Dr Alireza Abbasi is the Director of Postgraduate Studies at the School of Engineering and IT at UNSW Canberra. His research aims to enhance better functioning and performance of complex socio-technical systems, which primarily lies in the emerging field of Social Computing, leveraging the capacity to collect and analyse data to reveal patterns of individual and group behaviour.
** Scholarships of $35,000 (AUD) are available for PhD students who achieved High Distinction (H1) in their undergraduate program and/or have completed a Masters by Research.
Research Student (PhD & Master by Research) Scholarships:
Several types of scholarships are available; however, admission and scholarship applications are highly competitive. A self-assessment tool is available to get a general feel for your competitiveness. You need to meet the English language requirements.
If you are eligible and interested in working on the following (or closely related) topics or keywords, please send me your CV, academic transcripts, the result of the self-assessment, and a research proposal: highlight research Motivation, Research problems, Research Objectives and Questions, a brief Review of the most relevant Literature, your proposed Methodology (discussing your proposed approach to answer the RQs including the type of data you need and how you will get them, techniques, etc.) and Expected Outcome.
For more information, please refer to the following links on how and when to apply for a research degree.
Research Topics:
- Developing methods for Future Technology Prediction
- Computational frameworks and algorithms for predicting the dynamics of socio-technical systems
- Harnessing Technological Advancement to enhance Community Wellbeing, including: Disaster Management, Public Health Promotion, Transport Management
- Analysing Dynamics of and on Multilayer Networks
- Identifying Influential Agents in Evolutionary Networks / Systems
- Mining and Analysing Social Networks for Business Applications
- Recommendation Systems for Social Media
- Developing Novel Techniques for Predicting Project Success
- Decision Making under Uncertainty
- Addressing challenges in Resource Levelling and Project Scheduling
- Information and Knowledge Management System for Project Control and Management
- Understanding Human Mobility Patterns
- Developing Models and Tools for Community Resilience
Research Keywords:
Network Science, Social Network Analysis, Social Computing, Link Prediction, Community Detection, Network Dynamics and Evolution; Collaboration and Coordination Management, Disaster and Emergency Management;
Future Technology Prediction; Social Media Analytics, Data Analytics, Recommendation Systems, Machine Learning, Data Mining, Topic Modelling, Text Mining, Natural Language Processing; Qualitative and Quantitative Research, Multidisciplinary Research, ICT for Development; Transportation Management, Internet of Things, Smart Cities; Research Evaluation, Informetrics, Scientometrics; Health Informatics;
Project Management, Project Success, Project Outcome, Project Complexity, Project Planning, Project Scheduling, Estimation, Program and Portfolio Management, Benefit Realisation, Risk Analysis and Management, Decision Making, Decision Analytics, Logistics and Supply Chain Management, Sustainability, Performance Management and Evaluation; Business Process Management.
Education:
- PhD: Faculty of Engineering and IT, the University of Sydney, 2012.
- MSc: Department of Industrial Engineering, Seoul National University, 2008.
- BSc: Department of Computer Engineering, Isfahan University of Technology, 2002.
- Graduate Certificate in University Learning and Teaching, UNSW, 2017.
Teaching:
- Engineering Management
- Software Project Management
- Project Schedule and Budget Control
- Modelling Project Risks
- Computer Applications in Project Management
- Social Network Analysis
Professional Membership:
- Australian Institute of Project Management (AIPM)
- Project Management Institute (PMI)
- Australian and New Zealand Academy of Management (ANZAM)
- Association for Computing Machinery (ACM)
- IEEE
