Rhema is co-director and co-founder of the Centre for Social Data Analytics. She is a Professor of Health Economics at Auckland University of Technology and a Senior Research Fellow in the School of Economics at Singapore Management University. Rhema is widely published in Health and Development Economics and Applied Microeconomics. Rhema led the international research team that delivered the world-first Allegheny Family Screening Tool (a predictive risk model for child maltreatment) in 2016, and currently has a leading role on several other predictive analytics projects in the United States. She has a strong interest in implementing data-analytics solutions with agency partners that address entrenched social problems, like child maltreatment and homelessness. Rhema has previously worked as a policy analyst for the New Zealand Treasury and was a Harkness Fellow at Harvard Medical School in 2007/08. She earned her PhD in Economics from the University of Auckland.
Director of Communications
Aimee is responsible for communication of the Centre’s work to a range of audiences in channels ranging from social media to mainstream media and everything in between. Her role encompasses internal communications, website content and media relations for the Centre. Aimee’s previous roles include ministerial press secretary and communications manager for the Faculty of Business, Economics and Law at AUT. She has an LLB (Hons) from the The University of Waikato.
Senior Research Fellow
Matthew brings valuable experience in agency research as well as a strong publications record to his role at CSDA. After completing his PhD in Epidemiology and Population Health Sciences at the University of Wisconsin, Madison in 2010, Matthew spent four years working on the Survey of the Health of Wisconsin at the University of Wisconsin, Madison. Prior to joining CSDA, he was Research and Evaluation Section Chief for the Wisconsin Department of Children and Families (USA). His work at CSDA includes leading a study of protective factors of children and families at highest risk of adverse childhood experiences using data from an ongoing longitudinal study. Research projects utilising the New Zealand Integrated Data Infrastructure (a linked administrative dataset for researchers) are another focus of his work at the Centre.
Research Fellow (Economics)
Sophie's research interests are in Health Economics and her focus at CSDA is on New Zealand projects, frequently making use of the New Zealand Integrated Data Infrastructure (IDI), a large research database containing microdata about people and households. Sophie has previously worked as a Visiting Assistant Professor at the School of Economics and a Research Fellow in the Centre for Research on the Economics of Ageing, at the Singapore Management University. Sophie earned her PhD in Economics at the University of Auckland.
Diana Benavides Prado
Research Fellow (Data Science)
Diana has particular research and applied expertise in machine learning and data mining. She is currently completing her PhD at the University of Auckland, focusing on transfer and lifelong machine learning. Diana is part of the CSDA team working on the Allegheny Family Screening Tool (AFST), a predictive risk model for child maltreatment decision-making. On that project she has been focused on finding ways to optimise the accuracy and transparency of the tool. Diana completed her Master of Computer Engineering and Computer Science at the University of Los Andes in 2012.
Research Fellow (Data Science)
Since joining CSDA in May 2018, Katerina has been focusing on the centre’s predictive risk modelling for child welfare projects in Allegheny County, PA (USA). Prior to joining CSDA, Katerina spent almost four years as a postdoctoral researcher in Germany, at the Computational Biology and Data Mining Group at the Johannes Gutenberg University Mainz and the Institute of Molecular Biology. She has a PhD in Computer Science from the International Postgraduate School Jožef Stefan, Ljubljana, Slovenia (2012). The contributions of Katerina’s research are published and presented in several peer-reviewed journals and conferences/workshops in the field of numerical optimisation, machine learning, bioinformatics, engineering, systems biology and ecological modelling.
Chamari I. Kithulgoda
Research Fellow (Data Science)
Chamari’s research interests include data mining and machine learning, with a focus on data stream mining. At CSDA she is part of the team working on the Douglas County Decision Aide, a screening tool intended to enable earlier intervention to prevent adverse outcomes for children. Chamari recently submitted her PhD in Computer Science at AUT (“A Staged Approach to High Speed Classification in Concept Drifting Data Streams”). Chamari also has a Master of Science majoring in Financial Mathematics from the University of Moratuwa, Sri Lanka.
