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Associate Professor C. Peng Lam

Associate Professor - Software Engineering

Staff Member Details
Telephone: +61 8 6304 6914
Campus: Joondalup  

Peng is an Associate Professor of Software Engineering in the School of Science.

Current Teaching

  • Software Engineering.

Course Coordination:

  • Postgraduate Coordinator for the School of Science
  • Course Coordinator for Master of Science (Computer Science - by Research Course code: Q45, J16)
  • Course Coordinator for Doctor of Information Technology (Course Code: Q58, L14)
  • Course Coordinator for Doctor of Philosophy (Course Code: L10)


Peng's teaching and research focus is in the area of search-based software engineering, image analysis and computational intelligence within the School of Science. She is the co-leader of the Artificial Intelligence and Optimisation Research Cluster.

Professional Associations

  • Institute of Electrical and Electronics Engineers (IEEE)

Research Areas and Interests

  • Software Testing, Health Information Technology, Search-based Software Engineering, Data Mining, Computational Intelligence, Image Processing
  • Search-based Software testing, Mobile phone remote health diagnosis, Data mining, Bioinformatics, Computational red teaming


  • Doctor of Philosophy, Curtin University of Technology, 1995.


Recent Research Grants

  • Methods for Identifying Anomalies in Real Time Maritime Traffic Data,  Defence Science and Technology Group of the Department of Defence,  Grant,  2020 - 2021,  $196,756.
  • Interactive Evolutionary Computation for the Discovery of Warfighting Strategies ,  Department of Jobs, Tourism, Science and Innovation,  Defence Science Collaborative Research Grants,  2020 - 2021,  $149,880.
  • Opportunities and Implications of using Artificial Intelligence in the Establishment of Secure Physical Environments,  ASIS International,  ASIS - Grant,  2020 - 2021,  $47,800.
  • Evolutionary Algorithms for Real Time Strategy games,  Defence Science and Technology Group of the Department of Defence,  Grant,  2018 - 2019,  $53,373.
  • Evolutionary Algorithms for Complex Multi-Agent Simulation of Air Operations,  Defence Science and Technology Group of the Department of Defence,  Grant,  2017 - 2018,  $97,846.
  • Establishing a 3D sensing, visualisation and analytics lab,  Edith Cowan University,  Edith Cowan University, School of Science 2017 Strategic Initiative Fund,  2017,  $115,368.
  • Co-Evolutionary Algorithms for Multi-Agent Simulation of Air Operations,  Defence Science and Technology Group of the Department of Defence,  Grant,  2016 - 2017,  $44,339.
  • Simulation game engines for Maritime Experimentation,  Defence Science and Technology Group of the Department of Defence,  Grant,  2016,  $22,043.
  • Trailblazer: A Framework for Context Aware Multimodal Learning,  Edith Cowan University,  ECU Industry Collaboration Grant - 2013,  2013 - 2015,  $109,392.
  • Game based learning and educational data mining,  Edith Cowan University,  ECU Industry Collaboration Grant - 2014 (Round 1),  2014 - 2015,  $209,936.
  • Discovery and Validation of Alzheimer's disease biomarkers in human plasma,  National Health and Medical Research Council,  Project Grants,  2011 - 2014,  $352,524.
  • Remote Blood Pressure Monitoring for Preeclampsia,  Nortel Networks,  Grant - Development,  2011 - 2012,  $46,405.
  • Versatile Care @ Residential Environment - V-C@RE(tm),  Nortel Networks,  Grant - Development,  2009 - 2010,  $49,374.
  • Alarm Management - Silence is Golden.,  Australian Research Council,  Grant - Linkage (APAI),  2003 - 2007,  $124,552.
  • Configuration Management Techniques for Promoting Reuse in Process Design and Modelling,  Australian Research Council,  Grant - SPIRT,  2001 - 2005,  $57,915.

Recent Publications (within the last five years)

