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.
Minhui Xue is (continuing) Lecturer (a.k.a. Assistant Professor) of School of Computer Science at the University of Adelaide. He is also Honorary Lecturer with Macquarie University. Previously, he was Research Fellow with Macquarie University and a visiting research scientist at CSIRO-Data61 at Sydney, Australia. His current research interests are machine learning security and privacy, system and software security, and Internet measurement. He is the recipient of the ACM SIGSOFT distinguished paper award and IEEE best paper award, and his work has been featured in the New York Times. He co-chaired the 1st IEEE AI4MOBILE workshop and the 1st IEEE MASS workshop on Smart City Security and Privacy. He currently serves on the PC committee of USENIX Security and Privacy Enhancing Technologies Symposium (PETS).
Competencies: Machine Learning Security and Privacy, System and Software Security, and Internet Measurement
Le Ba Dung
My name is “Lê Bá Dũng” (in Vietnamese script) which can be written in English script as “Ba Dung” (first name) and “Le” (last name). My main research interests are in Data mining, Machine learning and Artificial intelligence. Currently, I am focusing on Classification and Clustering algorithms. I obtained a Ph.D. in Computer Science from the School of Computer Science of University of Adelaide, Australia. My Ph.D. thesis was on the topic “Community detection in complex networks”. During my Ph.D., I developed a novel algorithm for detecting the community structure of complex networks and a novel benchmark for evaluating community detection algorithms. Before pursuing my Ph.D., I was a lecturer at the Faculty of Information Technology of Vietnam Maritime University, Vietnam.
I am a Research Fellow in the Faculty of Information Technology, Monash University, Australia. I completed my Ph.D. in Computer Science with a major in Software Engineering in 2018 at The University of Adelaide, Australia. I am passionate about research on Software Engineering. My research goal is to develop a deep understanding of how software-intensive systems are developed, designed, and evaluated in the industry. Based on this deep understanding, I then develop and evaluate theories, techniques, processes, and tools to increase software organizations' ability to develop and deploy high-quality software-intensive systems. My research interests reside in Empirical Software Engineering, Human and Social Aspects of Software Engineering, Software Architecture, DevOps, Secure Software Engineering, and Qualitative Research. I am currently working with OVIS Lab and HumaniSE Lab to understand how to embed human values (e.g., equality, diversity) in software. I also develop techniques to help build the next generation of software that better meets the needs of diverse and unique people (e.g., aging people).
Competencies: Empirical Software Engineering, Human and Social Aspects of Software Engineering, Software Architecture, DevOps, Secure Software Engineering, and Qualitative Research.
Leonardo Horn Iwaya
Leonardo H. Iwaya is a Postdoctoral Research Fellow in the Centre for Research on Engineering Software Technologies (CREST) at the University of Adelaide on projects funded by the Cyber Security Cooperative Research Centre (CSCRC). His work focuses on information security and privacy for new technologies, in particular mobile and ubiquitous health (mHealth/uHealth) systems. Leonardo completed his PhD in Computer Science at Karlstad University (KAU), MSc in Electrical Engineering at University of São Paulo (USP) and BSc in Computer Science at Santa Catarina State University (UDESC). During his career he already worked for Ericsson Research (Brazil and Sweden) in various projects in the areas of mobile health, cloud network security, and security APIs. During the PhD he worked in many European projects, such as the EU H2020 PAPAYA (PlAtform for PrivAcY preserving data Analytics). At CREST he has been involved in the CSCRC projects such as the Cyber Common Operating Picture for Executive Level Decision-Making, as well as research on security and privacy for mHealth/uHealth systems, and Docker technology. Most of his research intersects the areas of security, privacy, and healthcare with advanced cloud- and AI-based technologies.
Competencies: Privacy engineering, cybersecurity, mobile health, health informatics, privacy impact assessment, natural language processing, human factors, mixed-method research.
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.
Fengyi (Frances) Yang is a research assistant of the Centre for Research on Engineering Software Technology (CREST). Frances has had experience in fields of machine learning, data mining, control and robotics. Frances’ Honours Project is on Adversarial Machine Learning in Network Intrusion Detection. Frances’ research interest is in machine learning and natural language processing. The current research project Frances is working on is Defence against Adversarial Machine Learning in Sentiment Classification.
Competencies: Machine learning, adversarial machine learning.
