Te Whiri Kawe—A Centre for Data Science and Artificial Intelligence soon to launch
A new centre for data science and artificial intelligence is being launched at Te Herenga Waka—Victoria University of Wellington early next year, bringing together world-class researchers to solve real-world problems across a range of applications.
The division of Science, Health, Engineering, Architecture and Design Innovation (SHEADI) will inaugurate Te Whiri Kawe—A Centre for Data Science and Artificial Intelligence in the first half of 2023, offering expertise in data science, artificial intelligence, and machine learning.
Pro Vice-Chancellor of the division, Professor Ehsan Mesbahi says the new centre will build on the current success and international leadership in this space at Te Herenga Waka—Victoria University of Wellington.
“We are continuing to grow our national and international partnerships so we can create local and global value.”
One of the key people associated with the centre, Professor Mengjie Zhang, a field leader in Genetic Programming and Evolutionary Computation1, says the team’s world-class researchers are incredibly pleased to be establishing the centre.
“We are excited to be able to offer our capabilities in data science, artificial intelligence and machine learning to our partners, and find solutions to real-world problems.”
Other key researchers in this area at the University include Professor Bing Xue (ranked 20 in Genetic Programming in the Genetic Programming bibliography, one of the largest bibliographies in AI2), Professor Richard Arnold, Associate Professor Ivy Liu, Dr Yi Mei, Dr Kevin Shedlock, Kirita-Rose Escott, as well as support staff Shell Heise, Rachael Odlin, and Sue Hall. The Royal Society of New Zealand ranks Professor Zhang, Professor Xue, and Dr Yi Mei as the top 3 (out of 500) IT/Computer Science researchers in New Zealand.
The Centre will provide a distinctive identity for the growing excellence and innovation in Data Science and Artificial Intelligence research at Victoria University of Wellington, capabilities which national and international partners are increasingly demanding across a vast array of application domains.
It will offer areas of expertise across the following ‘technology themes’—modelling and statistical learning; evolutionary and multi-objective learning; deep learning and transfer learning; image, text, signal, and language processing; scheduling and combinational optimisation; and interpretable artificial intelligence/machine learning.
These themes can be applied across a wide range of areas including primary industry, climate change and environment; health, biology, medical outcomes; security, energy, high-value manufacturing; and social, public policy, and ethics applications.
On top of traditional research, the Centre will also establish a pipeline of scholarships/internships for Māori students, train early career researchers, and focus on industry, IP and commercialisation.
1 Ranked 4th globally in genetic programming entries by author http://gpbib.cs.ucl.ac.uk/gp-html/index.html. Listed the first position regarding full paper publications during 2005-2017, and the third position regarding collaborators per author https://www.researchgate.net/publication/325640427_GECCO_statistics_and_collaboration_network
2 http://gpbib.cs.ucl.ac.uk/gp-html/index.html or https://scholar.google.co.nz/citationsview_op=search_authors&hl=en&mauthors=label:genetic_programming