Staff Profile

Professor

Sandhya Samarasinghe

MSc (Mech Eng (Hons)) (Moscow), MS, PhD (Eng)(Virginia Tech, USA)

Sandhya Samarasinghe

Contact Details

Faculty of Environment, Society and Design

Location NRE157
Phone +64 3 423 0439
Extension 30439
Email Sandhya.Samarasinghe@lincoln.ac.nz
 

Currently Teaching

  • COMP 627 Neural Networks Applications
  • ENGN 233 Water Science and Technology I
  • ERST 615 Systems Perspective for Sustainable Design
 

Academic and Professional Background

  • Head, Integrated Systems Modelling Group
  • Founding member of the Centre for Advanced Computational Solutions
  • Member, Centre for Mathematical Biology, Oxford University, UK
  • Distinguished Member Global Institute for Water Security, University of Saskatchewan, Canada
  • Visiting Fellow, Oxford University, UK (2008, 2013)
  • Visiting Fellow, Princeton University, USA (2004)
  • Visiting Fellow, Stanford University, USA (1998)
  • Associate Member, IEEE (Institute of Electrical and Electronics Engineers), USA
  • Member IEEE Society for Computational Intelligence
  • Feature in Who’s Who in the World and in Who’s Who of Women in the World
 

Current Research and Publications / Selected Publications

  • Development of Integrated Systems Modelling methods and concepts for the study of self organisation, complexity, emergent properties and dynamical behaviour of complex systems for their holistic understanding, management and development based primarily on Neural networks, Fuzzy and soft systems/Fuzzy Cognitive Maps, network modelling and Mathematics.
  • Application of Integrated Systems Modelling in:
    (i) Computational Systems Biology for system level understanding of the dynamics of cell signalling networks for understanding and promoting health (homeostasis) and preventing diseases (disorder); and 
    (ii) Water/environmental and Socio-ecological systems modelling for holistic understanding and integrated problem solving through dynamical systems approaches.  
  • Other Advanced  applications in Computational early detection of mastitis and Computer Based Decision Support Systems for complex systems


Book
Samarasinghe, S. 2007 Neural Networks for Applied Sciences and Engineering - From fundamentals to Complex Pattern Recognition, 570pp.  Taylor and Francis, Inc.,New York and Florida, USA.  (http://www.crcpress.com and http://www.amazon.com)

Book Chapters
Wannige, T., Kulasiri, D. and Samarasinghe, S. 2013 Modelling Stochasticity in Multi-stable and Oscillatory Biological Networks far from Equilibrium. In “Self-organization: Theories and Methods”, Editor: WJ Zhang, NOVA SCIENCE PUBLISHERS, INC,. NEW YORK, USA.

Refereed journal articles
Ling, H. Samarasinghe, S and Kulasiri, D. 2013 A Novel recurrent neural network for Modelling Cell Signalling Networks: Oscillatory p53 Interaction Dynamics. BioSystems 114 (2013) 191– 205 .

Ling, H., Samarasinghe, S. and Kulasiri, D. 2013.  Computational experiments reveal the efficacy of targeting CDK2 and CKIs for significantly lowering cellular senescence bar for potential cancer treatment.  BioSystems 111: 71– 82 [In the ‘Top 25 Hottest Articles in January to March quarter 2013]

Samarasinghe, S. and Strickert, G. Jan 2013. Mixed-method integration and advances in fuzzy cognitive maps for computational policy simulations for natural hazard mitigation. Environmental Modelling and Software (EMS) (in Thematic Issue on Integrated Modelling), Volume 39, pp 188-200. (Invited)

Wannige, T. Kulasiri, D and Samarasinghe, S.  2013. Mathematical Modelling of Meiosis initiation reveals a Bistable Switch between Meiosis and Mitosis Inducers in Budding Yeast.  Journal of Theoretical Biology 341(2014)88–101

Waidyaratne, P. and Samarasinghe, S. 2013 Artificial Neural Networks to Identify Naturally Existing Disease Severity Status.  Neural Computing and Applications

