ORCID ID – 000-0001-6794-4776
His research interest is developing new learning protocols; learning algorithms and compression techniques, which can efficiently be used in resource constraint analytic platforms such as sensor analytics and also to meet the requirements and applications of the Internet of Things, specifically, large scale farm deployments. Then, use them to derive a distributed data analytic framework, in order to derive an efficient decision support systems for smart dairy farming systems.
Currently, he is working in the VistaMilk project in which his research focus is on developing programmable food based on personal needs. This research covers the concepts in mathematical modelling, molecular communication, and nano-technology, and the application area is dairy milk consumption. The aim of this research is to set up a strategy which enables milk consumers to select the optimal milk composition based on their requirements such as physical fitness and activity level.
Dixon received his Bachelor`s of Science degree in Mathematics and Statistics from University of Ruhuna, Sri Lanka, in 2012 and Master’s of Science degree in Computational Engineering from Lappeenranta University of Technology, Finland, in 2015. The research experiences that he acquired included non-parametric data analysis and dynamic time series analysis. He is currently a Ph.D. student in Science at the Telecommunications Software and Systems Group (TSSG), Waterford Institute of Technology (WIT), Ireland.
- Vimalajeewa, E. Robson, D. Berry, C. Kulatunga, Evaluation of Non-linearity in MIR Spectroscopic data for Compressed Learning, High Dimensional Data Mining Workshop, IEEE Conference in Data Mining , New Orleans, USA, (ICDM 2017), pp. 545-553
- C. Kulatunga, K. Bhargava, D. Vimalajeewa, S. Ivanov, Cooperative In-network Computation in Energy Harvesting Device Clouds, Sustainable Computing: Informatics and Systems, Elsevier, vol. 16, December 2017, pp. 106-116, DOI: 10.1016/j.suscom.2017.10.006.