Data Science Institute (DSI)

Emily Booth is a Research Fellow at the University of Technology in Sydney, Australia. She specialises in narratives, particularly as they manifest at part of misinformation, disinformation, and conspiracy theories; and has a particular interest in the narrative experiences of young people, offline and online. Her work seeks to address the underlying drivers of social discord rather than their surface-level expressions. At the intersection of social sciences and literary studies, she draws on the theoretical and methodological strengths for her transdisciplinary research.

Her work has had considerable direct impact, including integrating into the national Respectful Relationships Education program for combatting sexism and discrimination in schools, supporting the Step Together deradicalisation program currently facilitated by the Australian Department of Home Affairs, and more. 

She has published widely on misinformation, conspiracy theories, and radicalisation; reading and book publishing; digital media; school education, and more. She has written for The Conversation and appeared on radio and podcasts disseminating her research. In 2025, she consulted on the BBC Documentary "Men of the Manosphere", available to watch in Australia on Stan. In 2026, her co-authored book How to use Wikibase for Mixed-Methods Research: An Interdisciplinary and Collaborative Approach was published by Elgar Publishing.

Her research includes work funded by the Facebook Research Award, the Australian Department of Home Affairs, the Defence Innovation Network, the Australian Department of Defence, the NSW Department of Communities and Justice, and more. She has also led a series of grants including the UTS Social Impact Grant (2019), the Frances Henne Research Grant from the Young Adult Library Services Association (YALSA), and a UTS Blue Sky Discovery grant (2024).

She is passionate about research ethics and has been a member of the UTS Human Research Ethics Committee since 2020. Formerly, she was also a member of the University Student Conduct Committee (USCC) and Student Misconduct Appeals Committee (SMAC).

Her PhD research explored how teenagers respond to adult influence on their reading practices in the contexts of leisure reading, school reading, and industry engagement. She has published widely on diversity and inclusion in the Australian publishing industry as part of her love for literature and the power of stories; particularly with regard to young people. Outside of academia, she worked in the publishing industry for a decade as a specialist in children's and young adult literature.

Distinguished Professor Fang Chen is a globally recognised and award-winning leader in artificial intelligence and data science. She is the Executive Director of the Data Science Institute at the University of Technology Sydney (UTS), where she drives transformative research and innovation at the intersection of academia, government, and industry. Her career has encompassed senior leadership roles at Intel, Motorola, and CSIRO, as well as serving as Dean of Faculty at Beijing Jiaotong University.

Research Expertise and Impact Areas

Distinguished Professor Chen’s research is internationally recognised across a broad spectrum of areas, including:

• Artificial Intelligence, Machine Learning, and Data Science
• Human–Machine Interaction and Behaviour Analytics

• Responsible and Human-Centred AI

• Visual and Interactive Analytics

• AI for Sustainability and Societal Impact

Her work delivers innovative, data-driven solutions spanning research, translation, and product deployment and adoption, addressing complex challenges in transportation, water, energy, agriculture, telecommunications, health, financial services, real estate, education and retail. 

Awards and Recognition

Distinguished Professor Chen has received numerous prestigious honours, including:

• Transport Woman of the Year,  by ITS Australia, the peak industry body for intelligent transport systems (2026)
• Australian Financial Review AI Awards (2025)
• The Leading Science Award, the Australian Museum Eureka Prize for Excellence in Data Science (2018)
• NSW Premier’s Prize for Science and Engineering (2021)
• ANZ Women in AI Award (2021)
• Brian Shackle Award (2017, IFIP) for outstanding contributions to human–computer interaction
• NSW Water Professional of the Year by the Australian Water Association (AWA), the peak national body for the water sector, for leadership in digital transformation. 

She has also led teams to multiple national and international awards, including the Intelligent Transport Systems Australia National Awards (2014, 2015, 2018, 2025), several iAwards (NSW 2017, 2023, 2024; VIC 2019, 2020), and the Australian Water Association’s Research and Innovation Awards (2018, 2022).