Chong, K.H., Samarasinghe, S and Kulasiri, S. 2013. Modelling core regulatory feedback mechanisms of p53 protein that decide cell fate. Journal of Mathematical Biosciences (in review) 

Samarasinghe, S. and Chaiboonchoe, A. 2013.  Assessment of the efficacy of microarray based intrinsic gene signatures in breast cancer classification and the character and relations of identified subtypes BioMedical Informatics (in review)

Chaiboonchoe, A. and Samarasinghe, S. 2013. Identification of genes and gene network of glucocorticoids-induced apoptosis in childhood leukaemia from microarray and pathway databases.  Special Issue on Big data and Networks of Bioinformatics (Bio Med Research International) (in review)

Kulasiri, D. Ling, H. and Samarasinghe, S. 2012. A Generalised Stochastic Solute Transport Model for Multi-scale Dispersion in Porous Media. Journal of Porous 15(2):153–170(2012)

Safa M. and Samarasinghe, S. 2012. CO2 Emissions from Farm Inputs -Case study of wheat production in Canterbury, New Zealand. Environmental Pollution (Elsevier) 171: 126-132

Safa M. and Samarasinghe S. 2012 Modelling fuel consumption in wheat production using artificial neural networks. Energy (Elsevier) 49 (2013) 337-343

Kulasiri, D., He Y. and Samarasinghe S. 2011 Robustness of circadian rhythms in the presence of molecular fluctuations: An investigation based on a mechanistic, statistical theory and a simulation algorithm. BioSystems. 1-10 2011[In the ‘Top 25 Hottest Articles’ in July-September Quarter in 2011]

Sarmah, C. and Samarasinghe, S. 2011. Microarray gene expression: A study of between-platform association of affymetrix and cDNA arrays. Computers in Biology and Medicine (Elsevier) 41: 980-986.

Safa, M. and Samarasinghe, S. 2011. Determination and modelling of energy consumption in wheat production using neural networks. Energy (Elsevier) 36: 5140-5147

Safa, M., Samarasinghe, S. and Mohssen. M. 2011. A Field study of energy consumption in wheat production in Canterbury, New Zealand. Journal of Energy Conversion and Management. 52: 2562-2532.

Ling, H., Samarasinghe, S. and Kulasiri, D. 2011. CDK2 and CKIs targeting can significantly lower the cellular senescence bar- reveals a mathematical model of G1/S checkpoint pathway. Nature Precedings- Pre-publication of Preliminary Findings

Sohn, S. and Samarasinghe, S. 2011. Relationship between socio-demographic attributes and personal level risk perception for climate change in Korea: An investigation based on ordered logit model. Asian Pacific Planning Review (2011 Special Issue), Vol . 7 pp 31-38.

Ling, H., Kulasiri, D. and Samarasinghe S. 2010. Robustness of G1/S checkpoint pathway in cell cycle regulation based on the probability of DNA-damaged cells passing as healthy cells.  BioSystems. Vol. 101:213  [In the ’Top 25 Hottest Articles’ for two quarters in 2010] 

Cominetti, O., Matzavinos, A. Samarasinghe, S., Kulasiri, D. Maini, P. and Radek Erban. 2010. DifFUZZY: A fuzzy spectral clustering algorithm for complex data sets. International Journal of Computational Intelligence in Bioinformatics and Systems Biology 1: (4):402-417

Chaiboonchoe, A., Samarasinghe, S. and Kulasiri, D. 2010. Machine learning for childhood acute lymphoblastic leukaemia gene expression data analysis: A review. Current Bioinformatics. 5:118-133.