Mai Anh Khoa Nguyen
Mai Anh Khoa Nguyen is a research engineer of the Centre for Research on Engineering Software Technology (CREST). He obtained his Master's degree in Software Engineering from The University of Adelaide. He is currently working on the security modelling of the Command, Control, Communication and Intelligence (C3I) Systems under the supervision of Professor Ali Babar. His research focuses on the application of model-driven engineering, text mining, agent-based modelling and simulation to discover the security vulnerabilities and cascading attacks of the System of Systems (SoS).
Competencies: Cyber Security, Security Modelling, Model Driven Engineering, Text Mining, Web Technologies.
I am currently pursuing a Master of Computer Science degree at the University of Adelaide. Before that, I worked as a Software Engineer at Ford Motor Company for four years, where I performed activities related to design, development, integration, and testing of complex Information Systems using Agile methodology. My interest lies in analyzing and solving complex problems in the field of Software Engineering and Cyber Security.
Anying is doing the Software Engineering activity under the supervision of Professor Muhammad Ali Babar at Crest, the University of Adelaide. She completed the Master of Software Engineering at the University of Adelaide.
Hien Le is a final year Master of Data Science student at the University of Adelaide. Hien obtained her bachelor’s degree in Accounting and Finance at the University of Melbourne. Hien received both scholarships on entry for her academic merit and was awarded Executive Dean’s Recognition of Academic Excellence by the University of Adelaide. Hien is currently working on a research project regarding automated cyber threat analysis module under the supervision of Professor Ali Babar and Dr. Chadni Islam. The research seeks to predict security incident and estimate financial impact of cyber-attacks on organisations from threat intelligence data by utilising Machine Learning and Artificial Intelligence techniques. Hien is enthusiastic about opportunities that allow her to combine both interests in data science and finance.
David Hin is currently a Ph.D. student at the University of Adelaide under the supervision of Professor M. Ali Babar and Dr. Huaming Chen. His area of research focuses on machine learning-assisted secure software development, with a particular interest in software vulnerabilities. Other interests include learning from big code, natural language processing, program comprehension, graph representations, and explainable AI.
Competencies: Mining software repositories, natural Language processing, security/vulnerability analytics, machine learning
Dr Ranran Bian received her PhD from The University of Auckland (New Zealand) and is currently working as a Postdoc researcher at The University of Adelaide. Her PhD focused on heterogeneous network mining and analysis, where novel algorithms for community discovery, ranking, dynamic embedding and change modeling in different heterogeneous networks were developed. The key areas of her research interests include: network embedding for dynamic heterogeneous networks, social network analysis, applying network analysis techniques in different cybersecurity domains.
Guanhua Wang is a PhD student under the supervision of Dr. Mingyu Guo and Prof. Ali Babar. His research is on applying deep learning technique to market design, and its application to cybersecurity domains (e.g., bug bounty systems).
Competencies: Deep Learning, Mechanism Design
Secure Mobile Health Application Engineering
Bakheet Aljedaani is a PhD student in the Centre for Research on Engineering Software Technologies (CREST) at the University of Adelaide. His current research focus is on the security of mobile health applications, particularly assessing the security perception for the end-users, as well as investigating the process of developing secure apps. His research is mainly conducted empirically (e.g., interviews and surveys) and analysing quantitive and qualitative data. The key areas of his research are human aspects of developing secure mobile health applications, security and privacy of mobile health applications, and end-users’ security requirements for mobile health applications. Bakheet worked as a lecturer at Umm Alqura University, Saudi Arabia before joining CREST. He obtained a bachelor degree in Computer Science from King Abdulaziz University, Saudi Arabia and a Master’s degree in Information Security from Lewis University, USA in 2008 and 2011 respectively.
Competencies: Human factor. Mobile health applications. Security and privacy. Security requirements. Empirical research. Quantitative and qualitative analysis.
Dr. Huaming Chen is a researcher of Centre for Research on Engineering Software Technologies (CREST). Huaming received his PhD from School of Computing and Information Technology in University of Wollongong. He completed his master in Computer System Architecture and bachelor (Hons) degrees in Electronics at Lanzhou University, in 2015 and 2012 respectively. During his research training in master and PhD, he has a major focus on the computational intelligence, particularly for applied machine learning and deep learning. He has collaborated with researchers with different expertises to develop leveraging algorithms and models to make contributions to the distinct challenges in different areas, including biologist, industrial production and transportation. He has also actively served as the reviewers for renowned grants and top international journals/conferences. He is now working on the topic lying at the intersection of machine learning, software engineering and cyber security. His research interests including: applied machine learning, software engineering, computational intelligence and cyber security.