Prof. KEUNG Wai Jacky (姜煒)

B.Sc (Hons) Sydney, Ph.D. New South Wales (UNSW)

HKCS, ACS, ACM, IEEE - Senior Member

IEEE HK Computer Society - Chairman

Artificial Intelligence and Software Engineering Research Group (AiSE) - Leader

Stanford's top 2% most highly cited scientists (2023 Oct, Version 6)

Stanford's top 2% most highly cited scientists (2022 Nov, Version 5)

Other Links

Visiting address
YEUNG-Y7721
Phone: +852 34422591

Author IDs

Willing to take PhD students: yes

Biography

Jacky Keung received B.Sc.(Hons) in Computer Science from the University of Sydney and Ph.D. in Software Engineering from the University of New South Wales, Australia. Before joining CityU, he was then the Research Scientist in the Software Systems Research Group at NICTA (now DATA61, CSIRO) based in Sydney, Australia.

Prof. Keung's research interests encompass a wide range of domains, reflecting his expertise in various areas. These include software and systems engineering, data science, AI, FinTech, machine learning, blockchain systems for FinTech applications, deep learning, LLM applications, defect prediction, and empirical modeling and evaluation of complex systems. His diverse expertise has led to fruitful collaborations with numerous software companies and government departments across the Asia Pacific region. He has produced over 150 journal and conference research papers in top venues.

Moreover, Prof. Keung boasts an impressive history of forging strong partnerships with various companies spanning diverse industries, exemplifying his prowess in industry connections. These partnerships have yielded substantial external funding for research and development projects, amounting to approximately HK$20M+. His industry connection not only fosters significant engagement between academia and industry but also creates enhanced student internship and placement opportunities and promising job prospects for undergraduate students. As a result, the starting salaries for CS students have witnessed a remarkable year-on-year increase of over 15% for the past three years, reflecting the tangible impact of Dr. Keung's industry connections on their future careers.

Overall, Prof. Keung contributions as a researcher, mentor, educator, and collaborator have left a significant impact on the field of software engineering and computer science. His expertise, publications, and industry partnerships demonstrate his dedication to advancing research and fostering practical applications in various domains.

Selected R&D projects have been successfully awarded over HK$20M+, including GRF: HKGov University Grants Committee (UGC) - General Research Fund, ITF: HKGov Innovation and Technology Commission – Innovation and Technology Fund, TDG: UGC Teaching Development Grant.
  • PI: HK$2.62Million (Industry Collaborative Project 9229029)
    • Smart Intelligent Process Automation for the Mortgage Lending Industry (6/2020~6/2025)
  • PI: HK$565,000 : (Industry Collaborative Project 9220103, 9229098, 9229109, 9220097)
    • Deep Probabilistic Reasoning and Statistical Analysis Using Deep-Learning , (8/2019 ~ 12/2015)
  • PI: HK $240,000 : (UGC/TDG No.6000769)
    • Innovative Learning using Gamification to Enhance Teaching and Learning Software Engineering (6/2022 ~ 1/2024)
  • PI: HK $781,000 : (ITF No.9678149)
    • Software Data Analytics and Blockchain Technological Advancements, Feb/2018 ~ Jul/2022
  • PI: HK $6 Million: (ITF ITS/379/18FX)
    • Deep-learning-based Artificial Intelligence Financial Portfolio Advisory Platform, 2019-2021
  • PI: HK $4 Million: (ITF ITS/380/18FX)
    • Ethereum Blockchain-enabled Common Platform for Self-sovereign Identity and Clinical Record System, 2019-2021
  • PI: HK $333,333 : (No. GRF 11208017)
    • A Software Analytics Framework using Deep Learning on Generalized Data Representations, Sept/2017 ~ Sep/2019
  • PI: HK $6.6 Million: (ITF ITS/133/17FX)
    • Blockchain Enhanced Common Platform for Syndicate Mortgage Transactions, Dec/2017 ~ Dec/2019
  • PI: HK $100,000: (No. 7005217)
    • Concept Drift in Software Defect Prediction and Its Impacts, Sept/2019 ~ Feb/2023
  • PI: HK $100,000: (No. 7005028)
    • Advanced Data Integrity and Exchange Framework for Software Engineering Data, Sept/2018~ Sep/2020
  • PI: HK $100,000 : (No. 7004683 )
    • RacePoint: A Software Defect Complexity Measurement Framework for Managing Data Race Bugs of Multithreaded Software, Sep/2016 ~ Aug/2018 
  • CoI: HK $844,559 : ( GRF 9042328)
    • FAVOR: a testing Framework for detecting Atomicity ViOlations in concuRrent traces, Jan/2017 ~ Jan/2020
  • PI: HK $100,000: (No.7004474)
    • AMORE: A Software Defect Complexity Measurement Framework for Managing Data Race Bugs of Multithreaded Software, Sep/2016 ~ Oct/2017
  • PI: HK $580,000: (No.7200354)
    • Predictive Modelling in Software Engineering using Ensemble Learning Techniques, Jul/2013 ~ Dec/2015
  • PI: HK $100,000 (No.7004222):
    • Exploiting Diversity in Ensembles for Software Effort Estimation Sep/2014 ~ Mar/2016
  • PI: HK $100,000 (No.6000485):
    • A Pragmatic Approach to Changing the Pedagogy of Object-Oriented Programming using Interactive Programming Environment, Nov/2013 ~ Dec/2015
  • PI: HK $100,000 (No.7003032):
    • Application of Case-based Reasoning in the Disease Prevention and Control of Congenital Syphilis in Southern China, Mar/2013 ~ Oct/2014
  • PI: ~ HK$1,200,000
    • Middleware Infrastructure Technology Research Grant Project, Department of Defence, Australia (DSTO) in collaboration with NICTA, 2007 ~ 2009, Australia
  • PI: ~ HK $500,000
    • Boeing Airborne Mission Control System Evaluation, Department of Defence, Australia (DSTO) in collaboration with NICTA, 2009 ~ 2010, Australia
Prof. Keung is accepting Industry Research Collborations and Proposals: 
  • ITF R&D Research Projects (with government cash rebate)
  • Donations from Industry (with government 1:1 matching)
  • Contract Research and Consultancy  (with government cash rebate) 
 