Megh brings experience using Big Data and Machine Learning for reporting, analysis and prediction to his work at CSDA. He is part of the team providing support to the Douglas County Decision Aide, a predictive risk modelling tool for Douglas County, CO (United States) that supports decision-making about incoming allegations of child maltreatment. Megh has a Masters in Data Science from the University of Auckland and has previously worked as a Software Engineer at Accenture.
US Project Manager
Emily is based in Chicago and - thanks to technology - works closely with the CSDA team in NZ. Emily provides a vital ‘on the ground’ presence for CSDA in the US, ensuring that existing projects are on track in terms of data, people and process. She also regularly shares CSDA’s work with interested groups and individuals around the US. Emily has previously worked at the US Department of Education and at the Allegheny County Department of Human Services, where she was Manager of External Partnerships in the Office of Data Analysis, Research and Evaluation. Emily has an MBA from Carnegie Mellon University, PA and strong interest in using data and analytics for social good.
Project Manager (US)
Allon works part-time for CSDA as a US-based project manager. His primary focus is managing the Centre’s child welfare predictive risk modelling research work in Douglas County, CO. Allon works closely with CSDA’s fulltime US project manager, international collaborators and the wider NZ-based CSDA team. Allon continues to work as a Regional Administrator for the Department of Children and Families in Connecticut (Region 3), a role he has held for seven years. He brings a wealth of Child Welfare domain experience to his role at CSDA. Since starting out as a front-line child protective services worker in 1996, Allon has accumulated more than 20 years of Child Welfare experience including work in operations, data analytics, quality improvement and evaluation. Allon has a Master of Social Work from the University Of Connecticut School Of Social Work (2002).
Trish looks after all of the Centre’s administration needs, from finance, contracts, travel, events and HR to supporting smooth day-to-day operations. Trish brings more than fifteen years’ of valuable experience in tertiary education sector administration to her role. Prior to joining CSDA she held an administration role in AUT’s School of Hospitality and Tourism.
Larissa has been part of CSDA since it launched in early 2016, balancing her role as research assistant with the final year of her Bachelor of Business in Economics and Market Insights*. Since graduating she has worked for CSDA fulltime, taking responsibility for managing the co-director’s diary and helping to keep the centre running smoothly by taking on numerous administration, communications and research tasks. Larissa is also gaining research experience by taking a lead project management role on one of CSDA’s current research projects - a workplace wellbeing survey.
*Market Insights is now called Marketing, Advertising, Retailing and Sales
Nic is completing his final semester of a Post-Graduate Bachelor of Business (Honours) in Economics at AUT and works at CSDA part time. He helps members of the CSDA team with a range of research-related tasks.
PhD Student and Research Assistant
Sahar has enrolled to complete a PhD in Economics (Algorithmic Fairness), supervised by Rhema Vaithianathan and Matt Walsh. She is also working as a lecturer in the School of Economics, teaching the Quantitative Foundation Skills paper. Sahar has a Bachelor of Science in Applied Mathematics from The University of Auckland, and a Master of Analytics (First Class Honours) from Auckland University of Technology. Sahar will also be assisting on the Learning Analytics project, analysing the data.
Ye (Zoe) Ye
PhD Student and Research Assistant
Ye (Zoe) is the recipient of a 2018 AUT Vice Chancellor’s Doctoral Scholarship. She has enrolled to complete a PhD in Economics supervised by Tim Maloney and Rhema Vaithianathan. She intends to complete an economic analysis of all possible changes to the NZ Superannuation that could increase its long-term fiscal sustainability. Zoe is also working as a Graduate Teaching Assistant in the School of Economics. Her previous degrees include a Master of Arts in Economics and a Master of Science in Mathematics, both from the Middle Tennessee State University. In the past Zoe has held actuarial and solvency management roles in government and in the insurance industry.
PhD Student and Research Assistant
Alex is the recipient of a 2018 AUT Vice-Chancellor's Doctoral Scholarship. He is completing a PhD supervised by Marilyn Waring (Professor of Public Policy, AUT) and Rhema Vaithianathan, investigating data sovereignty in New Zealand's NGO sector. Alex is also working as a research assistant at CSDA, where he is working alongside Rhema Vaithianathan and Tim Dare on their three-year project An Ethical Framework for Social Policy Applications of Predictive Analytics (which focuses on ethical data use).
