Speakers

30+ senior researchers from around the country

Watch at the Presentations page

Albert Bifet - University of Waikato

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).

Alex Gavryushkin - University of Otago

Alex Gavryushkin graduated from Novosibirsk University in 2009 with PhD in Mathematics, and completed postdoctoral fellowships at the University of Auckland and ETH Zurich. A Rutherford Discovery Fellowship brought Alex back to New Zealand, where he is currently heading a Biological Data Science lab at the University of Otago funded by a number of awards from the Royal Society Te Apārangi and Ministry of Business, Innovation, and Employment.

Alvaro Orsi - PlantTech Research Institute

Alvaro Orsi is a Principal Research Scientist at PlantTech, with over 12 years of experience in Scientific computing, AI and Machine learning applied to address both scientific and data-driven industry challenges. In 2010 I obtained a PhD in Computational Cosmology from Durham University, UK. After that I took 2 postdoctoral appointments in Chile, at the Institute of Astrophysics of Universidad Catolica. In 2015 I became a Cosmology Research Staff at Aragon's Research Centre of Physics of the Cosmos (CEFCA), in Spain. In 2019, shortly after moving to NZ I joined PlantTech as a Principal Scientist. Since then I've been implementing solutions for the NZ Horticulture industry through artificial intelligence technology.

Amanda Williamson - University of Waikato

Amanda is a Lecturer in Innovation and Strategy at the University of Waikato. She conducts research at the intersection of psychology and entrepreneurship by leveraging artificial intelligence/natural language processing. Dr Williamson has published in the leading journal for her field, and is engaged in ongoing international collaborations.

Andreas W. Kempa-Liehr - University of Auckland

Andreas is a Senior Lecturer at the Department of Engineering Science of the University of Auckland, New Zealand, and an Associate Member of the Freiburg Materials Research Center (FMF) at the University of Freiburg, Germany. Andreas received his doctorate from the University of Münster in 2004 and continued his research as head of service group Scientific Information Processing at FMF. From 2009 to 2016 he was working in different data science roles at EnBW Energie Baden-Württemberg AG and Blue Yonder GmbH in Karlsruhe, Germany.

Andrew Lensen - University of Victoria

Dr Andrew Lensen received the BSc (Hons) and PhD degrees in computer science from Te Herenga Waka—Victoria University of Wellington in 2016 and 2019 respectively. He is a Lecturer in AI (Pūkenga) in the Evolutionary Computation Research Group within the School of Engineering and Computer Science at Victoria University of Wellington. His current research interests are in the use of evolutionary computation for interpretable feature manipulation in unsupervised learning, with a particular focus on applying genetic programming to manifold learning, clustering, and data mining. He also maintains an interest in other AI topics, including neuroevolution, image analysis, and explainable AI.

Bernhard Pfahringer - University of Waikato

Bernhard Pfahringer received his PhD degree from the University of Technology in Vienna, Austria, in 1995. He is a Professor with theDepartment of Computer Science at the University of Waikato. His interests span a range of data mining and machine learning sub-fields, with a focus on streaming, randomization, and complex data.

Bing Xue - University of Victoria

Bing is currently a Professor in Computer Science and AI, the Program Director of Science in School of Engineering and Computer Science at Victoria University of Wellington. Bing's research focuses mainly on AI and evolutionary computation for machine learning and data mining, and their applications. Prof. Xue has over 200 papers published in fully refereed international journals and conferences. She has been serving as a key chair for a large number of international conferences, and an Associate Editor of several international journals, such as IEEE Transactions on Evolutionary Computation, and Journal of the Royal Society of New Zealand.