Xie, Z., Kulasiri, D., Samarasinghe, S. and Qian, J. 2010, An Unbiased Sensitivity Analysis Reveals Important Parameters Controlling Periodicity of Circadian Clock, Biotechnology and Bioengineering, 105:(2):250-259

G. Strickert, G. Samarasinghe, S. Doscher, C. and Davies, T. 2010. Mixing with the mountains: A triangulated super-physical true-social approach for policy advancement to improve resilience to low probability high consequences catastrophic natural events for mountainous communities. Special Issue of Journal of Natural Resource Policy Research, 2:(4):389-407

Safa, M., Samarasinghe, S. and Mohssen. M. 2010. A Field study of energy consumption in wheat production in Canterbury, New Zealand. Energy Conversion and Management 52:2526-2532

Sarmah, C., Samarasinghe, S. and Kulasiri, D. and Catchpoole, D. 2010. A simple Affymetrix Ratio-Transformation Method yields comparable expression levels quantifications with cDNA data. International Journal of Medicine and Medical Sciences, Volume 1(3):157 – 162. 2010.

Chaiboonchoe, A., Samarasinghe, S. and Kulasiri, D. 2010. Machine learning for childhood acute lymphoblastic leukaemia gene expression data analysis: A review. Current
Bioinformatics (5): 118-133

Sun, Z. and Samarasinghe, S. 2010. Detection of mastitis by robotic milking systems using neural networks. Journal of Dairy Research (77): 168-175

Xie, Z., Kulasiri, D., Samarasinghe, S. and Qian, J. 2010, An Unbiased Sensitivity Analysis Reveals Important Parameters Controlling Periodicity of Circadian Clock, Biotechnology and Bioengineering. Vol 105(2): 250-259.

G. Strickert, G. Samarasinghe, S. Doscher, C. and Davies, T. 2010. Mixing with the mountains: A triangulated super-physical true-social approach for policy advancement to improve resilience to low probability high consequences catastrophic natural events for mountainous communities. Journal of Natural Resource Policy Research. Vol.2(4):389-407.

Sarmah, C. and Samarasinghe, S. 2010. Microarray Data Integration: Frameworks and a List of Underlying Issues. Current Bioinformatics Vol. 5 (4): 280-289.

Safa, M., Samarasinghe, S. and Mohssen, M. 2010. Determination of fuel consumption and indirect factors affecting it in wheat production in Canterbury, New Zealand. Energy (Elsevier): 35(2010):5400-5405

Safa, M., Samarasinghe, S. and Mohssen. M. 2010. A Field study of energy consumption in wheat production in Canterbury, New Zealand. Journal of Energy Conversion and Management, 52:2526-2532

Sun, Z. and Samarasinghe, S. 2009. Detection of mastitis by robotic milking systems using neural networks. Journal of Dairy Research UK, 77:168-175

Samarasinghe, S. 2009. Exploration of fracture dynamics properties and predicting fracture toughness of individual wood samples using neural networks. Silva Fennica 43 (2):275-289.

Ling, H., Samarasinghe, S. and Kulasiri, D. 2009 Modelling variability in full-field displacement profiles and Poisson ratios of wood in compression using stochastic neural networks. Silva Fennica. 43(5):871-887.

Hassan, K.J., Samarasinghe, S. and Lopez-Benavides, M.G. 2009. Use of neural networks to detect minor and major pathogens that cause bovine mastitis. Journal of Dairy Science 92: 1493-1499

Rains, G., Kulasiri, D., Zhou, Z., Samarasinghe, S. Tomberlin, J.K. and Olson, D.M. 2009. Synthesizing Neurophysiology, Genetics, Behaviour and Learning to Produce Whole-Insect Programmable Sensors to Detect Volatile Chemicals. Biotechnology and Genetic Engineering Reviews. Vol. 26. 191-216.

Kulasiri, D., Nguyen, L., Samarasinghe, S. and Xie, Z. 2008. A review of systems biology perspective on genetic regulatory networks with examples. Current Bioinformatics. Vol. 29. pp. 197-225

Samarasinghe, S., Kulasiri, D. and Jamieson, T. 2007. Neural networks for predicting fracture toughness of individual wood samples. Silva Fennica 41(1):105-122.

