Professor Jeffrey Soar
| Name | Jeffrey Soar |
|---|---|
| Position | Co-Head of School (Business) |
| Section | School of Business |
| Office | A520 |
| Location | Springfield Campus |
| Phone | +61 7 3470 4831 |
| Extension | 4831 |
| Qualifications | BA(Hons) Monash , GDipEd HawthorneInstEd , GDipCommDataProc RMIT , MEd La Trobe , PhD NSWUT |
| Languages |
French (non accredited translator)
|
Fields of Research (FoR)
-
Public Health and Health Services not elsewhere classified
( 111799)
-
Information Systems not elsewhere classified
( 080699)
Research interests
Professor Soar has over 150 peer-reviewed publications as well as other papers, posters, abstracts and commissioned reports to governments; he has given over 40 invited key-note addresses at national and international events; and has attracted grants and commissions to support over $10M in research.
His research interests include:
- smart homes and intelligent assistive technologies
- smart ageing & independent living
- e-health, aged & community care informatics,
- technology and economic development
- aged care leadership and innovation
Professional memberships
Fellow of the Australian Computer Society
Fellow of the Australasian College of Health Informatics
USQ Research affiliations
-
Institute for Resilient Regions (IRR)
-
Centre for Health Sciences Research (CHSR)
-
Australian Centre for Sustainable Business and Development (ACSBD)
-
Australian Digital Futures Institute (ADFI)
Currently teaching courses/programs
Post-graduate research supervision, current student research topics include:
- e-government
- e-banking
- e-health
- e-learning
- technology and economic development
- eprocurement and economic development
- home telehealth for chronic illness support
- hospital avoidance and connected communities of care
- multi-media to support Aboriginal and Torres Strait Islander people's health
- ehealth development
Teaching experience(Tertiary)
20 Years
Teaching experience(Other)
5 Years
Administrative responsibilities
Personal Chair Human-Centred Technology
Research most recent
recent papers can be found at:
https://eprints.usq.edu.au/view/uniqueauthor/
Research most notable
Professor Soar's most notable research outcomes include:
- establishing the Queensland Smart Home Initiative in 2006, and
- building the SAIL (Smart Ageing & Independent Living) research consortium.
SAIL will develop, through research, pathways to adoption of ehealth in home and community settings - home telecare, telehealth and intelligent assistive technologies.
Its role is in attracting funds for its collaborative research program through grant writing, philanthropy, awareness-raising and networking.
Publications in ePrints
Ramakrishnan, Muralidharan
and Shrestha, Anup
ORCID: https://orcid.org/0000-0002-2952-0072 and Soar, Jeffrey
ORCID: https://orcid.org/0000-0002-4964-7556
(2021)
Innovation Centric Knowledge Commons—A Systematic
Literature Review and Conceptual Model.
Journal of Open Innovation: Technology, Market, and Complexity, 7 (1):35.
pp. 1-19.
ISSN 2199-8531
Yusif, Salifu
and Hafeez-Baig, Abdul and Soar, Jeffrey
ORCID: https://orcid.org/0000-0002-4964-7556
(2020)
A model for evaluating eHealth preparedness – a case study approach.
Transforming Government: People, Process and Policy, 14 (3).
pp. 561-587.
ISSN 1750-6166
Yusif, Salifu
and Hafeez-Baig, Abdul and Soar, Jeffrey
ORCID: https://orcid.org/0000-0002-4964-7556
(2020)
An Exploratory Study of the Readiness of Public Healthcare Facilities in Developing Countries to Adopt Health Information Technology (HIT)/e-Health: the Case of Ghana.
Journal of Healthcare Informatics Research, 4 (2).
pp. 189-214.
ISSN 2509-4971
Li, Yuan
and Li, Yutong and Wang, Yan and Ma, Guodong and Liu, Xinsheng and Li, Yonghong and Soar, Jeffrey
ORCID: https://orcid.org/0000-0002-4964-7556
(2020)
Application of zeolitic imidazolate frameworks (ZIF-8)/ionic liquid composites modified nano-carbon paste electrode as sensor for electroanalytical sensing of 1-hydroxypyrene.
Microchemical Journal, 159:105433.
pp. 1-7.
ISSN 0026-265X
Bargshady, Ghazal
ORCID: https://orcid.org/0000-0002-2557-7928
and Zhou, Xujuan and Deo, Ravinesh C.
ORCID: https://orcid.org/0000-0002-2290-6749 and Soar, Jeffery
ORCID: https://orcid.org/0000-0002-4964-7556 and Whittaker, Frank and Wang, Hua
(2020)
Enhanced deep learning algorithm development to detect pain intensity from facial expression images.
Expert Systems with Applications, 149 (Article 113305).
ISSN 0957-4174