TWTV: An interview with this year's Women in AI finalists

Dr Mahla Nejati

Research Fellow at the Centre for Automation and Robotic Engineering Science (CARES), University of Auckland

Mahla completed her PhD in computer system engineering at the University of Auckland. She is working as a research fellow at the CARES robotics team. She was selected as a finalist for the 2022 Aus-NZ Women in AI awards in the AI in Agribusiness category.
Her expertise lies in designing the vision system for orchard robots. Her goal is to change the male-dominant environment in the robotics field by encouraging young girls to contribute to this field and assisting them in their education journey.
She is currently working on the vision system of a tomato monitoring robot, vineyard pruner and blueberry harvester, as well as teaching robotic courses and supervising students in this field.

Rachel Kelly

Co-Chief Executive Officer, Taylored Technologies

Rachel Kelly MSc(Hons) is an ex-scientist, strategist, high-tech product developer, and commercialisation professional who has spent the last 20 years in the science and technology sector. 

Prior to returning to New Zealand in 2014, Rachel was in California working for a Fortune 150 biotech / high-tech manufacturing company where she led, managed and grew multi-million-dollar business units within the USA, South East Asia, Central Asia, Middle East, and Africa. 

She is co-CEO of New Zealand biotech startup, Taylored Technologies, leveraging advanced technologies to discover and harness the boundaries of human potential and creating the world's first human instruction manual. They deliver the learnings through Taylored Health & Performance, a health facility based in the Waikato which also offers executive programs and diagnostics across New Zealand and APAC.

Rachel is currently an appointed board director at Callaghan Innovation, New Zealand's innovation agency and most recently, a finalist in the 2022 Women in AI awards, an event recognising female contributions to the development of artificial intelligence (AI) across Australia and New Zealand.

Rachel is a co-founder of the Waikato technology cluster, former Deputy Chair of NZTech, former elected member of the New Zealand Artificial Intelligence (AI) Forum Executive Council and former Ministerial Advisor on the Digital Council of Aotearoa New Zealand. Rachel has previously worked with award-winning and innovative tech startups including CoHired and Nyriad, and was Chief Product Officer of Enterprise Security at Gallagher NZ.

Dr Yun Sing Koh

Associate Professor, School of Computer Science, The University of Auckland

Dr Yun Sing Koh is an associate professor at the School of Computer Science, The University of Auckland. Her main research area is Artificial Intelligence (AI) and Machine Learning (ML). Specifically, she focuses on three major research strands: data stream mining, continual learning and adaptation, and anomaly detection. She is passionate about using machine learning for social good, and her research has been applied to interdisciplinary applications in environment and health domains. To date, she has published 100+ peer-reviewed publications in top conferences and journals, including IJCAI, IEEE ICDE, IEEE ICDM, Machine Learning Journal and Journal of Artificial Intelligence. She has been active in the research community, including serving as the General Co-Chair at the IEEE International Conference on Data Mining 2021, Workshop Co-Chair at the ECML 2021, Program Co-Chair of the Australasian Data Mining Conference 2018 and as the Workshop CO-Chair for the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining.

Stefanie Zollmann

Associate Professor, Computer Science, University of Otago

Stefanie Zollmann is an Associate Professor for Computer Science at the University of Otago in New Zealand. She is co-leading the Visual Computing Otago research group. Before starting at Otago in 2016, she worked as a senior developer at Animation Research Ltd on eXtended Reality visualization, computer graphics and computer-vision-based tracking technology for sports broadcasting. She also worked for Daimler and Graz University of Technology. Her main research is in the field of Visual Computing, which describes the combination of traditional Computer Graphics, Computer Vision, Machine Learning, Visualization and Human-Computer-Interaction. Her research focus is on eXtended Reality (XR) for sports and media, visualization techniques for Augmented Reality and novel methods for capturing content for immersive experiences. 

Karla Taboada

Data Scientist Leader, Auckland Transport

Karla Taboada is a Data Science & AI specialist, with a master and PhD in engineering from Waseda University, Japan. She has over 15 years of international working experience in Latin America, Japan, Canada and New Zealand among others. Her expertise includes strategic planning for Data Science adoption, building advanced data analytics platforms, delivering value for organizations and people through data science products.

She is currently leading the AI journey and its responsible implementation at Auckland Transport in New Zealand.

In 2017, she founded Domitila Technologies with a mission to leverage AI literacy for everyone, starting with children and youth. Her goals are to develop AI talent globally and empower everyone to apply AI for social good.

Madeline Newman

Executive Director, AI Forum

Madeline has extensive experience in strategy, transformational change and helping people to see the potential that innovative technologies bring and is excited to join the AI Forum of New Zealand as Executive Director.

Originally from New Zealand, Madeline has been working with AI and Tech in mental health, financial services and regulation spaces in the UK, where she helped to shape and deliver the Financial Conduct Authority’s internationally renowned RegTech innovation programme. Most recently she was Head of Innovation and Product for a science based digital mental health service. She brings new thinking and international connections to our AI community.