Publications and Patents

Distinguished Professor Chen has authored over 400 peer-reviewed publications and several influential books on data science and AI research, AI for business, and human–computer interaction. Her two Springer volumes on trustworthy and human-centred AI, Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent (116,000 downloads since 2018) and Humanity Driven AI (32,000 downloads since 2022), have been widely read worldwide.

She has also filed more than 30 patents across eight countries (Australia, US, Canada, Europe, Japan, Korea, Mexico, and China), demonstrating her strong impact on both scientific advancement and technology transfer.

Thought Leadership and Keynotes

A sought-after global thought leader, Distinguished Professor Chen has delivered many keynote speeches at leading international conferences and has been invited numerous times to speak on the future of responsible AI and innovation at government, industry, and policy forums worldwide. A prominent public speaker, including TED Talks and international keynotes, she champions cutting-edge research and promotes responsible and inclusive innovation that builds public trust.

She has collaborated with more than 100 organisations across North America, Europe, and Asia, spanning blue-sky research through to product development and deployment. Her leadership consistently delivers pioneering technologies that generate measurable business value, societal benefit, and new models for innovation and community support.

Governance and Advisory Roles

 Distinguished Professor Chen serves on several influential boards and expert panels, including:

• Australian Federal Industry Science and Innovation Australia (IISA) Board
• NSW Government AI Review Committee (which established the AI assurance framework)
• Singapore National Research Foundation expert panel
• ITS Australia Board (2021–2024)

She is also the Chair of the ACM Intelligent User Interfaces Steering Committee and serves as an advisor to several startup companies.

Dr Victor W. Chu is a data science researcher specialising in agricultural AI, explainable AI (XAI), remote sensing, energy, climate and extreme weather modelling, carbon and emissions modelling, and AI ethics. He currently leads the A-Theme at the Data Science Institute, covering livestock, horticulture and environmental modelling. His work sits at the intersection of machine learning, spatio-temporal analytics, environmental modelling and responsible AI, contributing to national priorities in digital agrifood innovation and climate resilience.

Previously, he was a Senior Research Engineer (programme management) at the Smart National Research Centre of the Nanyang Technological University (NTU) in Singapore. His duty was to design and deliver data science solutions for government agencies, fulfilling their stringent requirements, e.g., explainability, data security, project governance and standards etc. Prior to venturing abroad, Victor was employed by the CSIRO where he completed an infrastructure failure prediction improvement project by transfer learning techniques.

He has published extensively in leading journals and conferences in data science, AI, information systems, and service computing, and serves as a reviewer for leading IEEE and ACM venues.

Dr. Yifei Dong is a Research Fellow at the Data Science Institute, University of Technology Sydney, specializing in LLM-assisted agent systems, explainable AI, and multimodal artificial intelligence. His research develops intelligent systems that can explain their decisions and operate across multiple modalities, with practical applications in healthcare, education, and government services.

With a PhD in Computer Science from UNSW Sydney and a decade of fintech industry experience including CTO roles, Dr. Dong brings unique expertise in both technical leadership and commercial AI deployment. He has secured over $2.4 million in competitive funding, developing AI solutions that bridge academic research with real-world applications across diverse sectors including healthcare analytics, educational technology, and financial systems.

Dr. Dong actively supervises PhD and Honours students while serving on international conference committees and reviewing for leading AI journals. His research consistently focuses on making AI systems more transparent, reliable, and beneficial for society, positioning UTS as a leader in responsible AI development that addresses both technical challenges and practical implementation.

