Dr Andrew Lensen

Cotton 354

School of Engineering and Computer Science

Kia ora!

I am a Senior Lecturer (Pūkenga Matua) in Artificial Intelligence (Atamai Horihori) at Te Herenga Waka—Victoria University of Wellington (THW-VUW), Aotearoa/New Zealand.

These days, I primarily specialise in explainable and interdisciplinary AI. My research explores AI’s social and ethical implications, with applications in ecology, legal decision-making, and more. I am an active science communicator, frequently contributing op-eds, interviews, and expert commentary on AI-related topics (see media).

I also have interests in ``fundamental” machine learning, such as genetic programming, unsupervised learning (nonlinear dimensionality reduction), as well as aspects of deep learning, such as embedding/manifold learning methods. For further information about my research, take a look at the projects and publications pages.

student opportunities

I currently have a full roster of thesis students and so I am limited in my ability to take on new students. If your research interests align with mine, please still get in touch — as I can be convinced for the right project! I am also able to host a limited number of visiting students.

collaboration

My interdisciplinary AI research involves collaboration with researchers across many different disciplines. I have some limited capacity for new research collaborations.

Chris McGavin and I have recently launched our new AI consultancy, LensenMcGavin AI. Check us out and get in touch if you need help with responsible AI: https://lm-ai.nz

teaching

In addition to my research, I also lecture in a range of AI and general computer science courses. My full teaching record is here.

We are offering a brand-new major in AI at THW-VUW from 2023 — the first University in NZ to do so. Take a look. We also have a very strong postgraduate qualification, the Master of AI.

Interested in AI but don’t want a full degree — or missing a programming/maths background? Check out the “Introduction to AI” (AIML 131) I teach, which is a new first-year course designed for an audience with no background in AI.

selected publications

Explainable Artificial Intelligence by Genetic Programming: A Survey

Yi Mei, Qi Chen, Andrew Lensen, Bing Xue, and Mengjie Zhang

IEEE Transactions on Evolutionary Computation, Nov 2023

Bib PDF DOI

@article{mei2022explainable,
  author = {Mei, Yi and Chen, Qi and Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
  title = {Explainable Artificial Intelligence by Genetic Programming: A Survey},
  journal = {{IEEE} Transactions on Evolutionary Computation},
  pages = {621--641},
  year = {2023},
  volume = {27},
  number = {3},
  month = nov,
  day = {25},
  publisher = {IEEE},
  doi = {10.1109/TEVC.2022.3225509},
}

Feature-based Image Matching for Identifying Individual Kākā

Fintan O’Sullivan, Kirita-Rose Escott, Rachael C. Shaw, and Andrew Lensen

arXiv, Jan 2023

Bib PDF DOI

@article{osullivan2023feature,
  author = {O'Sullivan, Fintan and Escott, Kirita{-}Rose and Shaw, {Rachael C.} and Lensen, Andrew},
  title = {Feature-based Image Matching for Identifying Individual Kākā},
  year = {2023},
  doi = {10.48550/arXiv.2301.06678},
  eprinttype = {arXiv},
  eprint = {2301.06678},
  journal = {arXiv},
  month = jan,
  day = {17},
}

Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand

Harry Rodger, Andrew Lensen, and Marcin Betkier

Journal of the Royal Society of New Zealand, Aug 2022

Bib PDF DOI

@article{rodger2022explainable,
  author = {Rodger, Harry and Lensen, Andrew and Betkier, Marcin},
  title = {Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand},
  journal = {Journal of the Royal Society of New Zealand},
  year = {2022},
  month = aug,
  pages = {1--15},
  day = {15},
  publisher = {Taylor & Francis},
  doi = {10.1080/03036758.2022.2114506},
}