Dr Khin Lwin

Research Fellow

Anglia Ruskin IT Research Institute

Faculty:Faculty of Science & Technology

Location: Chelmsford

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.

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View Khin's profile on Google Scholar


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.

Research interests

Khin's areas of research interest include:

  • Big Data Analytics
  • Machine Learning and Data Mining
  • Cyber Security –Malwares/Ransomwares Detection, Insider Threat Detection, Malwares in IoTs
  • Innovative IoTs and Smart Cities Applications
  • Intelligent Decision Support System
  • Portfolio Optimization
  • Multi-objective Optimization
  • Evolutionary Algorithms

Areas of research supervision

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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.


  • PhD in Computer Science, University of Nottingham, UK
  • BSc (Hons) in Computer Science, University of Nottingham, UK

Selected recent publications

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Lwin, K. T., Qu, R., & , MacCarthy, B. L. (2017). Mean-VaR Portfolio Optimization – A Non-parametric Approach. European Journal of Operational Research, DOI: 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.

Lwin, K., & Qu, R. (2013). A hybrid algorithm for constrained portfolio selection problems. Applied Intelligence, 39(2), 251-266.

Recent presentations and conferences

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Hasan, M., Abu-Hassan, K., Lwin, K., & Hossain, M. A. (2016) Reversible Decision Support System: Minimising Cognitive Dissonance in Multi-Criteria Based Complex System, Computer Science and Electronic Engineering (CEEC) Conference.

Hoque, M. T., 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

Shabut, A., Lwin, K., & Hossain, M. A. (2016) Cyber Attacks, Countermeasures, and Protection Schemes– A Comprehensive Survey. In 2016 10th International Conference on Software, Knowledge, Information Management and Applications (SKIMA). IEEE.

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.