CV
Please see a summary of my CV below. For a full CV, please flick me an email!
Education
- PhD in Computer Science at Victoria University of Wellington, 2019
- BSc (1st Class Hons) in Computer Science at Victoria University of Wellington, 2015
- BSc in Computer Science at Victoria University of Wellington, 2014
Experience
- July 2019 – current: Postdoctoral Research Fellow at Victoria University of Wellington
- May 2019 – July 2019: Research Assistant at Victoria University of Wellington
- July 2016 – June 2019: Tutor at Victoria University of Wellington
- November 2014 – March 2015: Summer Research Scholar at Victoria University of Wellington
- November 2013 – November 2014: Software Engineer at TechTime, Wellington
Teaching
Publications
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A Genetic Programming Encoder for Increasing Autoencoder Interpretability
Finn Schofield, Andrew Lensen, Luis Slyfield, "A Genetic Programming Encoder for Increasing Autoencoder Interpretability." Proceedings of the European Conference on Genetic Programming (EuroGP), 2023. To Appear.
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Feature-based Image Matching for Identifying Individual Kākā
Fintan O'Sullivan, Kirita-Rose Escott, Rachael Shaw, Andrew Lensen, "Feature-based Image Matching for Identifying Individual Kākā." arXiv, 2023. https://doi.org/10.48550/arXiv.2301.06678.
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Using Neural Networks to Automate Monitoring of Fish Stocks
Michael Stanley, Andrew Lensen, Mengjie Zhang, "Using Neural Networks to Automate Monitoring of Fish Stocks." Proceedings of the Symposium Series on Computational Intelligence (SSCI), 2022.
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Explainable Artificial Intelligence by Genetic Programming: A Survey
Yi Mei, Qi Chen, Andrew Lensen, Bing Xue, Mengjie Zhang, "Explainable Artificial Intelligence by Genetic Programming: A Survey." IEEE Transactions on Evolutionary Computation, 2022. Early Access.
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Speeding up Genetic Programming Based Symbolic Regression Using GPUs
Rui Zhang, Andrew Lensen, Yanan Sun, "Speeding up Genetic Programming Based Symbolic Regression Using GPUs." Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2022.
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Genetic Programming for Manifold Learning: Preserving Local Topology
Andrew Lensen, Bing Xue, Mengjie Zhang, "Genetic Programming for Manifold Learning: Preserving Local Topology." IEEE Transactions on Evolutionary Computation, 2022.
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Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand
Harry Rodger, Andrew Lensen, Marcin Betkier, "Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand." Journal of the Royal Society of New Zealand, 2022. doi: 10.1080/03036758.2022.2114506.
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Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution
Hayden Andersen, Andrew Lensen, Will N. Browne, Yi Mei, "Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2022.
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Large Scale Image Classification Using GPU-based Genetic Programming
Peng Zeng, Andrew Lensen, Yanan Sun, "Large Scale Image Classification Using GPU-based Genetic Programming." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2022.
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Improving the Search of Learning Classifier Systems Through Interpretable Feature Clustering
Hayden Andersen, Andrew Lensen, Will N. Browne, "Improving the Search of Learning Classifier Systems Through Interpretable Feature Clustering." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2022.
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Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation
Andrew Lensen, Bing Xue, Mengjie Zhang, "Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation." IEEE Transactions on Cybernetics, 2021.
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Using Genetic Programming to Find Functional Mappings for UMAP Embeddings
Finn Schofield, Andrew Lensen, "Using Genetic Programming to Find Functional Mappings for UMAP Embeddings." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2021.
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Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms
Hayden Andersen, Andrew Lensen, Bing Xue, "Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2021.
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Mining Feature Relationships in Data
Andrew Lensen, "Mining Feature Relationships in Data." Proceedings of the European Conference on Genetic Programming (EuroGP), 2021.
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Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis
Andrew Lensen, Bing Xue, Mengjie Zhang, "Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis." Evolutionary Computation, 2020.
