Dr. KEUNG Wai Jacky (姜煒)

Dr. Keung received the B.Sc (Hons) in Computer Science from the University of Sydney, and the Ph.D in Software Engineering from the University of New South Wales, Australia, under Professor Barbara Kitchenham and Prof. Ross Jeffery. He was then a Research Scientist in the Software Systems Research Group at NICTA (now DATA61, CSIRO) based in Sydney Australia prior to returning Hong Kong.

He is an active software engineering researcher and software systems consultant, his main research area are software engineering, data sceince, AI, FinTech, machine learning related, such as BlockChain Systems for FinTech applications, Deep Learning applications in Software cost estimation, defect prediction, empirical modeling and evaluation of complex systems, and intensive data mining and AI for software engineering data. He has worked with a number of software companies and government departments across Asia Pacific and attracted funding supports for research projects from both the government and the industry which had been successfully carried out. His research work have been published in prestigious journals including IEEE Transactions on Software Engineering, Empirical Software Engineering Journal, Information and Software Technology, the Journal of Systems and Software, Automated Software Engineering and many other leading journals and conferences. 

• Software Engineering
• Metrics and Mesasurements
• Empirical Experiments
• Software Effort Estimation
• Data Mining and Analytics
• Machine Learning
• Artificial Intelligence 
• Information Retrieval
• Cloud Computing
• Resource Provisioning
• Data Science and Data Analytics
• Concept Drift
• GPU Compute
• Deep Learning
• Financial Technology
• Blockchain

Selected Journal Publications (For full list here)

1. Y. Tang, H. Wang, X. Zhan, X. Luo, Y. Zhou, H. Zhou, Q. Yan, Y. Sui, J. W. Keung, 2021 "A Systematical Study on Application Performance Management Libraries for Apps," in IEEE Transactions on Software Engineering, pp, doi: 10.1109/TSE.2021.3077654.
2. S. JIANG, M. Zhang, Y. Zhang, R. Wang, Q. Yu and J. W. Keung, 2021 "An Integration Test Order Strategy to Consider Control Coupling," in IEEE Transactions on Software Engineering. vol 47, no. 7, pp1350-1367. doi: 10.1109/TSE.2019.2921965
3. Bennin, KE, Keung, J, Phannachitta, P, Monden, A & Mensah, S 2018, 'MAHAKIL: Diversity based Oversampling Approach to Alleviate the Class Imbalance Issue in Software Defect Prediction' IEEE Transactions on Software Engineering, vol 44, no. 6, pp. 534-550. DOI: 10.1109/TSE.2017.2731766
4. Menzies, T, Brady, A, Keung, J, Hihn, J, Williams, S, El-Rawas, O, Green, P & Boehm, B 2013, 'Learning project management decisions: A case study with case-based reasoning versus data farming' IEEE Transactions on Software Engineering, vol 39, no. 12, 6600685, pp. 1698-1713. DOI: 10.1109/TSE.2013.43
5. Kocaguneli, E, Menzies, T, Keung, J, Cok, D & Madachy, R 2013, 'Active Learning and effort estimation: Finding the essential content of software effort estimation data' IEEE Transactions on Software Engineering, vol 39, no. 8, 6392173, pp. 1040-1053. DOI: 10.1109/TSE.2012.88
6. Kocaguneli, E, Menzies, T, Bener, AB & Keung, JW 2012, 'Exploiting the essential assumptions of analogy-based effort estimation' IEEE Transactions on Software Engineering, vol 38, no. 2, 5728833, pp. 425-438. DOI: 10.1109/TSE.2011.27
7. Kocaguneli, E, Menzies, T & Keung, JW 2012, 'On the value of ensemble effort estimation' IEEE Transactions on Software Engineering, vol 38, no. 6, 6081882, pp. 1403-1416. DOI: 10.1109/TSE.2011.111
8. Keung, JW, Kitchenham, BA & Jeffery, DR 2008, 'Analogy-X: Providing statistical inference to analogy-based software cost estimation' IEEE Transactions on Software Engineering, vol 34, no. 4, pp. 471-484. DOI: 10.1109/TSE.2008.34
9. Mensah, S, Keung, J, MacDonell, SG, Bosu, MF & BENNIN, KE 2018, 'Investigating the Significance of the Bellwether Effect to improve Software Effort Prediction: Further Empirical Study' IEEE Transactions on Reliability. DOI: 10.1109/TR.2018.2839718
10. X. Yu, J.W. Keung, Q. Li, K. Bennin, Z. Xu, J. Wang, X. Cui., 2020 "Improving Ranking-Oriented Defect Prediction Using a Cost-Sensitive Ranking SVM," in IEEE Transactions on Reliability, vol. 69, no. 1, pp. 139-153, March 2020, doi: 10.1109/TR.2019.2931559.