Bob Durrant - University of Waikato

Bob Durrant, Senior Lecturer Department of Maths and Stats, U. Waikato, has a BSc(Hons) Mathematical Sciences from the Open University UK, and an MSc Natural Computation, PhD Computer Science both from University of Birmingham UK. His doctoral research mainly focused on theory quantifying the cost of random projection (RP) on classification performance, and a generic and interpretable algorithm for classification (with data-dependent performance guarantees) for n<p problems which employs RP. He is especially interested in the n<p problem, and when one can give performance guarantees, with high confidence, in these settings. He reviews widely for machine learning conferences and for machine learning and statistical journals, and his work on theory and applications of RP has garnered three conference 'best paper' awards

Eibe Frank - University of Waikato

Eibe Frank is a Professor in the Department of Computer Science at the University of Waikato. He obtained a first degree in computer science from the University of Karlsruhe, Germany, and a PhD in computer science from the University of Waikato. He has published extensively in the areas of machine learning and data mining and refereed for many conferences and journals in these areas. Jointly with others, he has received a Service Award from the Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining and two Test of Time Awards from the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.

Giulio Valentino Dalla Riva - University of Canterbury

Giulio Valentino Dalla Riva is a Senior Lecturer in Data Science at the University of Canterbury | Te Whare Wananga o Waitaha. He is from Italy, where he studied mathematics and complex networks. His research involves dynamical processes on and of complex networks, and is becoming more and more interdisciplinary opening to mixed methodology analysis of Social Networks. He has a keen interest in data ethics.

Hans W. Guesgen - Massey University

Hans Guesgen is a professor of computer science at Massey University, New Zealand. His research interests include smart environments, ambient intelligence (ubiquitous computing with artificial intelligence), knowledge representation, and spatio-temporal reasoning, with more than 250 publications in these areas. He holds a doctorate in computer science of the University of Kaiserslautern, and a higher doctorate (Habilitation) in computer science of the University of Hamburg, Germany. Hans is a senior member of the Association for the Advancement of Artificial Intelligence (AAAI) and an honorary fellow of the Munich University of Applied Sciences. He has been a member of the programme committees of more than 100 international conferences and workshops, and has served as a referee for the Australian Research Council, the US National Science Foundation, and the NZ Foundation for Research Science and Technology.

Harith Al-Sahaf - University of Victoria

Harith Al-Sahaf received the BSc degree in Computer Science from the Baghdad University (Iraq), in 2005. He joined the Victoria University of Wellington (VUW), (New Zealand) in July 2007 where he received his MCompSc and PhD degrees in Computer Science in 2010 and 2017, respectively. In October 2016, he joined the School of Engineering and Computer Science, VUW as a Post-doctoral Research Fellow and as a full-time lecturer since September 2018. His current research interests include evolutionary computation, particularly genetic programming, computer vision, pattern recognition, evolutionary cybersecurity, machine learning, feature manipulation including feature detection, selection, extraction and construction, transfer learning, domain adaptation, one-shot learning, and image understanding. He is the Vice-Chair of the IEEE Computational Intelligence Society (CIS) ISATC Task Force on Intelligent Systems for Cybersecurity of IoT and a member of the IEEE CIS ETTC Task Force on Evolutionary Computer Vision and Image Processing, the IEEE CIS ETTC Task Force on Evolutionary Computation for Feature Selection and Construction, and the IEEE CIS ISATC Task Force on Evolutionary Deep Learning and Applications.

Heitor Murilo Gomes - University of Waikato

Heitor Gomes is a senior research fellow at the University of Waikato, and before that, he was a postdoctoral researcher at Télécom Paris (IP-Paris, Paris, France) for two years after receiving his PhD in 2017 at PUCPR (Brazil). His research interests include ensemble learning, data stream mining, semi-supervised learning and distributed machine learning. He has published more than 40 peer-reviewed journal and conference papers and serves as a reviewer for premier conferences and journals. He contributes to some open data stream mining projects, mainly the Massive Online Analysis (MOA) framework.

Helen Lu - University of Auckland

Helen Lu is a senior lecturer in finance at the University of Auckland. Her research areas include machine learning, asset pricing and executive successions. She has published in leading finance journals including Journal of Banking and Finance, Journal of International Money and Finance and Economic Letters. Prior to moving to New Zealand and returning to her academic life, Helen was a vice president at Credit Suisse and, before that, at Deutsche Bank in Hong Kong. Her corporate finance experience includes IPOs, privatisations, convertible bonds and cross-border M&A for clients in the natural resources and the general industries sectors. Helen holds a PhD in Finance from Massey, an MBA from London Business School, a Masters of Economics from Peking University, and a Bachelor of Engineering (Computer Science) from Northern Jiaotong University in China.

