Recognising Visionaries in the Faculty of IT with the 2023 Dean’s Awards for Excellence in Research

Professor Phung is best known for his recent pioneering work in bringing the mathematics of optimal transport to advance research frontiers in trustworthy AI and human-like reliable, adaptive and robust machine learning. This year he was awarded an ARC Discovery Project for the aforementioned topics and a Best Student Paper Award at the Special Interest Group on Knowledge Discovery and Data Mining conference – considered the best conference in data science.

With a h-index of 46 and over 11,000 citations, Professor Phung is also internationally known for his work in graphical models and nonparametric machine learning for which he was a finalist of the 2022 Australian Museum Eureka Prize for Excellence in Data Science (the ‘Oscars’ of Australian science).

In addition to research excellence, he has demonstrated significant leadership at international and national levels, is an associate editor of the flagship Journal of Artificial Intelligence Research and has won several major research grants totalling 10M+ over the past five years.

Dr Rezatofighi is a leader in computer vision, machine learning and robotics. He has over 60 peer-reviewed research papers in top-tier conferences and journals, over 8100 citations and a h-index of 31.

Actively engaged in cutting-edge research projects, Dr Rezatofighi is a Chief Investigator in an Australian Research Council  Discovery Project and a Primary Investigator in three Defence Advanced Research Projects Agency grants.

Internationally recognised for his influence in the field, he has served as an area chair in esteemed IT venues including the 2020-2024 Computer Vision and Pattern Recognition Conference, the 2023 Neural Information Processing Systems conference, the 2023 Association for the Advancement of Artificial Intelligence conference and the 2021 Winter Conference on Applications of Computer Vision.

Associate Professor Wilson is the founder and co-director of the Artificial Intelligence for Law Enforcement and Community Safety (AiLECS) Lab, a collaboration with the Australian Federal Police (AFP).

Launched in 2019 and soon to become a formal centre, AiLECS is a culmination of prior work with the AFP on machine learning for digital forensics. It has attracted approximately $5.6M in cash funding from the Australian Government and industry.

Associate Professor Wilson’s expertise encompasses machine learning, information retrieval and digital forensics, with current research focusing on the application of AI in addressing serious societal issues such as transnational criminal activity. He also explores the ethical implications of AI technologies in law-enforcement applications and their explainability in policing and judicial contexts.

Professor Garcia De La Banda has supervised 11 students (10 PhD and 1 Master) to completion and has also been an Associate Supervisor for candidates in the Faculty of Medicine, Nursing and Health Sciences. Her students have all completed their candidature in a timely manner and achieved exceptional examination outcomes – a testament to the quality of her supervision.

As a supervisor, Professor Garcia De La Banda is well known for being generous with her time, giving detailed feedback on reports, papers and presentations, providing invaluable guidance to early career staff as an associate supervisor, as well as nurturing a collegial and welcoming environment for her research group.

Notably, Professor Garcia De La Banda has consistently provided high-quality supervision while holding a range of senior roles, including Head of the Caulfield School of IT, Deputy Dean, Deputy Dean (Research), ARC College of Experts member and Co-Chair of the Monash-Woodside Future Lab as well as undertaking her own research and attracting more than $60M in research income including $8M as Chief Investigator in 11 ARC grants (five as Lead).

Yicheng has contributed to eight peer-reviewed publications, four of which he was the first author in top-tier conferences and journals, accumulating a total of 146 Google citations.

A key area where Yicheng has made a remarkable difference is in addressing clinical problems associated with multiple sclerosis (MS), a severe global brain disease. Through his proposed AI model, Wu successfully automates the segmentation of newly appearing MS lesions, surpassing three existing methods and even outperforming two human experts on the widely recognized MICCAI-21 Challenge dataset.

This achievement significantly relieves the burden on clinicians and streamlines the process of diagnosis and treatment planning. In Australia, Yicheng’s work can potentially enhance the lives of over 25000 MS patients, potentially saving up to $1.75B in healthcare costs.

Tran studies causality and AI reasoning, envisioning a future where intelligent machines can reason and communicate effectively.

