Professor Daniel Johnson


Publications by classification


Technology
Studies In Human Society
Environmental Sciences
Information And Computing Sciences
Engineering
Built Environment And Design
Studies In Creative Arts And Writing
Psychology And Cognitive Sciences
Language, Communication And Culture
Commerce, Management, Tourism And Services
Education
Medical And Health Sciences

Publications by year


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Director and Professor, Games Research and Interaction Design Lab

PhD (University of Queensland)

Research discipline: Computer Science Dr. Daniel Johnson leads the QUT Games Research and Interaction Design Lab and is a Professor in the Bachelor of Games and Interactive Entertainment.  He has completed Bachelors and Honours degrees in Psychology, a Graduate Certificate in Higher Education and a doctorate on the psychology of human-computer interactions and video games. Daniel has also worked in the games industry with companies such as NextGenVideos and The Binary Mill. His research interests include motivations for videogame play, the player experience, the impact of videogames on wellbeing, and gamification. He worked as a post-doctoral fellow at the University of Cambridge working for the Engineering Design Centre and remains an Affiliate of the Cambridge University Well-being Institute. Over the past decade, Daniel has undertaken consultancies exploring usability, user experience and design issues in entertainment and non-leisure software.

Projects

Additional information

Title
Engaging Augmented Reality on 3D Head Up Displays to Reduce Risky Driving
Primary fund type
CAT 1 - Australian Competitive Grant
Project ID
LP150100979
Start year
2016
Keywords
Title
Make and Connect: Enabling People to Connect through their Things
Primary fund type
CAT 1 - Australian Competitive Grant
Project ID
DP150104001
Start year
2015
Keywords
Human-Computer Interaction; Participatory Design; User-centred Design
Title
Visual Analytics for Next Generation Sequencing
Primary fund type
CAT 1 - Australian Competitive Grant
Project ID
LP140100574
Start year
2015
Keywords
Visual Analytics; Bioinformatics - Next Generation Sequencing; Big Data - Large Scale Visualisation