Dana Rezazadegan

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Personal profile


Dana is a Post-doctoral Research Fellow with the Centre for Health Informatics (CHI) at the Australian Institute of Health Innovation, Macquarie University. She is currently working on using artificial intelligence to automate documentation and diagnosis for helping doctors.

She got her Ph.D. from Queensland University of Technology (QUT). Her thesis aimed to expand the robot’s understanding of ongoing and future human actions to assist the human in assembling tasks. She developed deep learning methods based on CNN and LSTM for human action recognition and prediction. Prior to joining the Queensland University of Technology, her research mainly focused on trajectory tracking control of mobile robots such as AUVs.

Research interests

Robotic vision, Deep learning, Machine learning, Autonomous systems, Human-robot collaboration

Education/Academic qualification

Robotics and autonomous systems, PhD, Queensland University of Technology


Electrical Engineering, BSc, MSc, Isfahan University of Technology


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Research Outputs 2013 2019

  • 5 Article
  • 3 Conference proceeding contribution
  • 2 Conference paper

A network model of activities in primary care consultations

Kocaballi, A., Coiera, E., Tong, H. L., White, S. J., Quiroz, J., Rezazadegan, F., Willcock, S. & Laranjo da Silva, L., 1 Oct 2019, In : Journal of the American Medical Informatics Association : JAMIA. 26, 10, p. 1074-1082 9 p., ocz046.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Primary Health Care
Referral and Consultation
Medical History Taking
Natural Language Processing
Primary Care Physicians

The personalization of conversational agents in health care: systematic review

Kocaballi, A. B., Berkovsky, S., Quiroz, J. C., Laranjo, L., Tong, H. L., Rezazadegan, D., Briatore, A. & Coiera, E., 7 Nov 2019, In : Journal of Medical Internet Research. 21, 11, p. 1-15 15 p., e15360.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Delivery of Health Care
Digital Libraries

On Encoding Temporal Evolution for Real-time Action Prediction

Rezazadegan, F., Shirazi, S., Baktashmotlagh, M. & Davis, L. S., 2018, (Submitted) In : International Journal of Computer Vision. 7 p.

Research output: Contribution to journalArticleResearchpeer-review

Unsupervised learning
Railroad cars

Action recognition: from static datasets to moving robots

Rezazadegan, F., Shirazi, S., Upcrofit, B. & Milford, M., 21 Jul 2017, ICRA 2017 - IEEE International Conference on Robotics and Automation. Institute of Electrical and Electronics Engineers (IEEE), p. 3185-3191 7 p. 7989361

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Computer vision

A real-time action prediction framework by encoding temporal evolution

Rezazadegan, F., Shirazi, S. & Davis, L. S., 2017, In : arXiv.org e-Print archive. 9 p.

Research output: Contribution to journalConference paperResearchpeer-review

Unsupervised learning
Real time systems
Railroad cars