James Atlas - University of Canterbury

James Atlas completed his PhD in 2009 and has over a decade of experience as faculty at the University of Canterbury in New Zealand and the University of Delaware in the USA. His research area is deep learning for physical models, distributed artificial intelligence, constraint optimization, and scientific computing. He is interested in large scale data models, simulations, and applications in health care and space exploration including current projects in spectral computed tomography imaging biomedical sensors. He also contributes to computer science education efforts with primary and secondary school teachers. He enjoys trail running, travel, board games, and painting.

Jaspreet Dhupia - University of Auckland

Dr. Jaspreet Dhupia is a Senior Lecturer in the Department of Mechanical and  Mechatronics Engineering in the University of Auckland. His research interests  lie in mechatronics, industrial automation and system monitoring. To this end,  Dr. Dhupia leverages his expertise in model and data driven approaches for  system identification, complex systems model discovery, system kinematics  and dynamic analysis, and control applications for robust system performance.  He is currently serving as a Senior Member of IEEE, a Technical Editor for  IEEE/ASME Transactions of Mechatronics and an Associate Editor for the ASME Dynamic Systems  and Control Division. He has PhD and MS in Mechanical Engineering from the University of Michigan  (USA) and B.Tech. in Mechanical Engineering from Indian Institute of Technology, Delhi (India). 

Jesin James - University of Auckland

Jesin is a Lecturer in the Department of Electrical, Computer, and Software Engineering at the University of Auckland, New Zealand. Jesin's main research areas are speech signal processing, under-resourced languages, machine learning and engineering education. During 2012-2014 she worked on developing a speech technology in her mother tongue, Malayalam (language spoken in south India), with special emphasis on developing a prosodic model for the same. Further, during 2014-2016 she worked as a Lecturer in Electronics and Communication Engineering in India, during which she was involved in some student projects that have been published and presented to a wider audience. In 2016, she joined University of Auckland as Ph.D scholar in Computer systems engineering. Jesin is currently working on developing speech analysis tools and speech technology for under-resourced languages like Malayalam, Māori, New Zealand English, by combining her language knowledge and engineering education.

Jiamou Liu - University of Auckland

Jiamou Liu is a Senior Lecturer at the School of Computer Science, The University of Auckland. Before joining the UoA, he was a Senior Lecturer at Auckland University of Technology between 2011 and 2015. Jiamou obtained a PhD in Computer Science from the University of Auckland and worked as a research associate at the University of Leipzig between 2009 and 2010 and Paris Diderot University (Paris 7) in 2013. He was a research intern at Microsoft Research Asia in 2008. During his PhD, he was a visiting student at Cornell University and the National University of Singapore. His work revolves around the structural analysis of social networks, multiagent systems, as well as natural language processing. His recent research also connects to health-care, data privacy, computational social science, and spatial-temporal data analysis with application in traffic flow prediction. He has published more than 90 papers at international venues that include NeurIPS, AAAI, IJCAI, LICS, AAMAS, and UAI. His work was supported by Marsden Fund (Fast Start 2012-2016).

Michael Cree - University of Waikato

Michael Cree is an Associate Professor in Electrical and Electronic Engineering at the University of Waikato. His research interests span medical imaging, computer vision and visual sensors including time-of-flight range imaging sensors. Michael along with Psychologist, John Perrone, is a recipient of an MBIE Smart Ideas grant on the development of a biologically based monocular visual sensor for autonomous navigation in robotics. It is insights gained from this research that inspire the proposed talk.

Michael Mayo - University of Waikato

Dr Michael Mayo works in the Department of Computer Science at University of Waikato. He is interested in the intersection of AI, machine learning, metaheuristic optimisation algorithms, and medical/health technology.