Xie, Z.; Kulasiri, D., Samarasinghe, S. and Rajanayake, C. 2007. The estimation of parameters for stochastic differential equations using neural networks. Journal of Inverse problems in Science and Engineering, (Taylor & Francis): 10:10-20

Chandraratne, M. R., Kulasiri, D. And Samarasinghe, S. 2007 Classification of lamb carcass using machine vision: comparison of statistical and neural network analyses, Journal of Food Engineering, 82: 26-34.

Ordonez, E., Samarasinghe, S. and Torgerson, L. August 2006. Artificial Neural Networks for Assessing Waste Generation Factors and Forecasting Waste Generation: A Case Study of Chile. Journal of Solid Waste Technology and Management, 32(3): 167-184.

Chandraratne, M. R., Samarasinghe, S., Kulasiri. D., Bickerstaffe, R., 2006, Prediction of lamb tenderness using image surface texture features. International Journal of Food Engineering 77(3) 492-499.

Chandraratne, M. R., Kulasiri. D., Frampton, C., Samarasinghe, S., Bickerstaffe, R., 2006, Prediction Of Lamb Carcass Grades Using Features Extracted From Lamb Chop Images, International Journal of Food Engineering 74(1): 116-124

Conference Papers (full paper refereed) (2007-2013)
Chong, K. H. Samarasinghe, S. and Kulasiri, D. 2013 Mathematical modelling of p53 basal dynamics and DNA damage response. International Congress on Modelling and Simulation (MODSIM’13)

Al-Yousef, A. and Samarasinghe, S. 2013 Gene expression based Computer Aided diagnosis system for Breast Cancer: A novel biological filter for biomarker detection. International Congress on Modelling and Simulation (MODSIM’13)

Waidyaratne, P. and Samarasinghe, S. 2013. Modelling rapid stomatal closure with Synchronous Boolean Network Approach. International Congress on Modelling and Simulation (MODSIM’13)

Obiedat, M. and Samarasinghe S., 2013 Fuzzy Representation and Aggregation of Fuzzy Cognitive Maps. International Congress on Modelling and Simulation (MODSIM’13)

Safa M. and Samarasinghe S. 2012. Modelling energy use and fuel consumption in wheat production using indirect factors and Artificial Neural Networks. International Conference on Neural Information Processing (ICONIP 2012). Doha City, Qatar

Ling, H., Samarasinghe, S. and Kulasiri, D. 2011. Robustness of CDK2 in Triggering Cellular Senescence based on Probability of DNA-damaged Cells Passing G1/S Checkpoint. IEEE International Conference on Systems Biology, Zhuhai, China.

Obiedat, M., Samarasinghe, S. and Strickert, G. 2011. A new method for identifying the central nodes in Fuzzy cognitive maps using consensus centrality measures. International Modelling and Simulation Congress (MODSIM’11). Perth, Australia.

Al-yousef, A. and Samarasinghe, S. 2011. Ultrasound based computer aided diagnosis of breast cancer: Evaluation of a new feature of mass central regularity degree. International Modelling and Simulation Congress (MODSIM’11). Perth, Australia.

Samarasinghe, S. 2010. Neural Networks for water systems analysis: from fundamentals to complex pattern recognition. IAHS (International Association of Hydrological Sciences) Redbook Series containing the seminal addresses of the 10th UNESCO-IAHS Kovacs Colloquium 2010 entitled “Hydrocomplexity: New Tools for Solving Wicked Water Problems”, UNESCO Headquarters Paris, France. 2-3 July 2010. pp. 209-213 (as part of a Key note address)

Sarmah, C., Samarasinghe, S. and Kulasiri, D. and Catchpoole, D. 2010. Integration of Affymetrix and cDNA data based on a ratio-measure. Proceedings of the International Conference on Bioinformatics and Bioengineering, Cape Town, South Africa, January 29-31, 2010. CD ROM.

Safa, M. and Samarasinghe, S. 2010 Modelling of Energy Consumption in Wheat Production using Neural Networks. ICESE 2010-Int. Conf. on Environmental Science and Engineering, Singapore, 25-27 August 2010, pp. 1233-1238.

