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Artificial Intelligence Institute Launch

Artificial Intelligence Institute, Te Ipu o te Mahara Launch

27 April 2021

Join us for the official launch of the Artificial Intelligence Institute - Te Ipu o te Mahara at the University of Waikato, which aims to foster connection and knowledge-sharing between tertiary institutions, research organisations and industry, contributing to a vibrant AI ecosystem in New Zealand.

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Full Replay

Dr. Thomas G. Dietterich

Professor Ian Witten

Dr. Alyona Medelyan

Professor Jesse Read

Event Details

When:
Tuesday 27 April 2021, 5:30pm

Cost:
Free

Venue:
Gallagher Academy of Performing Arts, Hamilton NZ

The Artificial Intelligence Institute - Te Ipu o te Mahara will take an interdisciplinary and collaborative approach to the development of cutting-edge research focused on real-time analytics for big data, computer vision and deep learning.  It will also support the building of greater awareness and talent, alongside opportunities to innovate and leverage the technology across disciplines and for the benefit of our communities.

Hear from local and international speakers about the University of Waikato's strength in research, industry collaboration and education in the field of artificial intelligence as well as the areas the new Institute will focus on and plans we have underway for the future.

Programme

Event MC - Jannat Maqbool, Associate Director - AI Institute - Te Ipu o te Mahara

TimeSession
5.30pm

Networking, nibbles and drinks

6.00pm

Mihi Whakatau
Koro Taki Turner, Kaumātua - Hamilton Campus

6.10pm

Opening comments
Professor Neil Quigley, Vice-Chancellor

6:15pm

Professor Bryony James
Deputy Vice-Chancellor Research

6.20pm

Keynote address
Thomas G. Dietterich, Distinguished Professor Emeritus
School of Electrical Engineering and Computer Science
Oregon State University

6.45pm

Professor Ian Witten
Emeritus Professor (Computer Science)
Computing and Mathematical Sciences

7.00pm

Dr. Alyona Medelyan
CEO - Thematic

7.10pm

Professor Jesse Read
Computer Science Laboratory of Ecole Polytechnique (France)

7.20pm

Associate Professor Te Taka Keegan
Co-Director Māori, AI Institute - Te Ipu o te Mahara

7.30pm

Closing comments
Professor Albert Bifet - Director, AI Institute - Te Ipu o te Mahara
Professor Geoff Holmes - Pro Vice-Chancellor, Division of Health, Engineering, Computing & Science

7.40pm

Closing karakia
Koro Taki Turner, Kaumātua - Hamilton Campus

7:45pm

Networking

8.00pm

Close

Gallagher Academy of Performing Arts Building

Venue: Gallagher Academy of Performing Arts, Hamilton NZ

Keynote Speakers

Thomas G. Dietterich

Thomas G. Dietterich

Thomas G. Dietterich (AB Oberlin College 1977; MS University of Illinois 1979; PhD Stanford University 1984) is Distinguished Professor Emeritus in the School of Electrical Engineering and Computer Science at Oregon State University.  Dietterich is one of the pioneers of the field of Machine Learning and has authored more than 200 refereed publications and two books. His current research topics include robust artificial intelligence, robust human-AI systems, and applications in sustainability. Dietterich has devoted many years of service to the research community. He is a former President of the Association for the Advancement of Artificial Intelligence and the founding president of the International Machine Learning Society. Other major roles include Executive Editor of the journal Machine Learning, co-founder of the Journal for Machine Learning Research, and program chair of AAAI 1990 and NIPS 2000. He currently serves as one of the moderators for the cs.LG category on arXiv.

Ian Whitten

Ian Witten

Ian H. Witten graduated from the University of Cambridge with a BA and MA (First Class Honours) in mathematics in 1969 and an M.Sc. in mathematics and computer science from the University of Calgary, where he was a Commonwealth Scholar, in 1970. He received his Ph.D. for Learning to Control in 1976 from the University of Essex, England (Electrical Engineering Science). Witten discovered temporal-difference learning, inventing the tabular TD(0), the first temporal-difference learning rule for reinforcement learning. Witten is a co-creator of the sequitur algorithm and also conceived of and obtained funding for the development of the original WEKA software package for data mining. Witten further made considerable contributions to the field of compression, creating novel algorithms for text and image compression with Alistair Moffat and Timothy C. Bell. He is also one of the major contributors to the digital libraries field, and founder of the New Zealand Digital Library project. Witten is a Fellow of the Royal Society of New Zealand and a recipient of the Hector Memorial Medal which was awarded to him in 2005.


Alyona Medelyan

Alyona Medelyan

Alyona Medelyan, Ph.D. is the CEO of Thematic, an AI-driven feedback analysis solution. Alyona holds a PhD in Natural Language Processing. Her academic work was cited more than 2500 times. Thematic helps companies like LinkedIn, DoorDash, and ManpowerGroup improve customer and user experience through insights from customer feedback.

Jesse Read

Jesse Read

Jesse Read is a Professor in the Computer Science Laboratory of Ecole Polytechnique in France since 2019, after joining as Assistant Professor in 2016. He obtained his PhD from the University of Waikato in 2010, followed by postdoctoral research in the Carlos III University of Madrid (Spain), Aalto University (Finland), and Télécom ParisTech (France).

