Mengjie Zhang (Meng) BE, ME (AUH), PhD (RMIT), FRSNZ, FEngNZ, FIEEE
	Professor of Computer Science
	Evolutionary Computation and Machine learning Research Group
	Centrer for Data Science and Artificial Intelligence & School of Engineering and Computer Science
	Email: mengjie.zhang@ecs.vuw.ac.nz
	Phone: +64 4 463 5654
	Fax: +64 4 463 5045

Room: CO 355 Postal Address

Research Interests

• Evolutionary Computation (GP, PSO, LCS, DE, EMO)
• Feature Selection and Big Dimensionality Reduction
• Symbolic Regression and Mathematical Modelling
• Computer Vision and Image Analysis
• Evolutionary Deep Learning and Transfer Learning
• Evolutionary Clustering and Visualisation
• Evolutionary Scheduling and Combinatorial Optimisation
• Bioinformatics (Working with Dr Lifeng Peng in Biology)

Research Projects, Funding and Scholarships

• I am working on several research projects.
• I have been awarded the following research grants:
  • Enabling unmanned aerial vehicles (drones) to use tools in complex dynamic environments. Oct 2021-Sep 2026. MBIE Research Program. Grant: $9,837,002. (with UoC)
  • Cyber-physical seafood systems: Intelligent and optimised green manufacturing for marine co-products (PFR, VUW, CI, Otago, Deakin). MBIE Endeavour Research Program Oct 2020-Sep 2025. Grant: $16,280,000. (RA/Theme Leader, Key Researcher)
  • AI and Machine Learning for Medical Applications. Huayin Medical (Industry). Oct 2020-Sep 2023. Grant: $234,000. (PI)
  • Bridging the gap between remote sensing and tree modelling with data science (Landcare, Scion, UoC, VUW). NZ-Singapore MBIE SSIF/Catalyst Fund on Data Science. Oct 2020-Sep 2023. Grant: $3,000,000. (AI, with Jan Schindler at Landcare)
  • A data-science driven evolution of aquaculture for building the blue economy (AI/ML Advanced Research and Applications to Aquaculture). MBIE SSIF Fund on Data Science . 2020-2027. Grant: $13,000,000. (PI)
  • Genetic Programming for Symbolic Regression. Marsden Fund of New Zealand, 2020-2023. Grant: $707,000. (PI)
  • Evolutionary Automated Design of Deep Convolutional Neural Networks for Image Classification. Marsden Fund of New Zealand, 2020-2023. Grant: $707,000. (AI, with Bing Xue)
  • Precision Farming National Science Challenge SfTI Spearhead. 2019-2022. Grant:$3,000,000 (Trench 2). (with Cawthron, UoA, UoC). VUW Grant: $512,300. (Co-PI)
  • Deep Learning Architecture with Context Adaptive Features for Image Parsing (DP200102252). Australia ARC Discover Project. 2020-2022. Grant: $480,000 AUD. (Partner Investigator, with Brijesh Verma at CQU).
  • Distributed and Automated Evolutionary Deep Architecture Learning with Unprecedented Scalability. Dutch Research Council (NWO) & industry partners Elekta and Ortec Logiqcare. 2020-2024. Grant: 1,086,368 Euro. (International Collaborator, with Peter Bosman at Delft)
  • Precision Farming National Science Challenge SfTI Spearhead. 2017-2019. Grant:$2,000,000 (Trench 1). (Chris Cornelisen is the Overall PI, and I am in charge of Artificial Intelligence and Machine Learning aspects)
  • Large-scale Evolutionary Feature Selection for Classification. Marsden Fund of New Zealand, 2016-2019. Grant: $300,000. (AI, with Bing Xue)
  • Automatic Design of Heuristics for Dynamic Arc Routing Problem with Genetic Programming. Marsden Fund of New Zealand, 2016-2019. Grant: $300,000. (Mentor, with Yi Mei).
  • Genetic programming for dynamic flexible job shop scheduling. Marsden Fund of New Zealand, 2016-2019. Grant: $550,000. (PI)
  • A Novel Framework for Optimised Ensemble Classifier. Australian Research Council (ARC) Discovery Project (DP160102639). 2016-2018. Grant: $270,000. (AI, with Brijesh Verma)
  • Distributed data-intensive service composition. Marsden Fund of New Zealand, 2016-2019. Grant: $300,000. (Mentor, with Hui Ma)
  • Genetic Programming for Job Shop Scheduling. Marsden Fund of New Zealand, 2013-2016. Grant: $520,000. (PI)
  • Anomaly Detection in Crowded Scenes using Particle Swarm Optimization and Genetic Programming. Overseas Collaboration Funding with State Key Lab in Software Engineering at Nanjing University. 2014-2016. Grant: $30,000 RMB. (Overseas PI)
  • Study on Bacterial Colony Optimisation Based on Quorum Sensing Mechanism. National Natural Science Foundation of China (International Collaboration). 2012-2013. Grants: $15,000 RMB. (Overseas PI).
  • Conditional outlier detection in Massive Data (using rough sets, granular computing, evolutionary computation techniques). National Natural Science Foundation of China. 2012-2015. Grant: $550,000 RMB. (Co-PI).
  • Feature Manipulation Based on Evolutionary Computation and Rough Sets Methods. Overseas Collaboration in State Key Lab in Software Engineering at Nanjing University. . 2011-2013. Grant: $40,000 RMB. (Co-PI)
  • Toward Optimal Offspring Selection in Genetic Programming. BuildIT Postdoctoral Fellowship Award, New Zealand. 2009-2011. Grant: $138,435. (PI)
  • Genetic Programming for Classification Tasks. Marsden Fund of New Zealand, 2009-2012. Grant: $465,000. (PI)
  • Predictive Difficulty Measures in Genetic Programming based on Complex Networks. International Mobility Fund, New Zealand., 2011. Grant: $8050. (NZPI. Overseas PI: Jing Liu)
  • Novel Program Structures and Search Algorithms in Genetic Programming, Marsden Fund of New Zealand, 2006-2008. Grant: $140,000. (PI)
  • Identification of Authors in Chinese Email, Natural Science Fundation of Hebei Province, China, 2006-2008. Grant: $50,000. (with Guifa Teng)
  • Machine Learning for Speech Recognition, New Economy Research Fund, 2001-2004. (with David Crabbe, etc.) Grant: $330,000.