Chaiboonchoe, A., Samarasinghe, S. and Kulasiri, D. 2010. Identification of GCs-Regulated genes and inferring the GR Gene Network in Leukemia based on Microarray data and Pathway Databases. Proceedings of the Eighth Asia Pacific Bioinformatics Conference, Bangalore, India, 18-21 January 2010.

Thaher, M., Samarasinghe, S. and Kulasiri, D. 2010. Neural Network Modelling of DNA damage detection in cells. New Zealand Computer Science Research Students Conference (NZCSRS) 2010. Victoria University, Wellington, New Zealand. April 2010. (CDROM)

Samarasinghe, S. and Kulasiri, D. 2009. Validating a gene expression signature of invasive ductal carcinoma in the breast and detecting key genes using neural networks. Joint 18th International Mathematics and Computer Science (IMACS) Conference and International Modelling and Simulation Congress MODSOM’09. Cairn, Australia

Chaiboonchoe, A., Samarasinghe, S. and Kulasiri, D. 2009. Identification of GCs-Regulated genes and inferring the GR Gene Network in Leukemia based on Microarray data and Pathway Databases. Proceedings of the Eighth Asia Pacific Bioinformatics Conference, Bangalore, India.

Chaiboonchoe, A. Samarasinghe S. and Kulasiri, D. 2009. Efficacy of emergent clustering methods in the investigation of the response to treatment of childhood leukaemia from short time series gene expression data Joint 18th International Mathematics and Computer Science (IMACS) Conference and International Modelling and Simulation Congress MODSOM’09. Cairn, Australia

Safa, M., Samarasinghe, S. and Mohssen, M. 2009. Modelling fuel consumption in wheat production using neural networks. Joint 18th International Mathematics and Computer Science (IMACS) Conference and International Modelling and Simulation Congress MODSOM’09. Cairn, Australia

Safa, M and Samarasinghe, S. 2009. Energy use pattern in wheat production in Canterbury. Proceedings of the 6th Annual Energy Post Graduate Conference, Massey University, New Zealand.

Strickert, G., Samarasinghe, S. and Davies, T. 2009 Neural Networks Naturally. 2009. Joint 18th International Mathematics and Computer Science (IMACS) Conference and International Modelling and Simulation Congress MODSOM’09. Cairn, Australia.

Arayl, J. Kulasiri, D., Carnaby, G.A. and Samarasinghe, S. 2009. Investigating the price of the New Zealand wool clip using modelling approaches. Joint 18th International Mathematics and Computer Science (IMACS) Conference and International Modelling and Simulation Congress MODSOM’09. Cairn, Australia.

Wijethunga, P, Samarasinghe, S., Kulasiri, D. and Woodhead, I. 2009. Towards a generalized colour image segmentation for kiwifruit detection. Proceedings of the Image and Vision Computing New Zealand 2009.

Wijethunga, P., Samarasinghe, S., Kulasiri, D. and Woodhead, I. Nov. 2008. Digital image analysis based automated kiwifruit counting technique. International Image and Vision Computing Conference (IVCNZ) 2008. New Zealand. Proceedings in IEEE Explore.

ChePa, N. Samarasinghe, S. Nov. 2008.predicting the spread of cancer using neural networks approach. International EPSM 2008 Innovation in Patient Care Conference Christchurch p. 79-80.

Strickert, G. and Samarasinghe, S. Dec. 2008. BUILDING RESILIENCE TO CNE: A case study of low probability high consequences catastrophic natural events; Learning from New Zealand’s ski field stakeholders. Annual Conference of the Australian Sociological Association (TASA), Melbourne, Australia.

Samarasinghe, S. 2007 Optimum structure of feed forward neural networks by SOM clustering of Neuron activation, International Congress on Modelling and Simulation. (MODSIM’07), Modelling and Simulation Society of Australia and New Zealand, In Oxley, L. and Kulasiri, D. (Eds). Christchurch, NZ, December 2007, ISBN: 978-0-9758400-4-7.

