
PhD (Deakin University), Graduate Certificate in Education (Queensland University of Technology), Bachelor of Information Technology (1st class Honours) (Queensland University of Technology)
A/Prof. Tjondronegoro founded and leads QUT Mobile Innovation Lab since 2010, which focuses on research, teaching, and industry engagement in mobile and multimedia computing. The team was nominee of the Vice Chancellor's Award for Excellence in 2015. He has lead the mobile research and development for three Cooperative Research Centres (CRCs): CRC Smart Services (smart video optimisation for mobile and multi-channel delivery), CRC Rail Innovation (mobile technologies for delivering real-time transit information and mobile payment), and CRC Young and Well (mobile music tool for mood journey). Since 2009, he has been actively collaborating with cross-disciplinary researchers to design, develop, and evaluate mobile eHealth applications for promoting women wellness after cancer, fostering motivations for perinatal mental health, and promoting responsible drinking. His research interest is bringing multimodal data (image, sound, video, and text) “out of the box” to support intuitive and engaging interactions through mobile and wearable devices and embedded sensors in the environment. He has published more than 120 papers in multimedia computing, mobile computing, and human-computer interactions fields, including in T-MM, T-AC, JASIS, IVC, MTAP, and TOMM journals, and at A* conferences such as ACM MM conference proceedings. He has written two edited books in the field of mobile multimedia. Research discipline: Information Systems (Service Sciences), Computer Science (Multimedia data analytics, machine learning, mobile health, Internet of Things) Research Themes:- Affective Computing: combine multimedia and sensor data for identifying human emotions and mood. Human response and reaction is important to understand their interest in video content, which can be leveraged to identify key segments/summaries from video. Also, it is important to understand the correlation between human mood and emotion. State-of-the-art sensors can be used to collect and analyse day-to-day human data
- Computational Health and Wellness: combine multimedia and signals data for quantifying health and wellness. We also apply information extraction and retrieval from Web and social media to aggregate health information.
- Pervasive User Interactions: deliver user-centered interactions with richly aggregated intelligent data to augment human’s intellect using the emerging user interface technologies, such as smartphones, smart watches, augmented reality (e.g. HoloLens) . deliver mobile video streaming that is acceptable for users in different contexts, particularly health and entertainment. The focus on users mean that we also aim to understand users’ factors in HCI and model the correlations with their acceptability, and perceived easy-to-use and usefulness. This also includes to use of “gamification” to improve user’s engagement.
- D. Anderson, A. McCarthy, P., Yates, M. Turner, N.King, L., Monterosso, M. Krishnasamy, K. White, S. Hall, D.Tjondronegoro. The Womens Wellness after Cancer Program. NHMRC Partnership $1,186,000
- 01/01/2014 to 31/12/2015: "TrISMA - Tracking Infrastructure for Social Media Analysis"ARC Linkage - Infrastructure Equipment and Facilities (LIEF) CIs: A Bruns, J Burgess, J Banks, D Tjondronegoro, A Dreiling, et al $710,000
- 01/07/2012 to 30/06/2016: "E-tools for wellbeing" CIs: Hides L, Kavanagh DJ, Young R, Shochet I, Tjondronegoro DW, Johnson D, Wolff R, Drennan J. Young and Well CRC Ltd $2,016,899
- 01/10/2008 to 30/06/2014: "Multi-Channel Content Delivery & Mobile Personalisation" CIs: Tjondronegoro, DW, Li, Y. Xu, Y. Smart Services CRC $657,879
- 01/01/2011 to 31/12/2013: "Leveraging Mobile Phone Technology to Influence Responsible Drinking Behaviours" CIs: Drennan JC, Connor JP, Kavanagh DJ, Tjondronegoro DW, Fry M-L, Previte JA, White AM. ARC Discovery Projects (DP110102848) $148,548
- 31/03/2006 to 30/06/2009 Investigation of a Dynamic Collaborative Framework for Multi-Modal Devices CIs: Roe, P, Tjondronegoro, D., Zhang, J. ARC Linkage Projects with APAI or APDI components $497,614
Additional information
Real World Engagement My commitment is to lead and work on cutting-edge research with cross-disciplinary disciplines (with Health, Creative Industry, Science and Engineering, and Law) while collaborating with industry partners, including: Fairfax Media, IceTV, Project Factory (as part of my engagement with the Smart Services CRC), Microsoft, Brisbane City Council, Regional Development Australia, Queensland Government (DSITIA). Consulting and Professional Education Training I have lead the research, design, and development of mobile apps for the Frog Field Guide (in collaboration with Australian Museum), Secret SLQ (in collaboration with Reading Room and SLQ); and these apps were finalist of Australian Mobile Awards 2012 in the Education category. We also built a gamified university orientation iPhone App for QUT. All apps are I am the current coordinator of Continuing Professional Education (CPE) courses in mobile computing series, courses in "Mobile Strategy", "Designing for Mobile", and "iOS and Windows Phone Software Development". He has a strong partnerships with Microsoft Australia in delivering Azure, Windows Phone, Windows 8, and Kinect 2.0 platforms.
