Faculty:Faculty of Science & Technology
Dr Khin Lwin's research interests focus on the interdisciplinary studies between computer science, operational research and artificial intelligence for the applications of modelling, search and optimization techniques to tackle constrained combinatorial problems to underpin the development of intelligent decision support systems across a wide range of real-world applications.
View Khin's profile on Google Scholar.
She has also been awarded the Springer Science and Business Media Prize, the University Prize for Academic Excellence and the International Research Excellence Scholarship from Springer and the University of Nottingham in 2010. She had also worked as a software engineer at Halliburton in Tewkesbury, UK.
Lwin, K., Qu, R., & Kendall, G. (2014). A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization. Applied Soft Computing, 24, 757-772.
Lwin, K., & Qu, R. (2013). A hybrid algorithm for constrained portfolio selection problems. Applied Intelligence, 39(2), 251-266.
Lwin, K., Qu, R. and Zheng, J. (2013). Multi-objective Scatter Search with External Archive or Portfolio Optimization, 5th International Conference on Evolutionary Computation Theory and Applications (ECTA 2013), pp. 111-119.
Khwanpheng, S., Lwin, K. T., Chaisricharoen, R. and Temdee, P. (2015). Collaborative crosschecking system of observed loss estimation for disaster relief management. In 2015 9th International Conference on Software, Knowledge, Information Management and Applications (SKIMA2015), pp. 1-5, IEEE, 2015, 15-17 December, Kathmandu, Nepal.
Lwin, K., Qu, R. and Zheng, J. (2013). Multi-objective scatter search with external archive for portfolio optimization. 5th International Conference on Evolutionary Computation Theory and Applications (ECTA2013), pp. 111-119, 2013, Vilamoura, Algrave, Portugal.