Nan is a Senior Lecturer in the School of Economics at Auckland University of Technology. Her research areas include Productivity and Efficiency analysis, Predictive Risk Modelling, Applied Microeconomics, and Agricultural and Resource Economics. Nan has previously served as a consultant for several public and private sector agencies, such as Vodafone, Fonterra and the Auckland District Health Board. She gained her PhD in Economics from the University of Auckland, where she was the first to apply econometric techniques to evaluate the efficiency of New Zealand dairy farming.
Peer Ebbesen Skov
Peer Ebbesen Skov is a Lecturer in the School of Economics at Auckland University of Technology. He is also a Research Fellow at the Economic Policy Research Unit at University of Copenhagen and at New Zealand Public Finance at Victoria University of Wellington. Peer’s main research focus is on tax policy from an empirical perspective, and includes research into tax evasion and enforcement, tax avoidance, and the elasticity of tax bases. Peer has also published research in criminology and is currently working on projects including the effects of the minimum wage on youth unemployment and the link between experimental measures of altruism and real world charity donations. Peer received his PhD from the University of Copenhagen in 2014.
Lydia is a Lecturer in the School of Economics at Auckland University of Technology. Her research areas include Industrial Organisation, Econometrics and Applied Microeconomics. She is also working with the Productivity Commission on job creation dynamics and firm productivity estimation using Statistics New Zealand’s Longitudinal Business Database. She previously spent a year at Amazon.com in Seattle, USA and is interested in using large, micro-level datasets to study business-relevant topics. Lydia gained her PhD in Economics from the University of Minnesota in 2012.
Gail is a Professor at Auckland University of Technology and Director of the NZ Work Research Institute. She is widely published in the research areas of Labour Economics and Applied Microeconomics. She has considerable experience leading projects involving both academic and industry collaborations (with for instance the Department of Labour, the Blind Foundation, Careers NZ, United Nations Women, and Coca-Cola Amatil NZ). She also currently holds the post of Editor-in-Chief for New Zealand Economic Papers. Gail earned her PhD in Economics from the University of Auckland.
Oleksandr Fialko, Data Scientist, Qrious
(CSDA Research Fellow 2017-2018)
Oleksandr joined CSDA with a PhD in physics and a strong mathematics and computing background, keen to pursue a growing interest in data analytics and machine learning.
He saysCSDA provided an excellent opportunity to gain data science experience by working on important and useful applications of predictive analytics. Working under supportive and friendly management, and the chance to travel internationally as part of project work added to his enjoyment of the role.
Oleksandr says the skills he picked up at CSDA were useful in securing, and his new role:
“At CSDA I gained the ability to work with messy real life data and cutting edge machine learning models. I also came away with a deeper understanding of the ethical and moral responsibilities that are part of working with predictive analytics."
Nina Anchugina, Data Scientist, Bank of New Zealand
(CSDA Research Fellow, 2017-2018)
Nina joined CSDA with a PhD in mathematics and experience working with data, looking to get into the world of data science.
“At CSDA I gained practical skills that gave me a competitive advantage compared to many data scientists in industry. While having theoretical knowledge is important, there is nothing like working with real world applications,” says Nina.
“CSDA has a truly international profile. With projects in US, UK and South America, it brings together the best of consulting and academic research. I enjoyed working on challenging projects that address important social problems and appreciated the atmosphere of growth where I always felt encouraged to pursue and learn new methods to gain the best results.”
At CSDA Nina particularly enjoyed being part of projects from beginning to end, including engaging with stakeholders, shaping questions, getting the right data, engineering modelling data sets, building predictive models, evaluating and improving models, and visualizing data to tell a compelling story.
Nina says some of the most transferable skills she acquired at CSDA were the ability to use data ethically, to understand and account for bias and to work with partners in a transparent and collaborative way.