Researcher

Professor Flora Salim

My Expertise

Prof Salim brings with her a wealth of award-winning research experience, where she investigates the intersection of ubiquitous computing, machine learning, and data science, with specific interests in human-centred AI, behaviour modelling, data-efficient machine learning, and Multimodal Foundation Models (MFMs) for sensor data.

Check our group website for more details: https://cruiseresearchgroup.github.io

Fields of Research (FoR)

Pervasive computing, Stream and sensor data, Machine learning, Deep learning, Artificial intelligence, Neural networks, Context learning, Semi- and unsupervised learning, Cyberphysical systems and internet of things, Data engineering and data science, Human-centred computing, Fairness, accountability, transparency, trust and ethics of computer systems

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Biography

Flora Salim is a Professor in the School of Computer Science and Engineering (CSE),  the inaugural Cisco Chair of Digital Transport & AI, University of New South Wales (UNSW) Sydney, and the Deputy Director (Engagement) of UNSW AI Institute. Her research is on machine learning for time-series and multimodal sensor data and on trustworthy AI. She has received several prestigious fellowships  including Humboldt-Bayer Fellowship, Humboldt...view more

Flora Salim is a Professor in the School of Computer Science and Engineering (CSE),  the inaugural Cisco Chair of Digital Transport & AI, University of New South Wales (UNSW) Sydney, and the Deputy Director (Engagement) of UNSW AI Institute. Her research is on machine learning for time-series and multimodal sensor data and on trustworthy AI. She has received several prestigious fellowships  including Humboldt-Bayer Fellowship, Humboldt Fellowship, Victoria Fellowship, and ARC Australian Postdoctoral (Industry) Fellowship.

She has attracted more than $20m in research and industry funding in the last 10 years, as lead or sole CI for more than half of these grants, including research funded by ARC, Microsoft Research US, Northrop Grumman Corporation US, Qatar National Priorities Research Program, Cisco, IBM Research, several city councils and many other industry and government partners/funders. She is a Chief Investigator on the ARC Centre of Excellence for Automated Decision Making and Society (ADM+S), co-leading the Machines Program and the Mobilities Focus Area. She was the recipient of the Women in AI Awards 2022 Australia and New Zealand in the Defence and Intelligence Category.

She is a member of the Australian Research Council (ARC) College of Experts. She serves as an Editor of IMWUT, Associate-Editor-in-Chief of IEEE Pervasive Computing, Associate Editor of ACM Transactions on Spatial Algorithms and Systems, a Steering Committee member of ACM UbiComp. She has served as a Senior Area Chair / Area Chair of AAAI, WWW, NeurIPS, and many other top-tier conferences in AI and ubiquitous computing.

She is an Associate of ELLIS Alicante and holds an Honorary Professor appointment at RMIT University. She was a Visiting Professor at University of Kassel, Germany, and University of Cambridge, England, in 2019. 

Group website: https://cruiseresearchgroup.github.io; Personal website: florasalim.com ; Twitter: @flosalim ; LinkedIn


My Research Supervision


Supervision keywords


Areas of supervision

The R&D ecosystem through Prof Salim’s Cisco chair role brings in new opportunities for novel research in human behaviour representation learning at multiple scale, given the access to high quality, high volume of multimodal spatio-temporal and mobility datasets from Australian cities, and excellent opportunities to engage with industry and communities to translate the research into real-world contexts of use.

Available PhD Topics:

  • Representation learning of spatio-temporal and/or mobility data
  • Data-efficient learning with multimodal sensor data
  • Multimodal Foundation Models (MFMs), Large Language models (LLMs), graph models, hybrid models for time-series/spatio-temporal/mobility data
  • Edge AI / machine learning on the edge
  • Graph embedding for spatio-temporal / POI recommendation
  • Human-centric behaviour learning with AI+IoT/wearables for applications in the future of transport/mobility and the associated areas

To apply, please submit the following documents to flora.salim@unsw.edu.au.

  • a cover letter (research statement), addressing the criteria and topics in the call.
  • a CV that includes any publications/awards and the contact details of 2 referees.
  • a copy of electronic academic transcripts.
  • a short brief or abstract of research proposal, to be developed further after successful interview.

My Engagement

A sample of news coverage and/or interviews

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