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Jen Jen Chung is an Associate Professor in Mechatronics within the School of Electrical Engineering and Computer Science at The University of Queensland. Her current research interests include perception, planning and learning for robotic mobile manipulation, algorithms for robot navigation through human crowds, informative path planning and adaptive sampling. Prior to working at UQ, Jen Jen was a Senior Researcher in the Autonomous Systems Lab (ASL) at ETH Zürich from 2018-2022 and was a Postdoctoral Scholar at Oregon State University researching multiagent learning methods from 2014-2017. She completed her Ph.D. on information-based exploration-exploitation strategies for autonomous soaring platforms at the Australian Centre for Field Robotics in the University of Sydney. She received her Ph.D. (2014) and B.E. (2010) from the University of Sydney.

Dr Chelsea Dobbins is a Senior Lecturer within the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland. Before relocating to Australia, Dr Dobbins was a full-time continuing Senior Lecturer within the Department of Computer Science at Liverpool John Moores University (LJMU) in the UK (2013-2018). She has a background in Software Engineering and expertise in Digital Signal Processing, Applied Machine Learning and Human-Computer Interaction. Her research focuses on the detection of emotion using smartphones/wearable sensors and personal informatics. This includes areas such as lifelogging, affective computing, pervasive computing, digital health, human computer interaction, machine learning, mobile computing, mobile/wearable sensors, human digital memories, signal processing, and physiological computing. Her research has been supported by the UK's Engineering and Physical Sciences Research Council (EPSRC) for work related to developing a mobile lifelogging platform to detect negative emotions during real-life driving. In 2016 she received an ACM Computing Review Notable Article award for work related to mining multivariate temporal smart mobile data.

Dr. Azadeh Ghari-Neiat is a Senior Lecturer in Software Engineering at the University of Queensland. Her research interests lie at the intersection of the Internet of Things (IoT), Mobile Computing, Crowdsourcing, and Cybersecurity. Her work focuses on enhancing connectivity and security in modern computing environments through innovative crowdsourcing solutions. She completed her PhD in Computer Science from RMIT University in 2018. Prior to joining UQ, Dr. Ghari-Neiat held academic positions at Deakin University as a Senior Lecturer and at the University of Sydney as a postdoctoral research fellow and casual lecturer.

Dr. Glencross' research interests are in computer graphics, human computer interaction and the application of these areas to real industry problems.

Glencross is director for teaching and learning in the school of EECS and leads the Graphics and Visualisation theme in the Centre for Energy Data Innovation, where she directs research into tools and technologies to support decision making in the Energy sector. With a background in industry focused research, her work in computer graphics has been supported through industry contracts and research council funding. Her work has had commercial impacts across computer games, visual effects, displays, mobile phones and image-based capture technologies.

She previously led the technical product management of a Graphics Processor Unit at ARM Ltd (UK), the intellectual property for which is deployed in mobile phone handsets. Glencross co-founded two UK-based technology startups; as research director of Pismo Software, she led innovation in automated 3D content creation pipelines for Virtual Reality interior design for Yulio Inc. As director for research at a smart heating company, Glencross led the research and development of an advanced intelligence heating system device.

She serves the computer graphics community as SIGGRAPH 2023 Emerging Technologies Chair. She is also member of the steering committee of the ACM PACM journals, and associate editor of the Computers & Graphics journal. She is recognised as a senior member of the ACM.

Dr Leah Henrickson is a Lecturer in Digital Media and Cultures at the University of Queensland. She is the author of Reading Computer-Generated Texts (Cambridge University Press, 2021) and other peer-reviewed articles about how we understand text generation systems and output, artificial intelligence, and digital media ecosystems. Dr Henrickson also studies digital storytelling for critical self-reflection, community building, and commercial benefit. She regularly supports projects and organisations in their digital storytelling efforts as consultant and advisor.

Dr Henrickson is especially keen to collaborate on projects involving digital methods and media, hermeneutics, histories of communications media, and unconventional text production and dissemination.

Dr Jessica Korte is passionate about the ways good technology can improve lives. To ensure technology is “good”, she advocates involving end users in the design process; especially when those people belong to “difficult” user groups - which usually translates to “minority” user groups. Her philosophy for technology design (and life in general) is that the needs of people who are disempowered or disabled by society should be considered first; everyone else will then benefit from technology that maximises usability. Her research areas include Human-Computer Interaction, Machine Learning, and Participatory & Collaborative Design.

Jessica was drawn to research by a desire to explore some of the ways technology and design can empower and support people from marginalised groups. She has worked with Deaf children and members of the Deaf community to create a technology design approach, and successfully organised and run international workshops on Pushing the Boundaries of Participatory Design, leading to the World’s Most Inclusive Distributed Participatory Design Project.

Jessica has recently been awarded a TAS DCRC Fellowship to create an Auslan Communication Technologies Pipeline, a modular, AI-based Auslan-in, Auslan-out system capable of recognising, processing and producing Auslan signing.

Jessica is currently looking to recruit research students with an interest in exploring topics in an Auslan context, including machine learning, natural language processing, chatbots, video GAN, or procedural animation.

