School of Computer Science

Dr Wei Bao is an Associate Professor in the School of Computer Science in the Faculty of Engineering at the University of Sydney. He is a member of the Centre for Distributed and High Performance Computing. He holds a Bachelor of Engineering degree from Beijing University of Posts and Telecommunications (2009), a Master of Applied Science degree from the University of British Columbia (2011), and a Doctor of Philosophy degree from the University of Toronto (2015).

Dr Wei Bao's research focuses on networking and distributed machine learning, an area that significantly impacts the performance, scalability, and collaboration of networked systems. To address the fundamental limitations of current networks and distributed systems that constrain AI applications, Dr Bao founded the I-Net (Intelligent Networking) Group. His current research focuses on three main areas: distributed machine learning, AI for networked systems, and optimisation for intelligent networks. In distributed machine learning, he has developed innovative solutions to improve the speed, scalability, and efficiency of machine learning workflows. His work on AI for networked systems integrates AI with existing networks to achieve high quality digital applications without requiring significant investment in network infrastructure. In addition, Dr Bao's research on intelligent network optimisation aims to improve performance through rigorous analysis of large-scale systems.

Dr Wei Bao has actively pursued industrial collaborations to translate his research into practical applications. His successful partnerships with companies such as Link Group have resulted in significant funding and impactful projects. Recognising the importance of bridging academic research with industry needs, Dr Bao continues to seek new collaborations with both established and emerging technology companies. His aim is to broaden the scope and scale of his research impact by fostering innovative solutions that benefit a wider range of industries.

Dr Wei Bao is also actively seeking self-motivated PhD candidates to join his research team. He offers a dynamic and supportive environment within the I-Net Group, where students can engage in cutting-edge research on networking and distributed machine learning. If you are interested, please send your CV to wei.bao@sydney.edu.au.

Professor Athman Bouguettaya received his PhD in Computer Science from the University of Colorado at Boulder in the US in 1992. Before joining the University of Sydney as Professor and Head of the School of Computer Sciencein 2016, he was Professor and Head of the School of Computer Science and IT at RMIT University in Melbourne. Prior to this he was Science Leader in Service Computing at the CSIRO ICT Centre (now DATA61) in Canberra, and a tenured faculty member and program director in the Computer Science department at Virginia Polytechnic Institute and State University (Virginia Tech) in the US.

Professor Bouguettaya is a founding member and past president of the Service Science Society, a non-profit organisation that aims to form a community of service scientists for the advancement of service science.

He has published more than 220 books, book chapters, journal articles and conference papers in the area of databases and service computing; he is currently editor-in-chief of the Springer-Verlag Services Science book series; and he has served as guest editor of a number of special issues of journals including ACM Transactions on Internet Technology on Semantic Web Services, IEEE Internet Computing on Database Technology on the Web, and IEEE Transactions on Services Computing on Service Query Models.

He has also served on the editorial boards of a number journals including ACM Transactions on Internet Technology, Distributed and Parallel Databases Journal, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Services Computing, International Journal of Cooperative Information Systems, International Journal on Next Generation Computing and VLDB Journal; and as a program chair of the 2017 WISE Conference, the 2012 International Conference on Web and Information System Engineering, the 2010 and 2009 Australasian Database Conferences, the 2008 International Conference on Service Oriented Computing and the 2004 IEEE RIDE Workshop on Web Services for e-Commerce and e-Government.

Professor Bouguettaya has been the recipient of several nationally competitive grants in Australia, the US, the EU, China and Qatar, as well as major industry grants from multinational companies including HP and Sun Microsystems (now Oracle).

He is an ACM Distinguished Scientist, an ACM Distinguished Speaker, a Fellow of the IEEE and a member of the IEEE Fellow Nomination Committee.

PhD

Dr. Weidong (Tom) Cai is an Associate Professor in the School of Computer Science, Director of the Multimedia Laboratory, and Associate Director of the Biomedical & Multimedia Information Technology (BMIT) Research Group at the University of Sydney. He was a Lead Investigator / Visiting Professor on medical image analysis and medical computer vision at Harvard Medical School in 2014. He received his PhD degree in Computer Science from the Basser Department of Computer Science, The University of Sydney, in 2001. His research interests include computer vision, medical image computing, machine learning, image/video processing, audio computing, multimedia AI, pattern recognition, computer graphics, bioimage informatics, and computational neuroscience. He has published over 300 peer-reviewed papers in leading international journals and proceedings of top international confereces. Dr. Cai is a Senior Area Editor on the editorial board of IEEE Transactions on Image Processing, Associate Editor of Computational Visual Media (Springer), Associate Editor of Brain Informatics (a Springer interdisciplinary journal on computational neuroscience, artificial intelligence, big data analytics, and cognitive research), and Guest Editor of Machine Vision and Applications (Springer) and Neurocomputing (Elsevier). He is also the Springer-Nature Brain Informatics & Health Book Series Editor, and Co-Editor of Medical Computer Vision: Algorithms for Big Data (Springer).