Dr Heather Ford is an ARC Future Fellow and Professor in the School of Communications at UTS. She is the Coordinator of the UTS Data and AI Ethics Cluster, Affiliate of the UTS Data Science Institute, and Associate of the UTS Centre for Media Transition. She was appointed to the International Panel on the Information Environment (IPIE) in 2023 and is currently conducting research funded by the Australian Research Council and the Wikimedia Foundation on Wikipedia bias, question and answering technologies, digital literacy and the impact of generative AI on our information environment. She has a background working for global technology corporations and non-profits in the US, UK, South Africa and Kenya. A former Google Policy Fellow at the Electronic Frontier Foundation, former Executive Director of iCommons and co-founder of Creative Commons South Africa, her research focuses on the social implications of media technologies and the ways in which they might be better designed to prevent misinformation, social exclusion, and harms as a result of algorithmic bias. 

Heather completed her DPhil (PhD) at the Oxford Internet Institute at Oxford University. She has a Masters in Information Management and Systems (MIMS) from the University of California, Berkeley iSchool and has worked as a fellow at Leeds University, Stanford University, as a Google Policy Fellow and as a researcher at the University of the Witwatersrand LINK Center. Before her postdoctoral studies, she worked for a number of non-profit technology organisations including the Association for Progressive Communications, Creative Commons, the Electronic Frontier Foundation, Privacy International and Ushahidi. She was the Executive Director of iCommons, a global non-profit organisation started by Creative Commons between 2006 and 2008. She has been on the advisory and executive boards of the Wikimedia Foundation, iCommons and The African Commons Project where she worked towards the goal of fairer, more flexible intellectual property provisions for the Internet, particularly in developing countries. She is passionate about using creative methods in the social sciences to reimagine future technologies. 

She has published in a variety of journals including Big Data and Society, New Media and Society, the International Journal of Communications, Social Studies of Science and a number of Advanced Computer Machinery (ACM) journals. She is a founder editor of ethnographymatters.net and reviews articles for a number of journals and conferences in the fields of science and technology studies, media and communication and media ethics. 

Amir H. Gandomi is internationally recognised as one of the world’s most highly cited and influential researchers, known for his pioneering contributions to global optimisation, machine learning, big data analytics, and evolutionary computation. His interdisciplinary research spans engineering, computer science, artificial intelligence, and data-driven modelling and has helped advance multiple research fronts worldwide.

He is a Professor of Data Science in the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). Demonstrating exceptional research momentum, he was promoted to Full Professor only four years after completing his PhD, reflecting the rapid development and sustained international impact of his research career. His research has been supported by major funding bodies, including the U.S. National Science Foundation (NSF), the Australian Research Council (ARC), and Cooperative Research Centres (CRC), among others.

Professor Gandomi has received numerous prestigious honours recognising his contributions to science and engineering, including the 2026 Thomas Hawksley Gold Medal from the Institution of Mechanical Engineers (IMechE), the 2025 Sigma Xi Young Investigator Award from Sigma Xi, The Scientific Research Honor Society, the 2025 IEEE HITC Award for Excellence in Hyper-Intelligence, the 2024 IEEE TCSC Award for Excellence in Scalable Computing, the 2023 Achenbach Medal (bestowed at Stanford University), and the 2022 Walter L. Huber Prize, the highest-level mid-career research award across all areas of civil engineering. Sigma Xi is one of the world’s oldest and most esteemed multidisciplinary scientific societies, with more than 200 Nobel Laureates among its members, including Albert Einstein.

He has published more than 500 peer-reviewed journal articles and 15 books, collectively attracting over 84,000 citations, with an H-index exceeding 125. He has been recognised by Clarivate Analytics as a Highly Cited Researcher for six years, placing him among the world’s most influential researchers. His international standing is further reflected in his ranking among the top 250 computer scientists worldwide and 3rd in Australia. In the Stanford University–Elsevier assessment of the world’s most impactful researchers, he was ranked 29th worldwide in Artificial Intelligence and Image Processing in 2024.

Professor Gandomi holds senior editorial roles across leading international journals and has served as Editor in Chief and Associate Editor for prominent IEEE publications. He is regularly invited to deliver keynote and plenary lectures at major international conferences and scientific forums.