    
    

  • Novel Transfer Learning Techniques in Genetic Programming for Big Data Mining. University Research Fund, Victoria University of Wellington, 2017-2018. Grant: $43,552.63. (PI).
  • Novel Approaches to High-dimensional Symbolic Regression. University Research Fund, Victoria University of Wellington, 2017. Grant: $32,187.72. (with Bing Xue)
  • Novel Genetic Programming Techniques for Object Recognition. University Research Fund, Victoria University of Wellington, 2015-2017. Grant: $29,834.14. (PI)
  • Evolutionary Computation for Feature Selection in Large-Scale Data Mining. University Research Fund, Victoria University of Wellington, 2016. Grant: $21,413.14. (with Bing Xue)
  • Evolutionary Dimensionality Reduction. Research Establishment Grant Victoria University of Wellington, 2016. Grant: $10,000. (with Bing Xue)
  • Statistical Grouping and Evolutionary Algorithms for Large Scale Classification. University Research Fund, Victoria University of Wellington, 2013-2014. Grant: $42,574. (PI)
  • PSO and Rough Sets for Feature Reduction in Classification. University Research Fund, Victoria University of Wellington, 2012-2013. Grant: $31,976. (PI)
  • Novel Particle Swarm Optimisation Techniques for Image Analysis. University Research Fund, Victoria University of Wellington, 2010-2011. Grant: $30,000. (PI)
  • Learning Classifier Systems for Feature Manipulation and Image Processing. University Research Fund, Victoria University of Wellington, 2010-2011. Grant: $25,000. (with Will Browne)
  • Novel PSO Topologies and Search Algorithms for Pattern Classification. University Research Fund, Victoria University of Wellington, 2009-2010. Grant: $25,000. (PI)
  • Evolutionary Multiple-criterion Optimization for Visual Object Detection. University Research Fund, Victoria University of Wellington, 2009-2010. Grant: $20,000. (with Mark Johnston)
  • Particle Swarm Optimisation for Image Recognition. University Research Fund, Victoria University of Wellington, 2008-2009. Grant: $38,239. (PI)
  • Simplification and Class Imbalance in Genetic Programming. University Research Fund, Victoria University of Wellington, 2008-2009. Grant: $22,580. (with Mark Johnston)
  • Genetic Programming for Image Recognition, University Research Fund, Victoria University of Wellington, 2007. Grant: $48,000. (PI)
  • Program Representations in Genetic Programming, University Research Fund, Victoria University of Wellington, 2005-2006. Grant: $45,500. (PI)
  • Genetic Programming for Multiclass Classification, University Research Fund, Victoria University of Wellington, 2004-2005. Grant: $25,000. (PI)
  • Novel Genetic Programming Techniques for Image Recognition Tasks, University Research Fund, Victoria University of Wellington, 2004. Grant: $12,200. (PI)

• PhD Sholarships: Good students (GPA of A- or above) with publications can apply for the following scholarships:
  • PhD Admission and Scholarships Applications; Victoria PhD scholarship (for PhD candidates already enrolled at, or with an offer of study from VUW). (Closing dates: 1 March, 1 July, 1 November Every Year, for both domestic and international students)

  • VUW and China Scholarship Council PhD Scholarship: (For Chinese Students Only). Successful students will get 48 months of stipend from China Scholarship Council and VUW will cover the tuition fees up to 48 months. An overview and process can be seen from Program Overview. (Closing date: 1 Feb, 1 November Every year)

  • Marsden/Goverment and Industry Funded PhD Scholarships: We are looking for a PhD student in Genetic Programming, Evolutionary Deep Learning, Transfer Learning, Feature Selection/Construction and Big Dimensionality Reduction, Clusering/Classification/Big Data, Image Analysis, Symboic Regression, Evolutionary Scheduling and Combinatorial Optimisation. . We have full funding available to cover tuition fees, living, and travel. Please email me for more information if you have a Masters or Honours degree (with a first-class Honours or Distinction or a GPA of 80% or above) and a good background in Evolutionary Computing, Machine Learning and/or Operations Research! (Closing dates: 1 March 2018, 1 July 2018, 1 November 2018 )

  Contact me if you want to do a PhD in my research areas and want to get a scholarship.

• BSc/BE (COMP/SWEN/AI/DATA) Hons Projects/Summer Research Sholarships --- For Current VUW students only:
  • My research grants can support several summer research scholarships/assistants (from November 2019 to Feburary 2020) and BSc/BE (COMP/SWEN/AI) Honours projects from March to October 2020.
  • Applicants are expected to have a A or above for COMP307, and have strong programming skills in Java/Python/C/C++.
  • Contact me if you want to do a research project in AI, machine learning, evolutionary computation (learning and optimisation), big data/data science/data analytics.