Within her first year of candidature, she had two A* papers accepted into the 2023 International Conference on Learning Representations and a third under embargo. During her Master of Data Science, she received a prestigious Monash Cliff Bellamy Award for ranking as one of the top postgraduate students in the faculty with a minimum average of 90% across all units in 2022.

She received partial funding for her PhD from CSIRO's Data61 and is collaborating with their research scientists on a project called Causality in Dynamical Systems. Targeting climate change problems, the project's main emphasis is on enhancing predictability and understanding of causal structures and dynamic systems.

During the first year of his candidature, Yujin’s inaugural PhD work ‘Smart App Attack: Hacking Deep Learning Models in Android Apps’ was successfully published in the 2022 IEEE Transactions on Information Forensics and Security journal. This publication has garnered substantial attention within the research community, receiving 71 likes on DeepAI and significantly raising awareness around safeguarding on-device deep learning models.

Additionally, Yujin’s second work ‘Training-free Lexical Backdoor Attacks on Language Models’ was published in the 2023 International World WIde Web conference. His paper merited a talk invitation from both New York University Tandon School of Engineering and Deque AI, serving as a testament to the importance and influence of Yujin's research contributions.

Yujin has consistently exhibited an astute ability to guide and inspire students, offering constructive feedback and presenting numerous insightful ideas. As a result of this collaborative effort, he jointly completed another highly impactful work ‘Exploring AI Ethics of ChatGPT: A Diagnostic Analysis’ in February this year, and as of June, has already amassed 64 citations. A further two collaborative papers were published to the 2023 Secure and Trustworthy Deep Learning Systems under the chapter ‘Security in On-device Machine Learning’.

Jimmie’s research achievements have seen him invited to be the Student Representative for the 2023 Learning Analytics and Knowledge conference. His esteemed standing in the academic community has also led to invitations for prominent speaking opportunities, such as a solo presenter at the 2023 international webinar by the Society for Learning Analytics Research on his paper ‘Socio-spatial Learning Analytics for Embodied Collaborative Learning’ – a research area he is pioneering.

Jimmie's effective leadership and collaboration skills are also evidenced by his extensive co-authorship and mentorship roles. His work on modelling COVID-19 transmission in schools was published by the Journal of Global Health and featured in Monash Lens and several other media outlets. His research on improving online learning tools has also been covered in the British Journal of Educational Technology's Research Headlines and was recognised as one of the top cited Wiley papers in 2021 to 2022.

Most importantly, Jimmie has demonstrated an entrepreneurial spirit and a commitment to translating academic knowledge findings into real-world practical applications. A prime example is his creation of AI-based software tools informed by his research, which he is making available to the public through his online platform, ResearchAIde.

Jialin’s research lies at the intersection of food science, human-computer interaction and computational technology. She has introduced novel perspectives on food as more than just a biological necessity but also as a platform for interaction, computation and engagement. For example, her work ‘Logic Bonbon: Designing Food as Computational Artefact’ demonstrates an innovative approach to viewing food as a computational artefact.

Thus far two of Jialin’s papers where she is the lead author have been accepted at esteemed conferences such as the ACM CHI Conference on Human Factors in Computing Systems (CHI) in 2022 (A* ranked) and ACM SIGCHI Conference on Designing Interactive Systems (DIS) in 2023 (A ranked). She has also contributed two peer-reviewed articles as the first author to the Q1-ranked International Journal of Food Science and Gastronomy, further establishing her prominence in the field. Additionally Jialin has contributed to four more short papers, including a Work in Progress paper and a Workshop paper to CHI’21, a Special Interest Group paper for CHI’22 and an Art Exhibition paper to DIS’23.

This year Jialin had the honour of delivering a keynote lecture on ‘From Food Design to Human-Food Interaction’ at RMIT University for their unit ‘Designing at the Intersection of Food & Technology’. She was also invited to present her ‘CyberFood: Food-Computation Integration’ research at the Dagstuhl Seminar: Eat-IT in Germany. In 2021, she was a guest speaker at the Morphing Matter Lab, part of the Human-Computer Interaction Institute at Carnegie Mellon University in the US. Esteemed media outlets such as ABC Radio Illawarra, Gizmodo Australia and The National Tribune have also featured her research.