Before joining UTS, Professor Gandomi was an Assistant Professor at the School of Business at Stevens Institute of Technology in the United States and a Distinguished Research Fellow at the BEACON Center at Michigan State University, an NSF-funded Science and Technology Center bringing together biologists, engineers, and computer scientists to investigate and apply evolutionary principles to complex scientific and technological challenges.

Tung Khuat is now working as a Research Fellow at the Complex Adaptive Systems Lab, Data Science Institute in the University of Technology Sydney with a focus on building modern explainable, transparent, and robust machine learning algorithms. He received a Ph.D. degree in 2021 from the University of Technology Sydney, Australia. Before his doctorate, he completed a Degree of Engineer in Software Engineering in 2014 from the University of Science and Technology, Danang, Vietnam.

Dr. Khuat is also an active reviewer for many prestigious journals and international conferences such as IEEE TNNLS, IEEE TIE, IEEE TSMC: Systems, Soft Computing, AI Review, ASE, IEEE Access, and ICONIP. He is currently a member of the IEEE, IEEE Computational Intelligence Society, and IEEE Computer Society.

Khuat's research interests include machine learning, interpretable machine learning, fuzzy systems, knowledge discovery, evolutionary computation, intelligent optimization techniques, and applications in software engineering.

He has previously been a Senior software engineer at the FPT Software Danang, Vietnam (Jan-2018 to Jun-2018), has been a project officer at the School of Computer Science and Engineering, Nanyang Technological University, Singapore (Aug-2016 to Mar-2017), and has been a research assistant at the University of Danang working on the research topics of Software Effort Estimation and Software Testing using Intelligent Computational Algorithms (Mar-2015 to Aug-2016 and Apr-2017 to Dec-2017).

Jooyoung Lee is a Research Fellow at the Behavioural Data Science Lab, University of Technology Sydney, specialising in computational social science, online misinformation, and digital safety. Her research integrates large-scale natural language processing, machine learning, and behavioural analytics to understand how harmful narratives emerge, spread, and influence online communities.

Peter Leihn is a Visiting Professor in Applied Artificial Intelligence and Data Science.

Peter’s 30+ year career has focused on science and technology development and commercialisation spanning industry, government and academia.  He was formerly the Director of the Office of the NSW Chief Scientist and Engineer, a Business Unit Director of ARC Centre of Excellence NICTA, Commercial Director of CSIRO’s Data 61, Deputy Director UTS Data Sceince Institute, and has led several companies commercialising technology R&D.

Peter acts as a strategic advisor to multiple Australian and international organisations ranging from start-ups to publicly traded entities and government agencies. He is a graduate of the Australian Institute of Company Directors and is an experienced Company Director.

Dr Bin Liang is a Senior Lecturer at the Data Science Institute, University of Technology Sydney (UTS). Prior to joining UTS, he was a researcher at CSIRO Data61. He received his PhD in Computer Science from Charles Sturt University. His research focuses on multimodal intelligence for complex systems, developing artificial intelligence methods that integrate and reason over heterogeneous information including images, text, geospatial data, graphs, time series, and operational records. His current research spans multimodal and vision-language models, agentic AI, retrieval-augmented generation, graph machine learning, computer vision, and geospatial AI, with a particular interest in intelligent systems that move beyond prediction towards reasoning, decision support, and interaction with real-world processes.

Bin has published in leading international AI, data mining and computer vision venues, including NeurIPS, ECCV, ICCV, ICDM, CIKM, and IEEE Transactions on Image Processing. His research combines methodological advances in machine learning and computer vision with the translation of AI into operational environments.

He has extensive experience leading and contributing to research collaborations with industry, government and community partners. His work has been applied across real estate and property management, urban infrastructure, water utilities, environmental monitoring, energy, and other data-intensive operational environments. His current research includes AI-enabled workflow and decision intelligence, multimodal AI for complex operational data, intelligent agents for real-world applications, and reliable AI systems for decision support.

