moaath Hajayya
Big Data mining, neural networks Advanced robotic mastitis detection with deep learning neural networks Sandhya Samarasinghe
Don Kulasiri
Mario Lopez (DeLaval, Inc. USA)
Ali Abroudi Comp systems biology Integrated systems approach (ODE and petri nets) for cell signalling modelling Sandhya Samarasinghe
Don Kulasiri
Maryam Kharazi Big Data mining, neural networks Evolving fuzzy self-organising maps and swarm intelligence for an advanced early detection system for mastitis in dairy cattle Sandhya Samarasinghe
Don Kulasiri
Ibrahim Al-Tarawni   Systems modelling Mapping reduction - An extension of Gillespie algorithm for modelling stochastic concurrent processes and case studies in systems biology Sandhya Samarasinghe
Don Kulasiri
Mutaz Khazaaleh      Systems modelling Model reduction for large networked systems Sandhya Samarasinghe
Don Kulasiri
Mustafa Pasha Big Data Mining, Computational Systems Biology A holistic assessment of cell signalling networks for understanding effective targets for cancer therapy Sandhya Samarasinghe
Don Kulasiri
Bilal Kayani Neural Networks Animal voice recognition system for assessing their wellbeing Sandhya Samarasinghe
Majeed Safa
Armin Werner
Jacopo Siliprandi Ecological informatics Implementing biosecurity in live plant trade networks Philip Hulme
Sandhya Samarasinghe
Raheel Khan Comp systems biology Modelling mechanisms of long-term memory formation Don Kulasiri
Sandhya Samarasinghe
Rahul Kosarwal Comp systems biology Software framework for solving chemical master equation Don Kulasiri
Sandhya Samarasinghe
Leshi Chen Data mining, comp biology A Boolean approach to fill gaps in short-time series micro array data Don Kulasiri
Sandhya Samarasinghe
Hamish Buller Comp systems biology Modelling memory formation Don Kulasiri
Sandhya Samarasinghe
Fatima Jamal Comp systems biology Investigation into bioenergetics of special protein TRAP found in soil bacteria Bacillus Subtilis Don Kulasiri
Sandhya Samarasinghe
Prerita Gupta informatics Post-hazard emotion identification from tweets - Christchurch earthquakes Pat Anthony
Sandhya Samarasinghe
Anita Thangaraj  Informatics Agent-based modelling of whole farm system operation Pat Anthony
Sandhya Samarasinghe
Kitti Chiewchan Informatics Agent-based model for optimum water allocation in Canterbury  Pat Anthony
Sandhya Samarasinghe
Zhe Wang  Informatics Multi-agents simulation of agile team dynamic process Pat Anthony
Stuart Charters
Shivani Khurana Informatics Agent-based modelling Pat Anthony
Stuart Charters
Ahmad Shalaldeh  Informatics, augmented reality Ewe body composition determination and communication through augmented reality Stuart Charters
Chris Logan
Olusegun Ahiadu (Hayford) GIS, hydrology Analysis of the hydrological processes and estimation of nutrient loads in surface flow for the Waipara river catchment, New Zealand – a contribution to integrated land and water resources management Crile Doscher
Ken Hughey
Abel Mambeleo GIS, agents Integration of agent-based and GIS- based modelling for geospatial simulation of human-elephant conflict in Bunda District, Tanzania. Crile Doscher
Adrian Patterson
Isabelle de Lange Ecological onformatics Gravity models for assessing biosecurity risks from the New Zealand recreational lake user network Phil Hulme
Crile Doscher
As Ari Wahyu Utomo GIS (M. Appl. Science) GIS modelling Crile Doscher
 

 

 

 

 

 



 

 

 

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