Dr Clément Canonne is a Senior Lecturer in the School of Computer Science, where he does research in theoretical computer science. His main research interests lie in property testing, learning theory, and, more generally, randomised algorithms and the theory of machine learning.

Prior to joining the University of Sydney, Clément was a Goldstine postdoctoral fellow at IBM Research Almaden, and a Motwani fellow at Stanford University. He obtained his Ph.D. from Columbia University in 2017.

Dr Lijun Chang is an Associate Professor in the School of Computer Science at the University of Sydney. Prior to that, he was a Future Fellow at the University of Sydney and a DECRA Fellow at the University of New South Wales. He received a Bachelors degree in Computer Science & Technology from Renmin University of China, and a Ph.D from the Chinese University of Hong Kong. Lijun joined the University of Sydney as a Lecturer in August 2017.

Dr. Armin Chitizadeh is a lecturer at the University of Sydney School of Computer Science. He received his Bachelor of Software Engineering with First Class Honours from the University of New South Wales (UNSW) in 2015 and completed his PhD in Artificial Intelligence at UNSW in 2020 under Professor Michael Thielscher's supervision.

He worked at UNSW as a casual academic and then education focused associate lecturer until 2024. He currently holds a lecturer position at the University of Sydney.

Prof. Davis is the Professor of Information Systems and Services at the School of Computer Science. He has been active researcher in the information systems field, with a focus on research questions at the intersection between information systems and computer science, namely on semantic information processing, crowdsourcing, decision support, and service computing. In particular, he has contributed extensively to understanding the creation, sharing and utilisation of information and knowledge in organisations and the links to decision making. He is a recipient of the IBM Faculty Research award for IT services-related research. His research has been funded by the Australian Research Council, Carnegie Bosch Institute, and IBM Research Labs, among others. He is a Charter Member of the Association for Information Systems, a Senior Member of the Association for Computing Machinery (ACM) and a Member of the IEEE.

Professor Davis is a board member for Service Science Society of Australia and is the Director of the Sydney Accelerator Network (SAN):IT.

More biographical information on Prof. Davis is available on Wikipedia: http://en.wikipedia.org/wiki/Joseph_G._Davis

Katy Ilonka Gero is a human-computer interaction researcher focused on creativity, writing technologies, and the ethics of AI. She is currently a Lecturer in the School of Computer Science at the University of Sydney and previously held fellowships at Harvard University and the Library Innovation Lab. Her research explores how language models impact creative practice, ownership, and learning, with a growing interest in community-driven AI. She holds a PhD from Columbia University and a BS from MIT, and her work has been supported by the NSF, Amazon, and the Brown Institute. Also a poet and essayist, she is the author of "The Anxiety of Conception" (2025) and co-edits "Ensemble Park", a literary magazine for human-computer co-writing. 

Rahul Gopinath is a Lecturer in the School of Computer science. His main research area lies in the junction between Software Engineering and Cybersecurity. His research focus is on using static and dynamic program analysis to improve reliability, security, and maintainability of software systems.

Prior to joining the University of Sydney, he was a postdoctoral researcher at the CISPA Helmholtz Center for Information Security, Germany. He earned his Ph.D. in 2017 from the Oregon State University, US.

Vincent Gramoli is Professor of Computer Science at the University of Sydney and the Founder and Director of Redbelly Network. He received the Habilitation to Direct Research from Sorbonne, the Oustanding Science to Safeguard Australia Eureka Prize from Australian Museum and Department of Defence, the Education Leader of the Year Award from Blockchain Australia and the Future Fellowship from the Australian Research Council. In the past, he has been affiliated with INRIA, Cornell, Data61 and EPFL. His area of interest is in distributed computing and security. Prof. Gramoli acted as the Chair of the Cybersecurity Committee for CORE, the Chair of the Blockchain Technical Committee for the ACS, and acts as a Blockchain expert for central and commercial banks. He teaches Distributed Systems at the University of Sydney, the Coursera Blockchain Scalability MOOC and published the textbook with Springer.

