Professor Ali Babar
On of the key goals of my research effort is to develop and/or rigorously evaluate approaches and tools for supporting the design, analysis, and evolution of complex and dependable software intensive system and services that meet both the functional and non-functional requirements as derived from the quality goals specified by the stakeholders. That means our research agenda is aimed at helping industry and society to build human- as well as technological-based competencies in designing, analyzing, and evolving high-quality software-intensive systems and services systematically and predictably.
My research is concentrated in the area of Software Engineering (SE). It is stimulated by the need of continuously evolving software development processes and practices to help organizations produce high-quality software intensive systems and achieve their business goals. Believing in close cooperation and alignment between industry and academia, my key research capabilities lies in the area of Empirical Software Engineering. My primary goal is to apply qualitative and quantitative research methods to investigate the role of people and processes in different software development paradigms. The key areas of my research interests include: Global Software Development (GSD), Knowledge Management, Continuous Software Engineering, Human factors in Software Engineering, Science to Technology Innovation and Socio-Technical aspects of Cyber Security.
I am passionate about research on software engineering. My research goals are (i) to develop a deep understanding of how actually software engineers design and implement large-scale software systems and (ii) to develop new techniques and tools to support software-intensive organizations in developing and deploying high-quality software. My research interests reside primarily in software architecture, empirical software engineering, DevOps, continuous delivery and deployment, global software engineering, requirement engineering, qualitative research, and human factors in software engineering, for which I extensively leverage both qualitative (e.g., grounded theory) and quantitative (e.g., controlled experiment) methods. My PhD research is focused on “Architecting and Organizing for DevOps”.
Faheem is a Ph.D. student at the University of Adelaide under Prof. Ali Babar supervision. He has been working with the research centre, Centre for Advanced Research in Engineering (CARE), on various research projects related to computer science. Afterward, he has been involved in various computer science related research adventures with GIK Institute. Before formally joining CREST, Faheem has been working on several research projects that include Architecture Patterns for Cloud-enabled Systems, Composition of Security into an IoT system, Data Exfiltration countermeasures, Security support in CDP and security of IoT and fog systems. Currently, his research primarily focuses on engineering big data security analytics solutions. The main focus of research is on investigating solutions that can adopt themselves in accordance with the quality of service requirements.
Nguyen Khoi Tran
My research interest is facilitating the discovery, retrieval, and utilisation of the content emerging from the Internet of Things (IoT) through the creation of “Internet of Things Search Engines” (IoTSE). My current focus is providing an architectural foundation for the open and distributed development, operation, and evolution of IoTSE. For more details and open topics, please refer to my Research page.
My research interest is in the field of security orchestration and automation, software architecture and self-adaptive system. I am a Ph.D. student of Software Engineering under the Supervision of Professor Muhammad Ali Babar and Dr. Surya Nepal in Crest Centre, at University of Adelaide, Australia. My Ph.D. is focused on “Providing architecture support for security orchestration.” My goal is to provide a reference architecture for security orchestration to facilitate the design and development of a self-adaptive security orchestration engine. Previously, I worked as a lecturer at Khulna University and Eastern University at Bangladesh. I obtained my master’s and bachelor’s degree from the School of Computer Science and Engineering, University of Dhaka, Bangladesh.
Mobile Health applications (mHealth apps) is promising technology which starts attracting people and health providers to improve the quality of service. The number of mHealth apps has increased, the number of publishers has also increased and the number of apps downloads has grown to indicate that mHealth is already become a part of people’s everyday life. However, sensitivity of data which will be collected by mHealth apps will require high protection to ensure data security. Manipulation of data can lead to impact patient’s health and will affect the growing of mHealth. Therefore, applying suitable mechanisms to provide secure transaction and reliable service is required. In my research, I will investigate and assess the security of mHealth from the software developers’ perspective. I will explore the different approaches and solutions that software developers are following to ensure developing secure mHealth apps, how their decisions can be made and what are the best practices to design secure apps to fulfil this demands. The research will identify the suitable solutions that can be applied for the healthcare domain.
My research interest is applying deep learning algorithms to software engineering and programming language. I am a Ph.D. student of Computer Science under the Supervision of Professor Muhammad Ali Babar and Professor Chunhua Shen in Crest Centre, at University of Adelaide, Australia. My Ph.D. is focused on “Deep Learning for General Purpose Code Generation.” My goal is to devise neural network models for source code analysis and generation. Previously, I worked as a research scientist at NetEase Inc. China. I obtained my master’s and bachelor’s degree from the School of Computer Science and Engineering, Zhejiang University, China.
Research on Software Engineering and its applications.
Research on Software Engineering and its applications.
Triet Huynh Minh Le (Lê Huỳnh Minh Triết) is currently a PhD student under the supervision of Professor Ali Babar at the Centre for Research on Engineering Software Technologies, the University of Adelaide. He obtained his first-class honours bachelor degree in Computer Science as a valedictorian from the International University – Vietnam National University, Ho Chi Minh City. His research interests include but are not limited to data mining and machine learning as well as their interdisciplinary applications. In his undergraduate study, Triet utilized machine learning to predict some challenging chemical properties. He published 7 papers including 2 SCI-indexed journal articles and won 4-time best conference paper awards. His PhD will expand his research works to explore how machine learning can perform predictive analytics and resource allocation in various domains of software engineering, especially in software maintenance. More information about Triet can be found here.
Bushra Sabir is currently a PhD student in the school of computer science, University of Adelaide. She was previously employed as permanent Senior Lecturer at Bahria University Islamabad Campus (Pakistan). She is a gold medalist in MS Computer and Software engineering and second position holder in BE Software Engineering. She has received both of the degrees from National University of Science and Technology (NUST) Pakistan, one of the best university with QS world ranking of 338. She has 6 years of experience as a lecturer and 2 years’ experience in software industry. She is active in research, her research interests include Cybersecurity, Software Engineering, Machine Learning, Computer vision, Data-mining, cloud computing, internet of things, Pattern Recognition, Spatial and temporal surveillance systems, Medical Imaging and
image processing. She has strong Programming skills and good knowledge of Data Structures, Object Oriented Programming, Digital Image Processing.