His research and industry impact have received significant recognition, including the Australian Museum Eureka Prize for Excellence in Data Science, the UTS Medal for Research Impact, the Australian Water Association R&D Excellence Award, and the Charles Sturt University Alumni of the Year Award for Research Excellence.

Wei Liu is a Professor in Artificial Intelligence and the Director of the Future Intelligence Research Lab in the School of Computer Science at the University of Technology Sydney (UTS). He obtained his PhD degree in Machine Learning research at the University of Sydney (USYD). His current research focuses on LLM robustness, model hallucination, and multimodal machine learning. 

Wei has been publishing extensively and consistently in CORE A*/A and Q1 (i.e., top-tier) journals and conferences. He has received 3 Best Paper Awards. In addition, one of his first-authored papers received the Most Influential Paper Award at the CORE A Ranking Conference PAKDD. He has obtained and led significant amounts of research funding, including ARC Discovery Project, government competitive grants, and industry R&D projects.

Wei is a senior member of IEEE, an Area Chair and a Senior PC member of world-leading international Data Mining and Artificial Intelligence conferences, such as the KDD (The ACM SIGKDD Conference on Knowledge Discovery and Data Mining), AAAI (The AAAI Conference on Artificial Intelligence), and ICDM (The IEEE International Conference on Data Mining). He has also been a frequent reviewer for top journals such as TKDE, TPAMI, TNNLS, and TKDD.

More information about Wei's research can be found on his homepage at https://wei-research.github.io/.

I am currently the Associate Head of School Research (ASHOSR) in the School of Computer Science and an Associate Professor at the University of Technology Sydney| Data Science Institute. My research expertise lies in applied Artificial Intelligence for healthier and resilient smart cities, safer transport and e-mobility, and sustainable buildings.

Together with the Future Mobily Lab team, I have secured significant funding across 23 research projects, contributing to more than $26.5M in total funding across Australian partners, plus the €15.6M European Union AUFRANDE programme supporting 64 dual PhD positions across Australian and French universities. Leadership roles include the $2M Australia–Singapore Strategic Collaboration (ARC Linkage/NRF), several iMOVE CRC projects on connected vehicles, automated road star rating and railway level crossing safety, and an ARENA project with Jet Charge, which is the first Australian large-fleet study for at-home charging of commercial fleet operators.

Through close collaboration with industry partners including TfNSW, DoT Victoria, V/Line, Compass IoT, TomTom, AEMO and Jet Charge, my research is applied directly to transport and urban problems. Because of this strong industry engagement, I was externally elected Board Director for ITS Australia in November 2024. I also serve as an IEEE ITSS NSW Area Chair and a member of the IEEE ITSS Board of Governors.

My standalone and collaborative work has attracted 21 awards, prizes and honours (12 competitive awards won), including the 2025 UTS Jenny Edwards Fellowship (one awarded annually across UTS), the 2023 iAwards NSW, the 2022 Women in AI Award Asia-Pacific, the 2018 and 2015 National ITS Awards for Research Excellence, and the 2018 Smart City Awards for On-Demand Transport.

Currently, I am a double finalist in the Women in Digital Awards 2026 for AI and Data Leader.

I have authored/co-authored 80+peer-reviewed publications, with 20+ in Q1/A-ranked IEEE venues, including IEEE ITSC and IEEE Transactions on ITS (the top journal in transportation science). My work has accumulated 2,600+ citations on Google Scholar as of Octpber 2026. Despite two-year maternity leaves, I have maintained research excellence while supervising 9 PhD students (4 as principal supervisor, 5 as co-supervisor) and 50+ undergraduate/postgraduate coursework students.

