I lead the multi-disciplinary Human Centred Technology Research Cluster at the University of Sydney, Australia.
My research is in the areas of Artificial Intelligence in Education (AIED), Ubiquitous Computing (Ubicomp) and Human Computer Interaction (HCI). A core driver has been to create systems that enable people to harness their personal data for lifelong and life-wide learning. My research creates systems and interfaces for user models that people can scrutinise, to really see, understand and control their personal data and its use. This is core to people managing privacy and use of their data. In learning contexts, interfaces onto learning data, Open Learner Models (OLM), provide a new way for people to harness data to manage their learning. This is because it suppose metacognitive processes like self-monitoring, reflection and planning, closely related to self-regulation in lifelong learning for important areas of health and wellness. My research is based on rich collaborations with researchers in diverse areas, such as nutrition, physical activity, psychology, medical informatics and ehealth.
Within Sydney University, I belong to Charles Perkins Centre Nodes, Active Ageing, Digital Health Information Network, Health literacy chronic disease network and Wireless wellbeing and personalised health and the Advanced Technology for Education group Centre for Research on Learning and Innovation. Other collaborations include: Digital Health Collaborative Research Centre.
PhD in Computer Science, 1999
University of Sydney
20 - 23 Nov 2022, General Chair (with Craig Anslow) Interactive Surfaces and Spaces (ISS 2022), hybrid in Victoria University of Wellington, New Zealand
13 Sep 2022, Program Committee and speaker: NUTEL - Nudges in Technology-Enhanced Learning, in conjunction with ECTEL 2022.
18 - 21 Jul, 2022, Invited speaker: Temporal Aspects in User Modeling, Research Workshop of the Israel Science Foundation
17 - 31 Jul 2022, AIED 2022: The 23rd International Conference on Artificial Intelligence in Education (AIED2022) hybrid in Durham University, UK.
21-26 June, 2021, User Modeling, Adaptation and Personalization, UMAP 2021, Utrecht/Virtual, Netherlands.
14-18 Jun, 2021, Invited keynote at the 2021 conference on Artificial Intelligence in Education, AIED 2021, Utrecht/Virtual, Netherlands, Theme: Mind the Gap: AIED for Equity and Inclusion.
6–11 Jun, 2021, Dagstuhl Seminar Transparency by Design. Organizers: Casey Dugan, IBM Research – Cambridge, US; Judy Kay, The University of Sydney, AU; Tsvi Kuflik, Haifa University, IL; Michael Rovatsos, University of Edinburgh, GB.
8-13 May, 2021, CHI 2021
14-19 Mar, 2021, Invited keynote at ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR’21) The Case for Scrutable, Personal, Long-Term User Models for Information Retrieval, Abstract
13-20 Mar, 2021 SIGCSE Technical Symposium – Alan Fekete, Judy Kay and Uwe Röhm will present A Data-centric Computing Curriculum for a Data Science Major
4 Mar, 2021, Sarah Howard, Simon Buckingham Shum, Judy Kay ACS Panel discussion: How AI transforms the learning experience
8-9 Feb, 2021, Invited speaker at BIOTech Futures Challenge Virtual Symposium for high school students, Topic: Human-centred AI for human health
21-22 May, 2020: Keynote speaker at CHI Down Under 2020, Australia and New Zealand virtual CHI event, 21-22 May 2020 2020, Title “Learning to see, with uncertainty: lessons, reflections and vision for our community”.
7 Aug, 2019: Invited speaker at Emerging Digital Technologies & Ergonomics in Health, Ageing & Education, Human Factors and Ergonomics Society of Australia (HFESA) Professional Development Seminar.
This section is under construction
My current projects are:
Scrutable user modelling. This has been a core focus of my research. Key publications:
1994: UMUAI paper on accretion/resolution architecture: Kay, Judy. “The um toolkit for cooperative user modelling.” User Modeling and User-Adapted Interaction 4, no. 3 (1994): 149-196. | pdf
1998: Thesis - my first use of term “scrutable”: A scrutable user modelling shell for user- adapted interaction.
2013: Summary of first fifteen years work: Kay, Judy, and Bob Kummerfeld. “Creating personalized systems that people can scrutinize and control: Drivers, principles and experience.” ACM Transactions on Interactive Intelligent Systems (TiiS) 2, no. 4 (2013): 1-42. | pdf
Lifelong and lifewide user modelling: creating interfaces and infrastructure for people to control and harness their personal long term data for their learning.
Dashboards for long term personal data.
Tackling truth decay by creating personalised interfaces that enable people make judge the trustworthiness of online science news.
E-textbook of the future.
Ambient appliances and personal sensors to help people tackle long term personal goals for health and wellness.
Online modules to support communication in oncology by the TRIO, clinician-patient-carer.
Editor-in-chief (2012 -) IJAIED: International Journal of Artificial Intelligence in Education | Springer site | IAIED | Submissions and reviews | ERIC | May 2020 Citescore 9.1, rank 9⁄1254 Education, 7⁄128 Computational Theory and Maths
Editorial Board (2000 - ): User Modeling and User-Adapted Interaction: The Journal of Personalization Research (UMUAI) | submissions | SCImago HCI
Management Committee (2012 -) Artificial Intelligence in Education Society (IAIED) | Facebook | management
Advisory Board (2014 - ) User Modeling (UM Inc) Roof Body for User Modeling and Personalization Conferences (UMAP)
Human-in-the-loop data analytics | DATA3506 Syllabus
Usability Engineering | COMP5427 Syllabus
Advanced research methods for HCI | INFO4994/5995 Syllabus | This reading unit for PhD and Honours thesis students covers recent papers illustrating diverse research methods for human computer interaction (HCI) from venues such as CHI, CSCW, UIST and IMWUT.
Problem Based Learning (PBL): Over several years, we established and refined the approach to teaching programming fundamentals along with a very broad problem-based skills. If you are considering this approach you may find the resources below useful.
Kay, J., Barg, M., Fekete, A., Greening, T., Hollands, O., Kingston, J. H., & Crawford, K. (2000). Problem-based learning for foundation computer science courses. Computer Science Education, 10(2), 109-128. DOI | Tech Report
Student resources: 80 page student resources
Curriculum mapping: The CUSP system was created to tackle the challenge of designing a university curriculum that builds generic skills such as communication. This has been commercialised as u-improve and published in the PhD work of Richard Gluga.
Building group work skills: This aspect of my teaching has been core to several HCI and AIED reseach projects. This is reflected in the publications by PhD alumni Andrew Clayphan, Roberto Martinez Maldonado, undergraduate reseach by Kim Upton and Dilhan Perera.
Current research students:
Kim Bente - Uncertainty quantification and communication in environmental modelling (Co-supervisor: Sally Cripps funded by ARC Training Centre in Data Analytics for Resources and Environments (DARE) Centre
I am also co-supervising:
Alan Yung - Exploring support for oncologists with the data that drives decisions in diagnosis and treatments (with: Tim Shaw)
Also see alumni and their theses.