Journal Articles

  • Pech, A., Lam, P., Masek, M., (2020), Quantifiable Isovist and Graph-based Measures for Automatic Evaluation of Different Area Types in Virtual Terrain Generation. IEEE Access, 8(2020), 216491-216506, DOI: 10.1109/ACCESS.2020.3041276.
  • Lam, P., Masek, M., Kelly, L., Papasimeon, M., Benke, L., (2019), A simheuristic approach for evolving agent behaviour in the exploration for novel combat tactics. Operations Research Perspectives, 6(2019), Article Number 100123, DOI:
  • Masek, M., Lam, P., Tranthim-Fryer, C., Jansen, B., Baptist, K., (2018), Sleep monitor: A tool for monitoring and categorical scoring of lying position using 3D camera data. SoftwareX, 7(January–June 2018), 341-346, DOI: 10.1016/j.softx.2018.10.001.
  • Masek, M., Boston, J., Lam, P., Corcoran, S., (2017), Improving mastery of fractions by blending video games into the Math classroom. Journal of Computer Assisted Learning, 33(5), 486-499, DOI: 10.1111/jcal.12194.
  • Pech, A., Masek, M., Lam, P., Hingston, P., (2016), Game level layout generation using evolved cellular automata. Connection Science, 28(1), 63-82, Taylor & Francis, DOI: 10.1080/09540091.2015.1130020.
  • Adi, E., Baig, Z., Hingston, P., Lam, P., (2016), Distributed denial-of-service attacks against HTTP/2 services. Cluster Computing, 19(1), 79-86, Springer New York LLC, DOI: 10.1007/s10586-015-0528-7.

Conference Publications

  • Masek, M., Lam, P., Kelly, L., Wong, M., (2019), Evolving behaviour trees for automated discovery of novel combat strategy in real-time strategy wargames. MODSIM2019, 23rd International Congress on Modelling and Simulation, 277-283, Online, Modelling and Simulation Society of Australia and New Zealand, DOI: 978-0-9758400-9-2.
  • Masek, M., Lam, P., Benke, L., Kelly, L., Papasimeon, M., (2018), Discovering Emergent Agent Behaviour with Evolutionary Finite State Machines. PRIMA 2018: Principles and Practice of Multi-Agent Systems, 11224(October 31-November 2, 2018), 19-34, Cham, Springer, DOI: 10.1007/978-3-030-03098-8_2.
  • Pazhoumanddar, H., Lam, P., Masek, M., (2017), An Automatic Approach for Generation of Fuzzy Membership Functions. Agents and Artificial Intelligence 8th International Conference, ICAART 2016, Revised Selected Papers, LNAI, volume 10162(24-26 February, 2016), 247-264, Springer, DOI: 10.1007/978-3-319-53354-4_14.
  • Pazhoumanddar, H., Masek, M., Lam, P., (2016), Unsupervised monitoring of electrical devices for detecting deviations in daily routines. 2015 10th International Conference on Information, Communications and Signal Processing (ICICS), 1-6, IEEE, DOI: 10.1109/ICICS.2015.7459849.
  • Wheat, D., Masek, M., Lam, P., Hingston, P., (2016), Modeling perceived difficulty in game levels. Proceedings of the Australasian Computer Science Week Multiconference, Article no. a74, Australian Computer Society Inc., DOI: 10.1145/2843043.2843478.
  • Pech, A., Lam, P., Hingston, P., Masek, M., (2016), Using isovists to evolve terrains with gameplay elements. Applications of Evolutionary Computation, 9597(30 Mar - 1 Apr 2016), 636-652, Springer Verlag, DOI: 10.1007/978-3-319-31204-0_41.
  • Pazhoumanddar, H., Lam, P., Masek, M., (2016), A Novel Fuzzy Based Home Occupant Monitoring System Using Kinect Cameras. 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI), 1129-1136, Piscataway N.J., IEEE, DOI: 10.1109/ICTAI.2015.160.
  • Pazhoumanddar, H., Lam, P., Masek, M., (2016), Automatic Generation of Fuzzy Membership Functions using Adaptive Mean-shift and Robust Statistics. Proceedings of the 8th International Conference on Agents and Artificial Intelligence, 2(24-26 Feb 2016), 160-171, Science and Technology Publications, DOI: 10.5220/0005751601600171.
  • Dang, V., Lam, P., (2016), Gene selection using a hybrid memetic and nearest shrunken centroid algorithm. BIOINFORMATICS 2016 - 7th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016, 190-197, online only, Science and Technology Publications, DOI: 10.5220/0005665201900197.

Research Student Supervision

Principal Supervisor

  • Doctor of Philosophy,  Evolutionary approaches for feature selection in biological data
  • Doctor of Philosophy,  Model based test suite minimization using metaheuristics.
  • Doctor of Philosophy,  Alarm management - mining for groups of co-occuring alarm tags
  • Doctor of Information Technology,  An investigation into the use of neural networks for the prediction of the stock exchange of Thailand.
  • Doctor of Information Technology,  Coevolutionary algorithms for the optimization of strategies for red teaming applications
  • Doctor of Philosophy,  Strategies for the intelligent selection of components

Co-principal Supervisor

  • Doctor of Philosophy,  Evolving gameplay elements into virtual terrains

Associate Supervisor

  • Doctor of Philosophy,  Intelligent network intrusion detection using an evolutionary computation approach
  • Master of Science (Computer Science),  Seagrass detection using deep learning
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