His research focus is mainly in machine learning, and particularly multi-label learning and models for data streams. He has also picked up interests in Monte Carlo methods and reinforcement learning, and has been involved in numerous applied data-science projects in medicine, biology, transport, wireless sensor networks, and other domains. Jesse was born in Auckland and grew up in the Waikato, completing his BCMS (Hons) degree from the University of Waikato in 2005.

Professor Neil Quigley

Neil Quigley

Neil Quigley is Vice-Chancellor of the University of Waikato, Director of the Reserve Bank of New Zealand, and Director of the New Zealand Qualifications Authority. He has a BA and MA from the University of Canterbury and a PhD from the University of Toronto.

During his career he was Professor of Economics at the University of Western Ontario and Victoria University of Wellington where he taught and published research in the fields of industrial organisation, money and finance and economic history.

Professor Bryony James

Bryony James

Bryony James was appointed as Deputy Vice-Chancellor Research in April 2020 (mid-lockdown) and is responsible for shaping and delivering the University's research strategy.

She was previously Deputy Dean in the Faculty of Engineering at the University of Auckland and has a background in materials science and engineering, and food engineering.

She is a member Physical Sciences Investment Panel, for Return on Science, and a member of the board of WaikatoLink.

Te Taka Keegan

Te Taka Keegan

Te Taka Keegan is an Associate Professor in Computing, and Associate Dean Māori for the Division of Health, Engineering, Computing Science at the University of Waikato.

Te Taka has worked on a number of projects involving the Māori language and technology. These include the Māori Niupepa Collection, Te Kete Ipurangi, the Microsoft keyboard, Microsoft Windows and Microsoft Office in Māori, Moodle in Māori, Google Web Search in Māori, and the Māori macroniser. In 2009 Te Taka spent 6 months with Google in Mountain View as a visiting scientist assisting with the Google Translator Toolkit for Māori. Further work with Google led to Translate in Māori.

In 2013, Te Taka was awarded the University of Waikato's Māori/Indigenous Excellence Award for Research. In 2017 Te Taka was awarded the Prime Minister’s Supreme Award for Tertiary Teaching Excellence. Te Taka’s general research interests include traditional navigation, Māori language technologies, indigenous language interfaces, and multi-lingual usability. His current research interests have focused on the use of Te reo Māori in a technological environment.

Albert Bifet

Albert Bifet

Albert Bifet is Professor at University of Waikato. Previously he worked at Huawei Noah's Ark Lab in Hong Kong, Yahoo Labs in Barcelona, and UPC BarcelonaTech. He is the co-author of a book on Machine Learning from Data Streams published at MIT Press.

He is one of the leaders of MOA, scikit-multiflow and Apache SAMOA software environments for implementing algorithms and running experiments for online learning from evolving data streams. He was serving as Co-Chair of the Industrial track of IEEE MDM 2016, ECML PKDD 2015, and as Co-Chair of KDD BigMine (2019-2012), and ACM SAC Data Streams Track (2021-2012).

Geoff Holmes

Geoff Holmes

Geoff is the Pro Vice-Chancellor, Division of Health, Engineering, Computing & Science. Geoff obtained BSc and PhD degrees in Mathematics from Southampton University, UK in 1986. After time as a research assistant in Cambridge University he joined Waikato in 1987, after moving up the ranks, he was promoted to Professor in 2008, and was also Dean of the Faculty of Computing and Mathematical Sciences .

He has been head of the machine learning group and has been involved in several open source projects over the last 20 years. He has made contributions in machine learning across several branches of the subject and has been active in finding ways to reward researchers for their efforts to produce open source software. In this regard he acts as an action editor for the branch of JMLR dedicated to open source software. He was part of the team that in 2005 won the SIGKDD Data Mining and Knowledge Discovery Service Award for Weka and regularly serves on senior PCs for KDD, ECMLPKDD and Discovery Science.

Janna Maqbool

Jannat Maqbool

Jannat is a CPA and former CIO with a Masters in Digital Business from the University of Waikato and actively engaged in the New Zealand technology ecosystem. With a focus on leveraging technology in innovative ways to benefit individuals, organisations and communities, Jannat has recently taken up the role of Associate Director at the Artificial Intelligence Institute.

Jannat's initial career was in the financial services industry leading mid to large-scale technology adoption initiatives, following which she spent more than a decade in the vocational education sector teaching, and coordinating several collaborative projects and applied research initiatives involving students, staff and the wider community.  More recently Jannat has been involved with supporting digital inclusion and enablement initiatives in the Waikato region, including as Smart Cities Advisor at Hamilton City Council, and Tech Sector Lead at Te Waka: Waikato Regional Economic Development Agency, coordinating the development of the Digital Waikato 2025 strategy and delivering several large events and initiatives bringing together small businesses, schools, tertiary providers, the technology sector and general public.

Jannat is also a Trustee at Web Access Waikato Trust, on the Executive Council at NZ IoT Alliance and TechWomen NZ, a board member at NZ Tech, and Director - NZ at Smart Cities Council ANZ.

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