Michael Winikoff - University of Victoria

Michael Winikoff is full professor in the School of Information Management at Victoria University of Wellington, New Zealand. He is known for his work on engineering aspects of autonomous systems, including the Prometheus methodology. More recently he has been working on issues relating to trust in autonomous systems, including verification and explanation. Michael is on the IFAAMAS board of directors. He is on the editorial board of the Journal of Autonomous Agents and Multi-Agent Systems, and was programme co-chair and general co-chair for the conference on Autonomous Agents and Multi-Agent Systems in 2012 and 2017 respectively.

Michael Witbrock - University of Auckland

Michael Witbrock is a full professor of computer science at The University of Auckland (UoA) in New Zealand, building a research group, the Broad AI Lab. Michael has a PhD in Computer Science from Carnegie Mellon University and a BSc Hons in Psychology from Otago University. Before coming to UoA, he led Learning and Reasoning research within IBM Research AI at IBM’s Thomas J Watson Research Center in upstate New York. His current research goals involve the development and use of quasi-logical systems that can reason broadly, retaining approximations of the formal properties of logic while adding the learnability and flexibility distributed representations, and have the full representational power of natural languages. Prof. Witbrock is the author of numerous publications. Michael is also very interested in entrepreneurship and entrepreneurship around AI and for social good, and in the social and economic outcomes of advances in AI.

Mike Barley - University of Auckland

I was born in Denver, Colorado and after many detours went to San Diego for primary and intermediate schooling. I attended Central High School in London and did my undergraduate work at the University of California at San Diego. I received an MSc in Cybernetics from Brunel University in England and my PhD in Computer Science from Rutgers University in the US. I worked for the Burroughs Corporation in the UK for most of the '70s, and for the Boeing Company in Seattle before coming to the University of Auckland in 1997.

Patricia Riddle - University of Auckland

I work in both Artificial Intelligence and Machine Learning. My work in Artificial Intelligence is specifically in search, problem solving, problem reformulation and planning. I also do research in Machine Learning (over the years publishing in many of the fields in Machine Learning). I have supervised 12 PhD students to completion. I currently supervise 9 PhD students who work in a wide variety of areas. I co-supervise them with Yun Sing Koh, Georgy Gimel'farb, Jim Warren, Joerg Wicker, and Michael Witbrock. In addition I work in problem reformulation, search, and planning, with a wide range of international collaborators along with Michael Barley One of our recent papers won the "Honourable Mention" at AAAI 2020. We are planning to continue this work and hope to have an improved problem solver for the next International Planning Competition.

Paul Geertsema - University of Auckland

Paul is a senior lecturer at the University of Auckland in the Department of Accounting and Finance. Paul's research interests include return predictability, empirical asset pricing and the application of machine learning to problems in finance. Prior to his return to academia, Paul worked at Barclays Capital as a derivatives trader in Hong Kong and as a sell-side research analyst in London. Before that he held positions at Credit Suisse, Citibank and Audit New Zealand. Paul holds a Bachelor of Accounting degree from Stellenbosch University, a B.Sc. Computer Science degree from the University of Auckland, an MBA from London Business School, a Master of Management (Economics) from Massey University and a PhD in Finance from the University of Auckland. He is a member of Chartered Accountants Australia and New Zealand. Paul is the founding director of North Shore Consulting Limited, a boutique consulting firm providing solutions at the intersection of finance and technology.

Qi Chen - University of Victoria

Dr Qi Chen received the PhD degree in computer science in 2018 at Victoria University of Wellington (VUW). Since 2014, she has joined the Evolutionary Computation Research Group at VUW. Currently, she is a Lecturer in Artificial Intelligent in School of Engineering and Computer Science at VUW. Qi's current research mainly focuses on genetic programming for symbolic regression. Her research interests include machine learning, evolutionary computation, feature selection, feature construction, transfer learning, domain adaptation and statistical learning theory. She serves as a reviewer of international conferences, and international journals including IEEE Transactions on Evolutionary Computation and IEEE Transactions on Cybernetics.