- Type
- Editorial Role for an Academic Journal
- Reference year
- 2016
- Details
- Associate Editor of IEEE Access Journal
- Type
- Membership of Learned Societies
- Reference year
- 2016
- Details
- Senior Member of IEEE
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2015
- Details
- Silver medal in Grand Challenge track in ACM Multimedia - MM'10
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2013
- Details
- Reviewer of ARC grant proposals
- Type
- Editorial Role for an Academic Journal
- Reference year
- 2016
- Details
- Article Editor for Sage Open Journal
- Fitz-Walter, Z., Johnson, D., Wyeth, P., Tjondronegoro, D. & Scott-Parker, B. (2017). Driven to drive? Investigating the effect of gamification on learner driver behavior, perceived motivation and user experience. Computers in Human Behavior, 71, 586–595. https://eprints.qut.edu.au/99668
- Zhang, L., Tjondronegoro, D., Chandran, V. & Eggink, J. (2016). Towards robust automatic affective classification of images using facial expressions for practical applications. Multimedia Tools and Applications, 75(8), 4669–4695. https://eprints.qut.edu.au/84135
- Tjondronegoro, D., Drennan, J., Kavanagh, D., Zhao, E., White, A., Previte, J., Connor, J. & Fry, M. (2015). Designing a mobile social tool that moderates drinking. IEEE Pervasive Computing, 14(3), 62–69. https://eprints.qut.edu.au/86086
- Himawan, I., Song, W. & Tjondronegoro, D. (2017). Impact of automatic region-of-interest coding on perceived quality in mobile video. Multimedia Tools and Applications, 76(1), 785–813. https://eprints.qut.edu.au/90733
- Stoyanov, S., Hides, L., Kavanagh, D., Zelenko, O., Tjondronegoro, D. & Mani, M. (2015). Mobile App Rating Scale: A new tool for assessing the quality of health mobile apps. JMIR mHealth and uHealth, 3(1), 1–9. https://eprints.qut.edu.au/84696
- Song, W. & Tjondronegoro, D. (2014). Acceptability-based QoE models for mobile video. IEEE Transactions on Multimedia, 16(3), 738–750. https://eprints.qut.edu.au/66621
- Zhang, L., Tjondronegoro, D. & Chandran, V. (2014). Facial expression recognition experiments with data from television broadcasts and the World Wide Web. Image and Vision Computing, 32(2), 107–119. https://eprints.qut.edu.au/67090
- Zhang, L., Tjondronegoro, D. & Chandran, V. (2014). Random Gabor based templates for facial expression recognition in images with facial occlusion. Neurocomputing, 145, 451–464. https://eprints.qut.edu.au/71005
- Zhang, L., Tjondronegoro, D. & Chandran, V. (2014). Representation of facial expression categories in continuous arousal-valence space: feature and correlation. Image and Vision Computing, 32(12), 1067–1079. https://eprints.qut.edu.au/77785
- Zhang, L. & Tjondronegoro, D. (2011). Facial expression recognition using facial movement features. IEEE Transactions on Affective Computing, 2(4), 219–229. https://eprints.qut.edu.au/43787
- Title
- Establishing Advanced Networks for Air Quality Sensing and Analyses
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP160100051
- Start year
- 2017
- Keywords
- Title
- Clinical Trial: The Women's Wellness after Cancer Program
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- 1056856
- Start year
- 2013
- Keywords
- Cancer; Health Behaviours; Self-Management; Telemedicine; Wellbeing
- Title
- Leveraging Mobile Phone Technology to Influence Responsible Drinking Behaviours
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP110102848
- Start year
- 2011
- Keywords
- Social Marketing; Women's Health; Responsible Alcohol Drinking
- Design Guidelines for Designing Effective Mobile Pedestrian Navigation Systems (2016)
- Influencing Public Transport Passenger Experiences via Mobile Social Services (2016)
- Achievement Unlocked: Investigating the Design of Effective Gamification Experiences for Mobile Applications and Devices (2015)
- Robust Face Clustering for Real-World Data (2015)
- Detecting News Topics from Microblogs Using Sequential Pattern Mining (2014)
- Towards Pose-Robust Face Recognition on Video (2014)
- Towards Spontaneous Facial Expression Recognition in Real-World Video (2012)
- User-Driven Quality of Experience Modelling for Mobile Video Optimisation (2012)
- Multitasking, Cognitive Coordination and Cognitive Shifts During Web Searching (2010)
- Ontology Based Image Annotation (2010)