I have been highly active in the ITS community across Australia and internationally over the past decade, initially at CSIRO Data61 and now at UTS. I have served as a committee member and/or organiser for major conferences, including the ITS World Congress (multiple editions), ITS Australia Summit 2024, IoT Australia Impact Conference 2024, and as ITS Australia Awards judge (2022–2026). I regularly review for ARC schemes (DP/LP/DECRA/ITTC) and premier IEEE venues, while maintaining active public engagement through 50+ speaking events and media interviews with Channel 7 News and The Guardian. This combination of research excellence, industry translation and community leadership positions me to drive transformative impact in intelligent transport systems and future mobility solutions.

More details can be found at: www.simona-mihaita.com

Yuming has strong expertise in data analytics, machine learning, and large language models, specialising in AI-driven solutions across several domains such as transport, real estate, smart cities, and finance. Yuming is recognised for the ability to translate innovative research into practical applications, with a proven track record in industry collaboration with Transport for NSW, Ernst and Young, Microsoft, ACER, Australian Taxation Office, Centrelink, Westpac, Insurance Australia Group (IAG), Property Investors Alliance, Albury City Council, and Mornington Peninsula Shire Council.  He has received multiple awards including 2023 iAwards, finalist of the 2025 ITS Australia Awards, finalist of the 2021 IoT Australia Awards and the finalist of the 2021 ITS Australia Awards 2021.

Dr. Catarina Moreira is a Computer Scientist and Engineer with extensive expertise in deep learning technologies and their societal impacts. She holds the position of Associate Professor in Machine Learning at the Data Science Institute, University of Technology Sydney. Her research interests comprise human-centered AI, multimodal deep learning, explainable AI, and probabilistic graphical models. Dr. Moreira is committed to advancing these fields while addressing their broader societal implications.

Dr. Moreira co-founded the XAMI research initiative (eXplainable Analytics for Machine Intelligence), where she co-leads a team of PhD students dedicated to developing human-interactive probabilistic models. This initiative focuses on creating AI models that are fair, transparent, and trustworthy. Her work in this area addresses critical issues in AI ethics and transparency, fostering the development of reliable and comprehensible systems.

In her role as the UNESCO Co-Chair on Artificial Intelligence (AI) and Extended Reality (XR), Dr. Moreira is instrumental in developing collaborative programs and projects that leverage explainable AI frameworks for medical diagnosis. This position allows her to contribute significantly to the training of future radiologists, ensuring they are equipped with advanced tools and knowledge to excel in their field. Her work in this capacity underscores her commitment to integrating cutting-edge AI technologies with practical medical applications.

She has been recognised for her outstanding contributions to the field, winning the Women in AI Awards: AI in Quantum (2024) and the Women in Technology Awards: The Heart of Our Values Award (2021). Additionally, she was a finalist for the Women in Technology Awards: Rising Star in Technology (2021). 

I am a Research Fellow at the Data Science Institute (DSI) at University of Technology Sydney (UTS). My core research interests lie in the areas of mobile and pervasive computing, multi-modal sensing systems using wearables & IoT devices embodied in the real-life space. I am passionate about research that explores practical solutions targeted at making a positive impact on the lifestyle of humans. My goal is to create innovative, human-centered systems that address global challenges while empowering individuals and communities.

Before joining UTS, I was a Senior Scientist at the Institute of High Performance Computing (IHPC), A*STAR, Singapore and a Research Scientist at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU). I completed my PhD in Computer Science from SMU under the guidance of Prof Archan Misra. During my PhD, I was a visiting research scholar at Carnegie Mellon University (CMU), Pittsburgh, USA from August 2016 to May 2017.

