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

AIML430: Applications and Implications of Artificial Intelligence

COMP309: Machine Learning Tools and Techniques

COMP307: Introduction to Artificial Intelligence

COMP361: Design and Analysis of Algorithms

Publications

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.

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.

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. Early Access.

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.

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.

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.

Mining Feature Relationships in Data

Andrew Lensen, "Mining Feature Relationships in Data." Proceedings of the European Conference on Genetic Programming (EuroGP), 2021.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.