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Evolving Simpler Constructed Features for Clustering Problems with Genetic Programming
Finn Schofield, Andrew Lensen, "Evolving Simpler Constructed Features for Clustering Problems with Genetic Programming." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2020.
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Multi-Objective Genetic Programming for Manifold Learning: Balancing Quality and Dimensionality
Andrew Lensen, Mengjie Zhang, Bing Xue, "Multi-Objective Genetic Programming for Manifold Learning: Balancing Quality and Dimensionality." Genetic Programming and Evolvable Machines, 2020.
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Evolutionary Feature Manipulation in Unsupervised Learning
Andrew Lensen, "Evolutionary Feature Manipulation in Unsupervised Learning." , 2019.
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Can Genetic Programming Do Manifold Learning Too?
Andrew Lensen, Bing Xue, Mengjie Zhang, "Can Genetic Programming Do Manifold Learning Too?." Proceedings of the European Conference on Genetic Programming (EuroGP), 2019. Best paper.
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A survey on evolutionary machine learning
Harith Al-Sahaf, Ying Bi, Qi Chen, Andrew Lensen, Yi Mei, Yanan Sun, Binh Tran, Bing Xue, Mengjie Zhang, "A survey on evolutionary machine learning." Journal of the Royal Society of New Zealand, 2019.
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Automatically Evolving Difficult Benchmark Feature Selection Datasets with Genetic Programming
Andrew Lensen, Bing Xue, Mengjie Zhang, "Automatically Evolving Difficult Benchmark Feature Selection Datasets with Genetic Programming." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2018.
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Particle Swarm Optimisation for Feature Selection and Weighting in High-Dimensional Clustering
Damien O'Neill, Andrew Lensen, Bing Xue, Mengjie Zhang, "Particle Swarm Optimisation for Feature Selection and Weighting in High-Dimensional Clustering." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2018.
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Generating Redundant Features with Unsupervised Multi-tree Genetic Programming
Andrew Lensen, Bing Xue, Mengjie Zhang, "Generating Redundant Features with Unsupervised Multi-tree Genetic Programming." Proceedings of the European Conference on Genetic Programming (EuroGP), 2018.
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New Representations in Genetic Programming for Feature Construction in k-Means Clustering
Andrew Lensen, Bing Xue, Mengjie Zhang, "New Representations in Genetic Programming for Feature Construction in k-Means Clustering." Proceedings of the 11th International Conference on Simulated Evolution and Learning (SEAL), 2017.
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GPGC: genetic programming for automatic clustering using a flexible non-hyper-spherical graph-based approach
Andrew Lensen, Bing Xue, Mengjie Zhang, "GPGC: genetic programming for automatic clustering using a flexible non-hyper-spherical graph-based approach." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2017.
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Using Particle Swarm Optimisation and the Silhouette Metric to Estimate the Number of Clusters, Select Features, and Perform Clustering
Andrew Lensen, Bing Xue, Mengjie Zhang, "Using Particle Swarm Optimisation and the Silhouette Metric to Estimate the Number of Clusters, Select Features, and Perform Clustering." Proceedings of the European Conference on the Applications of Evolutionary Computation (EvoApplications), Part I, 2017.
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Improving k-means clustering with genetic programming for feature construction
Andrew Lensen, Bing Xue, Mengjie Zhang, "Improving k-means clustering with genetic programming for feature construction." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2017.
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Particle Swarm Optimisation Representations for Simultaneous Clustering and Feature Selection
Andrew Lensen, Bing Xue, Mengjie Zhang, "Particle Swarm Optimisation Representations for Simultaneous Clustering and Feature Selection." Proceedings of the Symposium Series on Computational Intelligence (SSCI), 2016.
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Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data
Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, Bing Xue, "Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data." Proceedings of the European Conference on Genetic Programming (EuroGP), 2016.
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A hybrid Genetic Programming approach to feature detection and image classification
Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, Bing Xue, "A hybrid Genetic Programming approach to feature detection and image classification." Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ), 2015.
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Genetic Programming for algae detection in river images
Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, Brijesh Verma, "Genetic Programming for algae detection in river images." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2015.