1. BENNIN, KE, Keung, JW & Monden, A 2018, 'On the relative value of data resampling approaches for software defect prediction' Empirical Software Engineering. DOI: 10.1007/s10664-018-9633-6
2. Kitchenham, B, Madeyski, L, Budgen, D, KEUNG, WJ, Brereton, P, Charters, S, Gibbs, S & Pohthong, A 2017, 'Robust Statistical Methods for Empirical Software Engineering' Empirical Software Engineering, vol 22, no. 2, pp. 576-630. DOI: 10.1007/s10664-016-9437-5
3. Phannachitta, P, KEUNG, WJ, Monden, A & Matsumoto, K 2017, 'A stability assessment of solution adaptation techniques for analogy-based software effort estimation.' Empirical Software Engineering, vol 22, no. 1, pp. 474-504. DOI: 10.1007/s10664-016-9434-8
4. Kocaguneli, E, Menzies, T & Keung, JW 2013, 'Kernel methods for software effort estimation: Effects of different kernel functions and bandwidths on estimation accuracy' Empirical Software Engineering, vol 18, no. 1, pp. 1-24. DOI: 10.1007/s10664-011-9189-1
5. Kitchenham, B, Al-Khilidar, H, Babar, MA, Berry, M, Cox, K, Keung, J, Kurniawati, F, Staples, M, Zhang, H & Zhu, L 2008, 'Evaluating guidelines for reporting empirical software engineering studies' Empirical Software Engineering, vol 13, no. 1, pp. 97-121. DOI: 10.1007/s10664-007-9053-5

• Journal of Systems and Software (JSS)
• Information and Software Technology Journal (IST)
• Applied Soft Computing (ASC)
• Transactions on Software Engineering and Methodology (TOSEM)
• Empirical Software Engineering Journal (EMSE)
• IEEE Transactions on Software Engineering (TSE)

• Premium Award for Best Journal Paper (IET Software) 2018
• IEEE QRS 2017 Best Paper Award International Conference on Software Quality, Reliability & Security (QRS-2017)
• IEEE QRS 2016 Best Paper Award International Conference on Software Quality, Reliability & Security (QRS-2016)
• National Natural Science Award - Ministry of Education of the People Republic of China 2015 (高等學校科學研究優秀成果獎-自然科學獎)
• IEEE Hong Kong Competition on Cloud Computing 2011 – Silver Award Most innovative cloud computing mobile application, Hong Kong
• IEEE ASWEC 2010 Best Paper Award Australian Software Engineering Conference, Auckland, New Zealand
• IEEE ICIW 2010 Best Paper Award International Conference on Internet and Web Applications and Services, Barcelona, Spain
• IEEE ASWEC 2008 Best Paper Award Australian Software Engineering Conference, Perth
• IEEE APSEC 2007 Best Paper Award Asia Pacific Software Engineering Conference, Japan
• IEEE ISESE 2006 Best Paper Award International Symposium on Empirical Software Engineering, Brazil
• 2020 CityU President's Teaching Excellence Awards (TEA).