Hassan, K., Samarasinghe, S. and Lopez-Benavidis, M. 2007. The use of neural networks to detect minor and major pathogens that cause bovine mastitis. Proceedings of the Conference of New Zealand Society for Animal Productions (NZSAP), Wanaka, New Zealand, July, 2007.

Ling, H., Samarasinghe, S. and Kulasiri, G.D., 2007 Modelling displacement fields of wood in compression loading using stochastic neural networks, International Congress on Modelling and Simulation. (MODSIM’07), Modelling and Simulation Society of Australia and New Zealand, December 2007. In Oxley, L. and Kulasiri, D. (Eds). ISBN: 978-0-9758400-4-7.

 

Supervision

Masters and PhD research involving development and application of Integrated Systems Modelling involving Neural Networks, Fuzzy Systems/Fuzzy Cognitive Maps, Network Modelling, Soft Computing and Mathematics. Application areas are:

  • Systems Biology
    Computational Systems Biology and BioInformatics- Modelling Cell Signalling Pathways (in cell cycle, cancer, plants) for system level understanding; Microarray Data Analysis, Gene Regulatory Networks, Disease Diagnosis

Water/Environmental and Socio-ecological systems modelling
Modelling water/Environmental and Socio-ecological systems; and Computational Policy Scenario Simulations for Sustainable Systems Management

Sandhya has supervised the following PhD and Masters students (2011-2013):

  • Ali Abroudi (PhD) Systems Modelling of the dynamics of cell signalling networks
  • Ibrahim Altarawani (PhD).  Biological Networks and Social Networks- The common Ground; and application to cell signalling
  • Ket Hing Chong, PhD. Modelling Core Regulatory feedback mechanisms of p53 protein that decides cell fate.
  • Pramuditha Waidyaratne, (PhD) Dynamic Evolution of Rapid Abscisic Acid Signal Transduction in Plant Guard Cells.
  • Ansar Ali, PhD. Computational Models of Protein-Protein Interaction motifs.
  • Obiedat, M. (PhD) Development of a fuzzy cognitive map framework for decision-making in Complex Systems.
  • Mutaz Kazaleh (PhD) Advances in Fuzzy Cognitive Maps
  • Maryam Kharazi (PhD) Evolving Self Organising Map neural networks and Particle Swarm Optimisation for early detection of mastitis 
  • Al-Yousef, A. (PhD) Computational framework for early detection of breast cancer (completed 2013).
  • Almazroey, A. (MApplSc) Gene expression data analysis for identifying novel breast cancer genes (2013).
  • Freeman, S. (PhD) Integrating conservation and production on private land: a sociological model using fuzzy cognitive maps and individual based modelling for western weka conservation at Cape Foulwind (2013)
  • Kohli, M. (Masters IT) Detection of mastitis by automatic milking systems using fuzzy neural networks (2012)
  • Ling, H. (PhD) Mathematical modelling of cell cycle regulation (2012)
  • Matroushi, S. (MApplSc) Building a hybrid neural network model for gold price forecasting (2012)
  • Strickert, G. (PhD) Participatory adaptive risk management of compounding natural hazards: an integrative trans-disciplinary framework involving Fuzzy Cognitive Mapping applying a mixed-method multi-site case study for improving resilience to natural hazards for alpine recreation environments; utilizing experience and perceptions of experts and lay experts to improve policy, practice and design of preparation, response and recovery strategies to mountain hazards. (2011)
  • Safa, M. (PhD) Determining and modelling energy consumption in wheat production using neural networks (2011)
  • Chaiboonchoe, A. (PhD) Reverse engineering of gene regulatory networks in childhood leukemia based on micro-array data and neural networks (2011).
  • Sarmah, C. (PhD) A system to denoise, integrate and classify multi-platform expression data (2011).

The complete list of supervisions for Faculty of Environment, Society and Design.
 

Page last updated on: 06/03/2012