Jacki Liddle is a research fellow and occupational therapist researching quality of life, participation and life transitions. She uses innovative technology, along with qualitative and quantitative research methods to investigate the needs and experiences of people living with neurological conditions (dementia, Parkinson's disease, stroke), older people and their caregivers. She has worked with a multi-disciplinary team co-designing technology with people living with dementia and their care partners to support communication. Currently, she is in a conjoint position with Princess Alexandra Hospital, supporting the development, conduct and application of research that improves outcomes for patients.

She has also been involved in developing technology to measure outcomes including lifespace, time use, and activity and role participation to help monitor and improve community outcomes. Dr Liddle's PhD focused on researching the experiences related to retirement from driving for older people, which led to the development of the CarFreeMe program to improve outcomes related to driving cessation. Versions of the program for older drivers, people living with dementia and people with traumatic brain injury have been developed and trialled.

Dr Moni holds a PhD in Artificial Intelligence & Data Science in 2014 from the University of Cambridge, UK followed by postdoctoral training at the University of New South Wales, University of Sydney Vice-chancellor fellowship, and Senior Data Scientist at the University of Oxford. Dr Moni then joined UQ in 2021. He also worked as an assistant professor and lecturer in two universities (PUST and JKKNIU) from 2007 to 2011. He is an Artificial Intelligence, Computer Vision & Machine learning, Digital Health Data Science, Health Informatics and Bioinformatics researcher developing interpretable and clinical applicable machine learning and deep learning models to increase the performance and transparency of AI-based automated decision-making systems.

His research interests include quantifying and extracting actionable knowledge from data to solve real-world problems and giving humans explainable AI models through feature visualisation and attribution methods. He has applied these techniques to various multi-disciplinary applications such as medical imaging including stroke MRI/fMRI imaging, real-time cancer imaging. He led and managed significant research programs in developing machine-learning, deep-learning and translational data science models, and software tools to aid the diagnosis and prediction of disease outcomes, particularly for hard-to-manage complex and chronic diseases. His research interest also includes developing Data Science, machine learning and deep learning algorithms, models and software tools utilising different types of data, especially medical images, neuroimaging (MRI, fMRI, Ultrasound, X-Ray), EEG, ECG, Bioinformatics, and secondary usage of routinely collected data.

• I am currently recruiting graduate students. Check out Available Projects for details. Open to both Domestic and International students.

Javad Pool is a Postdoctoral Research Fellow at The University of Queensland. He completed his PhD in Business Information Systems at UQ Business School in 2022, with a focus on data privacy and the effective use of information systems, specifically in the digital health context. By employing a combination of qualitative and quantitative research methodologies, Javad has conducted studies in a wide range of organizational and technological contexts, including healthcare, artificial intelligence, digital health, and social media. His work includes the development of inductive and theory-driven models, contributing to the existing body of knowledge on the effective use of information systems and health informatics research. Passionate about collaboration, Javad seeks to engage with diverse stakeholders, encompassing multidisciplinary researchers, industry professionals, and government partners, to advance research on information resilience and data protection practices. His research endeavors to better understand and address socio-technical challenges within information systems use, including data governance, privacy risks, cybersecurity, data breaches, data protection, misinformation, and responsible use of data.

Human-centred design of interactive systems

Stephen Viller is a researcher and educator in human-centred design methods, particularly applied to designing social, domestic and mobile computing technologies, and understanding how people's interactions in everyday settings inform the design of such technologies. He has over 20 years of experience in Computer Supported Cooperative Work (CSCW), Interaction Design, and Human-Computer Interaction (HCI) research, where he has focused on bridging disciplines and perspectives. He has concentrated on qualitative methods, particularly observational fieldwork, contextual interviews, diary studies and field trips, but also increasingly on more ‘designerly’ approaches such as cultural probes, low-fidelity prototypes, rapid prototyping and sketching.

Stephen is an Associate Professor and leader of the Human-Centred Computing discipline in the School of Electrical Engineering & Computer Science, and UQ's Theme Leader for the Digital Worlds and Disruptive Technologies theme in the QUEX Institute. From 2016-2019 he was the Director of Coursework Studies (Chair of T&L committee) and from 2011-2016 he was Program Director of the Bachelor of Multimedia Design and Master of Interaction Design. His publications span various interdisciplinary journals and conferences in HCI/CSCW and technology design. He has a BSc (Hons) Computation (UMIST), MSc Cognitive Science (Manchester) and PhD Computing (Lancaster).

Janet Wiles is a Professor in Human Centred Computing at the University of Queensland and leads the Future Technologies Thread of the ARC Centre of Excellence for the Dynamics of Language (CoEDL).

Her multidisciplinary team co-designs language technologies to support people living with dementia and their carers and social robots for applications in health, education, and neuroscience.

She received her PhD in computer science from the University of Sydney, and completed a postdoctoral fellowship in psychology. She has 30 years’ experience in research and teaching in machine learning, artificial intelligence, bio-inspired computation, complex systems, visualisation, language technologies and social robotics, leading teams that span engineering, humanities, social sciences and neuroscience. She currently teaches a cross disciplinary course ”Voyages in Language Technologies” that introduces computing students to the diversity of the worlds Indigenous and non-Indigenous languages, and state-of-the-art tools for deep learning and other analysis techniques for working with language data.

Featured projects

• Human-centred AI
• Florence communication technology
• For more on Human Centred Computing see the HCC projects page