Dr. M.Reza HoseinyFarahabady is a full time associate researcher and educator specializing in cutting-edge advancements in computer science, with a particular focus on the following areas:

• High-Performance Parallel and Distributed Computing: Investigating scalable computing solutions for large-scale systems to meet the growing demands of modern applications.
• Big Data Applications: Addressing challenges in processing, managing, and analyzing massive datasets to enable insights and innovation.
• Reliability Principles of Distributed Systems and Networks: Developing robust frameworks to enhance fault tolerance, resilience, and dependability in complex systems.
• Operating System Internals: Delving into the design and optimization of core system components to improve overall system performance.
• Dynamic Resource Allocation in Cloud and Virtualized Systems: Exploring efficient strategies to optimize resource usage and performance in cloud environments and distributed infrastructures.
• Green and Sustainable Computing: Promoting energy-efficient and environmentally friendly computing practices for sustainable technological growth.
• Theoretical Computer Science: Advancing the foundational principles that underpin computational systems and algorithms.

Dr. Reza earned a Ph.D. in Computer Science from Uni. of Sydney in 2015. He is passionate about bridging the gap between theoretical research and practical implementation, fostering innovation that addresses real-world challenges.

In addition to his research, Dr. Reza actively contributes to academic communities by publishing in esteemed journals, participating in conferences, and mentoring the next generation of computer scientists. He is currently affiliated with Uni. of Sydney, where he continues to explore innovative solutions to some of the most pressing problems in modern computing.

Dr. Karlos Ishac is an academic researcher and lecturer with a PhD in Human Informatics from Tsukuba University Japan. He holds multiple publications across high-end Journals and international conferences such as IJCAI, ICRA and SIGGRAPH ASIA. He has developed and delivered University courses in Computer Science and Engineering with incredibly positive student feedback scores (SFS). Additionally, Dr. Ishac has spearheaded major innovative projects with industry giants such as Google, Fujitsu, and the Tokyo Dome. He was the recipient of a Japanese Government full Scholarship and awarded several additional Government grants for his research. Dr. Ishac completed his PhD at the world-famous Artificial Intelligence Lab at the University of Tsukuba in Japan and continued to work there as a Postdoctoral Researcher in the fields of AI, human cyber-physical systems, and immersive technologies.Dr. Ishac has also built his company Lifeform AI, from an idea to raising investment, managing an international diverse multi-disciplinary team, and delivering a range of products to end-users.

Dr. Anastasia Isychev is a lecturer at the School of Computer Science, University of Sydney. Earlier, she was a postdoctoral researcher at TU Wien with Maria Christakis and received her PhD from TU Munich, where she was co-advised by Eva Darulova and Helmut Seidl. Before that she was a graduate student in Max-Planck Institute for Software Systems (MPI-SWS) and Saarland University.

Anastasia's research interests span over various topics in formal methods and software engineering. Her work is centered around static analysis, optimization, repair and testing and how they can help make software reliable and understandable.

Hong Jin Kang is a Lecturer in the School of Computer Science. His research area lies in Active Learning and AI for Software Engineering. With an overarching aim of improving developer productivity, his work has a focus on the application of human-centric AI to a range of software engineering tasks, including secure code development.

Prior to this role, he conducted research at leading, renown software engineering groups as a postdoctoral fellow at UCLA and a Ph.D. student at Singapore Management University. His industrial collaborations have led to the deployment of research techniques in industry, and had practical impact in discovering vulnerabilities leading to assigned CVEs.

His work has been published at top venues of Software Engineering research, including ICSE, FSE, ASE, TSE, and TOSEM. He has also served on the program committees and as a reviewer at the top publication venues.

Judy Kay is Professor of Computer Science. She leads the Human Centred Technology Research Cluster in the Faculty of Engineering at the University of Sydney. A core focus of her research has been to create infrastructures and interfaces for personalisation, primarily to support people in lifelong, life-wide learning. This ranges from formal education settings to helping people use their long-term ubicomp data to support self-monitoring, reflection, and planning.

Central to her work has been the design of user modelling frameworks and interfaces that enable people to control their long-term personal information from diverse sensors on devices, be they worn, carried, embedded in the environment, or conventional desktops. She has integrated this into new forms of interaction, including virtual reality, surface computing, wearables, and ambient displays.

