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.
Khin’s current research interests include computational intelligence, decision support systems, cyber security, portfolio optimization, risk management, big data analytics, machine learning, multi-objective optimization, evolutionary algorithms, heuristics and meta-heuristics. She received 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.
Khin's areas of research interest include:
Khin is currently supervising the following PhD researchers
We welcome applications for postgraduate research under the supervision of Khin Lwin. We also have a number of exciting research project opportunities that you may want to consider. These are self-funded research proposals that have already been identified by our staff.
Kaiser, M., Lwin, K. T., Hajializadeh, D., Chaipimonplin, T., Sarhan, A., & Hossain, M. A. (2018). Advances in Crowd Analysis for Urban Event Detection and Real-Time Transportation Management. Accepted at IEEE Intelligent Transportation Systems Transactions. DOI: https://doi.org/10.1109/TITS.2017.2771746
Lwin, K. T., Qu, R., & , MacCarthy, B. L. (2017). Mean-VaR Portfolio Optimization – A Non-parametric Approach. European Journal of Operational Research, DOI: https://doi.org/10.1016/j.ejor.2017.01.005
Lwin, K., Qu, R., & Kendall, G. (2014). A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization. Applied Soft Computing, 24, 757-772. DOI: https://doi.org/10.1016/j.asoc.2014.08.026
Lwin, K., & Qu, R. (2013). A hybrid algorithm for constrained portfolio selection problems. Applied Intelligence, 39(2), 251-266. DOI: https://doi.org/10.1007/s10489-012-0411-7
Cortesi, N., Gotti, K., Psaila, G., Burini, F., Lwin, K. T., Hossain, M. A. (2017). A Network-based Ranking Approach to Discover Places Visited by Tourists from Geo-located Tweets. Accepted In 11th International Conference on Software, Knowledge, Information Management & Applications.
Tania, M. H., Lwin, K. T., AbuHassan, K., Bakhori, N. M., Azmi, U. Z. M., Yusof, N. A., & Hossain, M. A. (2017). An Automated Colourimetric Test by Computational Chromaticity Analysis: A case study of Tuberculosis Test. In 11th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB2017), Vol. 616, p. 313. Springer. DOI: https://doi.org/10.1007/978-3-319-60816-7_38.
Hasan, M. M., Abu-Hassan, K., Lwin, K., & Hossain, M. A. (2016). Reversible Decision Support System: Minimising Cognitive Dissonance in Multi-Criteria Based Complex System using Fuzzy Analytic Hierarchy Process, In 8th Computer Science and Electronic Engineering Conference (CEEC2016), pp. 210-215. IEEE. DOI: 10.1109/CEEC.2016.7835915.
Tania, M. H, Lwin, K. T., & Hossain, M. A. (2016) Computational Complexity of Image Processing Algorithms for an Intelligent Mobile Enabled Tongue Diagnosis Scheme, In 2016 10th International Conference on Software, Knowledge, Information Management and Applications (SKIMA). IEEE. DOI: 10.1109/SKIMA.2016.7916193
Lwin, K. T., Sabor, M., & Hossain, M. A. (2016). New Social Engineering Challenges in Phishing – A Case Study of Ransomware Attack. In Journal of Information System Security, 2016 European Security Conference: The Future of Cybersecurity, 2016, 15-17 June, Lisbon, Portugal.
Khwanpheng, S., Lwin, K. T., Chaisricharoen, R., & 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, DOI: 10.1109/SKIMA.2015.7400049.
Lwin, K., Qu, R., & Zheng, J. (2013). Multi-objective Scatter Search with External Archive for Portfolio Optimization. In 5th International Conference on Evolutionary Computation Theory and Applications (ECTA2013), pp. 111-119, 2013.