Te Taka Keegan - University of Waikato

Te Taka received a Diploma in Computer Engineering from CIT (Wellington) in 1987. He spent six years working as a hardware engineer for Datacom and Digital before returning to Waikato and Waikato University. He received a BA through the Te Tohu Paetahi stream (Māori immersion) and in 1996 was awarded an MA having completed a thesis on traditional navigation. Te Taka worked with the Māori Department and then in 1997 switched to the Computer Science Department. He completed a PhD in 2007, titled Indigenous Language Usage in a Digital Library: He Hautoa Kia Ora Tonu Ai. 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.

Thomas Li - University of Canterbury

Thomas Li is a Lecturer in Statistics and Data Science at University of Canterbury (UC), School of Mathematics and Statistics. His current research areas involve image processing and classification, phylogenetic trees, classification trees, and deep learning applications. He currently leads the UC Spatial And Image Learning (SAIL) group, working on research in collaboration with NZ Transport Agency, Christchurch City Council, Christchurch Airport and Stats NZ. Thomas completed his PhD research at The Australian National University, in the Department of Applied Mathematics, he worked on image processing algorithms for Computed Tomography. The outcome of his PhD research improved the signal to noise properties. He has published papers in highly ranked international peer reviewed journals, presentations at international conferences, and two US patent publications for which he was one of the inventors.

Varvara Vetrova - University of Canterbury

Dr. Varvara Vetrova is a Senior Lecturer in the School of Mathematics and Statistics at University of Canterbury. Her research interests revolve around applied machine learning and deep learning in the environmental domain. Currently, she is a part of the research team in the MBIE-funded environmental data science initiative - TAIAO. Specifically, she is researching methods for anomalous climate events prediction as part of the TAIAO project. Varvara received her Ph.D. at the University of Waikato in 2016. Her Ph.D. was focused on methods for seasonal hydroclimatological forecasting. Prior to coming to UC, Varvara worked in Landcare Research from 2014 to 2016.

Wai Yeap - AUT

Professor Yeap is the Director for the Centre for AI Research at AUT. His research goal is to develop a computational theory of the mind.

Xiaoying Gao - University of Victoria

Dr Xiaoying Gao got her BE and ME from China in 1990 and 1992, and received a PhD from the University of Melbourne, Australia in 2000. She has been working at Victoria University of Wellington, New Zealand since 2000. Her main research projects are in the area of Web Intelligence and Text Mining. She has over 80 papers published in international journals and conferences, and has supervised 10 PhD and Masters research students to successful completion. She has been a member of the program committee of about 45 international conferences, a reviewer for more than 10 international journals, the publicity chair for AI2018, and an industry co-chair for CEC 2019.

Yi Mei - University of Victoria

Dr. Yi Mei received the BSc and PhD degrees from the University of Science and Technology of China, Hefei, China, in 2005 and 2010. He is currently a Senior Lecturer at the School of Engineering and Computer Science, Victoria University of Wellington. His research interests include evolutionary scheduling and combinatorial optimisation, machine learning, genetic programming, and hyper-heuristics. He is a recipient of the Victoria University of Wellington Early Research Excellence Award 2018. He has over 100 fully referred publications, including the top journals in EC and Operations Research such as IEEE TEVC, IEEE TCYB, Evolutionary Computation Journal, European Journal of Operational Research, ACM Transactions on Mathematical Software. He serves as a Vice-Chair of the IEEE CIS Emergent Technologies Technical Committee, and a member of the Intelligent Systems Applications Technical Committee. He is an Editorial Board Member/Associate Editor of three International Journals, and a guest editor of a special issue of the Genetic Programming Evolvable Machine journal. He serves as a reviewer of over 30 international journals. He is a Senior Member of IEEE.

Yun Sing Koh - University of Auckland

Dr Yun Sing Koh is a machine learning researcher at the School of Computer Science, The University of Auckland, New Zealand. Her research is in the area of machine learning. Within the broad research realm, she is currently focusing on three strands of research: data stream mining, lifelong and transfer learning, and pattern mining.

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