Her research has been commercialised and deployed, and she has extensive publications in leading venues for research in user modelling, Artificial Intelligence in Education, Human-Computer Interaction, and Ubiquitous Computing. She has held leadership roles in top conferences in these areas, notably having served as Editor-in-Chief of the IJAIED, International Journal of Artificial Intelligence in Education (IJAIED), and Editor of IMWUT, Interactive Mobile Wearable and Ubiquitous Technology (IMWUT). She is a member of the Ubicomp Steering Committee,

and a member of the Advisory Boards of peak journals in her area, ACM Transactions on Interactive, Intelligent Systems (TiiS), and Proceedings of the ACM in Interactive, Mobile, Wearable and Ubiquitous Technology (IMWUT).

Professor Jinman Kim is a Professor of computer science at the University of Sydney. He established and leads the Biomedical Data Analysis and Visualisation (BDAV) Lab at the School of Computer Science. He is the Imaging Theme Leader of the ARC Training Centre in Innovative Biomedical Engineering on musculoskeletal technologies. He is the also the Director of the Telehealth and Technology Center, Nepean hospital. Prof Kim co-leads the ‘digital health imaging’, as part of the Faculty of Engineering’s Digital Science Initiative, with the vision and strategy to improve the use and accessibility of medical imaging via AI innovations.

Prof Kim received his PhD degrees in computer science from the University of Sydney in 2006. He received the APD Research Fellowship from the ARC in 2008. In 2010, he joined the University of Geneva as an Experienced Researcher (Marie Curie). He then worked as a Senior Lecturer (2013), A/Prof (2016), and Prof (2022) at the University of Sydney.

PhD and MSc (Computer Science), MEd (Higher Education)

I am Professor at the School of Computer Science, University of Sydney. My research is in Machine Learning, Data Mining and Neural Networks. I also teach courses in these areas -Introduction to Artificial Intelligence, and Machine Learning and Data Mining. I have received several best paper and other research awards and two times the Dean's Award for Outstanding Teaching. I have supervised to completion 11 PhD and about 60 Honours thesis students, all in Machine Learning. My students have received many prizes and awards including the Google Fellowship in Machine Learning which recognises exceptional research and the prestigious ZONTA International Women in Technology Scholarship. I have been co-organising the Data Science for Social Good workshop at ECML PKDD since 2017. I am Associate Editor of the International Journal of Artificial Intelligence in Education (IJAIED) and the International Journal of Data Science and Analytics (IJDSA), and an editorial board member of the Journal of Educational Data Mining (JEDM); I have taken leadership roles in leading conferences on Artificial Intelligence and Machine Learning and regularly serve on their program committees. I am currently the Associate Head Research Education for the School of Computer Science, and previously was the Sub-Dean Teaching and Learning for the Faculty of Engineering.

Jonathan K. Kummerfeld is a Senior Lecturer (ie., research tenure-track Assistant Professor) in the School of Computer Science at the University of Sydney and collaborates with a range of academics across the world, including on US DARPA-funded projects on AI agents that communicate. He completed his Ph.D. at the University of California, Berkeley, and was previously a postdoctoral research fellow at the University of Michigan, a visiting scholar at Harvard, and a DECRA fellow, at Sydney (2023-2025).

Jonathan’s research focuses on interactions between people and NLP systems, developing more effective algorithms, workflows, and systems for collaboration. He has been on the program committee for over 50 conferences and workshops, as the CTO for ACL Rolling Review (a peer review system), and as a standing reviewer for the Transactions of the Association for Computational Linguistics journal and the Computational Linguistics journal.

Dr HaeJin Lee is a postdoctoral research fellow in the School of Computer Science at the University of Sydney. She holds a PhD in Information Sciences and a bachelor’s degree in Mathematics, both from the University of Illinois Urbana-Champaign. Her research focuses on human–computer interaction, explainable AI, learning analytics, educational data mining, and learning sciences, with a particular emphasis on understanding and supporting self-regulated learning. She combines learner modelling and explainable AI to develop personalised feedback and learning technologies that help learners reflect on and regulate their learning. Her work also explores how human–AI collaboration can support learning and teaching.

I received my PhD in Computational Science from the Australian National University (ANU), where I worked under the supervision of Professor Amanda Barnard and subsequently held a Postdoctoral Fellowship. Prior to joining the University of Sydney, I was an Assistant Professor at the City University of Macau. I am also a Visiting Fellow with the MINT Lab at Johns Hopkins University, collaborating closely with Professor Seth Lazar.