Centre for Discrete Mathematics and Theoretical Computer Science



Welcome to CDMTCS, a joint venture involving the School of Computer Science and the Mathematics and Philosophy Departments of The University of Auckland in New Zealand. CDMTCS was founded in 1995 to support basic research on the interface between mathematics and computing, to foster research and development in these areas within the South Pacific region, and to create links between researchers in that region and their counterparts in the rest of the world.

News and Events

Unconventional Computation and Natural Computation 2019

The International Conference on Unconventional Computation and Natural Computation is a meeting where scientists from many different backgrounds are united in their interest in novel forms of computation, human-designed computation inspired by nature, and computational aspects of natural processes. UCNC provides a forum for such scientists to meet and discuss their work.
The 18th UCNC will be hosted by will be hosted by the University of Electro-Communications, Tokyo.

Mathematics Almost Everywhere. In Memory of Solomon Marcus: the book presentation will take place on 27 August 2018 at the University of Bucharest, Romania.

Speakers: C. Calude, G. Dinca, L. Leustean, G. Paun, D. Stefanescu, T. Zamfirescu. Pictures.

A talk by Aaron Li at the Data Science Club 2018

On 2 August 2018 Aaron Li, CEO of Qokka.ai., a former student of Prof. C. Calude and Dr. M. Dinneen, gave the talk Machine learning & Blockchain at the Data Science Club.

Aaron got a BSc from Australian National University and an MSc in Languages Technologies (Computer Science) from Carnegie Mellon University. He immigrated to USA and was granted an "Extraordinary Ability Green Card (EB-1A)" (Einstein Green Card). Aaron worked as an engineer in machine learning at Google Research and lead engineer at the startup Scaled Inference" before founding his own company Qokka.ai.

A talk by Shane Legg at the Data Science Club 2018

On 6 May 2018 DeepMind Co-founder Shane Legg gave the talk Does this road lead to AGI? at the Data Science Club.

To succeed in AI you need to know 1) inear algebra well (e.g. matrix maths), 2) calculus to an OK level (not advanced stuff), 3) probability theory and stats (to a good level), 4) theoretical computer science basics to code well in Python and OK in C++, S. Legg (BBC)

DeepMind’s AlphaGo and Message from Shane Legg at the Data Science Club 2018

The University of Auckland data science club will be holding a free screening of the 2017 documentary AlphaGo and playing a recorded message from University of Auckland alumnus Shane Legg, who is a cofounder of the artificial intelligence company DeepMind.

DeepMind was acquired by Google in 2014 for US$500 million, and in 2016 developed the program AlphaGo that used a deep neural network and reinforcement learning to beat the world champion of the complex board game Go for the first time. We will be showing the exciting 90 minute documentary, which is rated 8/10 on IMDB, and follows the development of the record-breaking program and its match against then world-champion Lee Sedol in his home country of South Korea.

Shane Legg is one of the three cofounders of DeepMind, and is an alumnus of Auckland university, completing his master's degree in mathematics in 1996, see his CDMTCS Research Report 030, March 1997: Solomonoff Induction, with complexity theorist Professor Cristian Calude. He went on to complete his PhD in Switzerland on super-intelligent machines, be awarded the $10,000 Canadian Singularity Institute for Artificial Intelligence Prize, and take up post-doctoral research at the Gatsby Computational Neuroscience Unit in London, before cofounding DeepMind in 2010. He has kindly agreed to record a message especially to accompany our documentary screening.

Please give us your feedback or ask us a question

This message is...

My feedback or question is...

My email address is...

(Only if you need a reply)

A to Z Directory | Site map | Accessibility | Copyright | Privacy | Disclaimer | Feedback on this page