I have served in the Technical Program Committees of prestigious international conferences such as IEEE PerCom 2025, ICDCN 2025, COMSNETS 2021-2025, EWSN 2022-2023, WristSense 2021-2023. I have also been a part of the organizing committees of AutoMLPerSys 2024-2025, IEEE WoWMoM 2024, COMSNETS 2023, ACM UbiComp 2018, ACM MobiSys 2016 in various roles. I’m a regular reviewer of premier journals such as PACM IMWUT, ACM TIoT, Elsevier PMC, Adhoc Networks, IEEE Sensors and top-tier conferences such as IEEE PerCom, ACM ISWC, ACM CHI, IEEE/RSJ IROS, WWW, ACM/IEEE SEC. Recently, I was invited to be in the grant assessment panel by the European Research Council.

I am a recepient of the following honors and awards:

1.  UTS Competitive Early Career Researcher Capability Development Initiative Award, April 2024
2.  Australia's Rising Women in Data Science Stars (among 25 women recognized by Australian Data Science Network and Women in Data Science Worldwide movement), March 2024
3.  Recipient of the Abbe Grant by the Carl-Zeiss-Stiftung Foundation, Germany (among only 30 of the 200 young researchers at the HLF 2023 to receive this grant), Sep 2023.
4.  Young Researcher-10th Heidelberg Laureate Forum -- Among 100 young researchers in Computer Science worldwide to participate in the prestigious HLF 2023, Germany.
5. Best Paper Award, sponsored by Apple Inc. at WristSense 2019 Workshop (co-located with IEEE PerCom 2019).
6. Selected as 'Young Scientist' to attend Global Young Scientists Summit (GYSS 2018), Singapore, Jan 2018.
7. Carnegie Mellon University Overseas Exchange, funding worth USD 100,000 by the Living Analytics Research Centre in SMU. (August 2016- May 2017)
8. Second Best Poster Award,  Xerox Research Centre India Open House Poster Presentation, July 2015.
9. ‘Most Valuable Player Award’ from Infosys Limited, March 2014.
10. Best Outgoing Student-‘Sarasija Thampuran Memorial’ Endowment Award from Rajiv Gandhi Institute of Technology, 2011.
11. University First Rank holder for Bachelor of Technology in Computer Science and Engineering among 1718 students, Mahatma Gandhi University, Kerala, India (July 2011).

Marian-Andrei Rizoiu is a Professor of AI and Behavioral Data Science at the UTS Data Science Institute and Director of the Defence Innovation Network. He leads the Behavioral Data Science lab, where his research addresses one of democracy's pressing challenges: detecting and countering state-sponsored information operations and online misinformation. As DIN Director, he facilitates defence research collaboration across nine NSW and ACT universities, managing a $2.3M annual budget and connecting academic capabilities with defence and industry needs.

His work combines computer science, artificial intelligence, and mathematical modelling to understand how harmful information spreads and influences society. Rather than analysing content, his research detects problematic information through behavioural patterns and writing style—an approach that works across languages and platforms. This research has direct impact: his findings have been implemented in national policy and delivered to government agencies the tools to counter online misinformation that can lead to youth radicalisation.

Marian-Andrei has secured $12.1 million in research funding, including $8.56 million from Defence's Advanced Strategic Capabilities Accelerator across three major projects. He leads a research group of five postdoctoral researchers and eight PhD students who publish in top-tier venues including PNAS, Nature Scientific Data, AAAI, and The Web Conference.

His research has been recognised through multiple awards: two-time finalist for the Australian Museum Eureka Prize for Outstanding Science in Safeguarding Australia (2024, 2025), recipient of the Excellence Award and Academic of the Year at the 2023 Australian Defence Industry Awards, and Best Paper Award at The Web Conference 2025. His work appears regularly in major media outlets including Bloomberg Business Week, Nature Index, BBC, and World Economic Forum.

Beyond academic research, Marian-Andrei translates complex research into public discussion. He has published 18 articles in The Conversation reaching 264,000+ readers, appeared on Dr Karl's "Shirtloads of Science" podcast, and participated in international forums such as SXSW's "Democracy Under Fire" panel alongside Australia's eSafety Commissioner. He regularly engages with government agencies to inform policy on misinformation and information integrity.