Prof. Keung is currently hiring for (2024/2025 exercise) :
  • Post-doctoral Fellowship (with PhD from HK, or top-100) Candidates  (Salary highly competitive ) 
  • Multiple (10+) Software Developers/Programmers (Salary highly competitive) 
  • PhD Candidates in Software Engineering   (UGC/PhD Fellowship Scheme)
  • PhD Candidates in Software Engineering (Self-Finance Scheme, early 2024 admission)

Research Interests/Areas

  • Software Engineering
  • Empirical Experiments
  • Software Defects
  • Data Mining and Analytics
  • Machine Learning
  • Artificial Intelligence 
  • Data Science and Data Analytics
  • Deep Learning
  • Financial Technology and Blockchain
  • Large Language Models (LLM)

Research Journal Papers published (October 2023)::

  • Journal IEEE Trans.TSE(8), TR(2), TII(1) & ACM Trans. TOSEM(1): x12 (JCR Q1)
  • Journal IST(20): x20 (JCR Q1)
  • Journal JSS(6), EMSE(6), ASE(1), ASC(5), SOFTWARE(1): x19 (JCR Q1)
  • Other Journals: x16
  • Journal Papers (x67) + Conference Papers: (x83): total x150
  • Scopus H-index: 33, citations 5818
  • Google H-index: 40, citations 5686
  • Stanford’s top 2% Most Highly Cited Scientists 2022

 

Selected Journal Publications (For full list here)

  1. Zhen Yang, Jacky Keung, Xiao Yu, Yan Xiao, Zhi Jin, Jingyu Zhang, 2023 "On the Significance of Category Prediction for Code-Comment Synchronization". ACM Trans. Softw. Eng. Methodol. 32(2): 30:1-30:41 (2023)
  2. Y. Tang, H. Wang, X. Zhan, X. Luo, Y. Zhou, H. Zhou, Q. Yan, Y. Sui, J. W. Keung, 2022 "A Systematical Study on Application Performance Management Libraries for Apps," in IEEE Transactions on Software Engineering, 48(8): 3044-3065 (2022)
  3. 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. (2021)
  4. 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. (2018)
  5. 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. (2013)
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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.

Editor or Editorial Membership

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

Prizes/Honours

  • Stanford’s top 2% Most Highly Cited Scientist 2022
  • President's Teaching Excellence Awards (TEA). 2020 
  • Nomination for the UGC Teaching Award 2020 
  • Excellent Paper Award, International Symposium on Education Technology 2023
  • Research Excellence Award in Software Engineering (SIGSE IPSJ Japan) 2018
  • 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

Services outside CityU

  • IEEE Computer Society Hong Kong Chapter (IEEE CS) - Chairman
  • Hong Kong STEM Education Alliance - Vice-President
  • Hong Kong Museum Expert Adviser - Leisure and Cultural Service Department (LCSD) - Expert Adviser/Consultant for LCSD
  • Hong Kong Council for Accreditation of Academic & Vocational Qualifications (HKCAAVQ) - Assessment Specialist on Degree Programmes
  • EDB Curriculum Development Council Standing Committee on STEM Education (EDB) - EDB Curriculum Development Council Panel Member