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, Multimodal Foundation Models (MFMs), small LMs and VLMs, continual learning, and applications of AI for climate, weather, earth systems modelling, and energy, grid, transport and mobility systems.
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 systemsSEO tags
Biography
Flora Salim a full Professor in the School of Computer Science and Engineering at the University of New South Wales (UNSW) Sydney, where she also serves as the Deputy Director (Engagement) of the UNSW AI Institute. Her work focuses on multimodal machine learning and foundation models for time-series and spatio-temporal data, behavioural modelling with multimodal sensors and wearables, robust and trustworthy machine learning, and on...view more
Flora Salim a full Professor in the School of Computer Science and Engineering at the University of New South Wales (UNSW) Sydney, where she also serves as the Deputy Director (Engagement) of the UNSW AI Institute. Her work focuses on multimodal machine learning and foundation models for time-series and spatio-temporal data, behavioural modelling with multimodal sensors and wearables, robust and trustworthy machine learning, and on applications of AI and LLMs for smart and sustainable cities, and for mobility, transport, energy, and grid systems. She has received multiple nationally and internationally competitive fellowships, such as Humboldt Fellowship, Bayer Fellowship, Victoria Fellowship, ARC Australian Postdoctoral Industry (APDI) Fellowship, and many accolades and awards such as the Women in AI Award Australia and New Zealand (2022) and IBM Smarter Planet Industry Innovation Award.
She is a member of the Australian Academy of Sciences’ National Committee for Information and Computing Sciences and an elect member of the Australian Research Council (ARC) College of Experts. She is a Vice Chair of the IEEE Task Force on AI for Time-Series and Spatio-Temporal Data. She serves in the editorial board of ACM TIST, ACM TSAS, PACM IMWUT, IEEE Pervasive Computing, and Nature Scientific Data, and has served as a senior reviewer or area chair for NeurIPS, ICLR, WWW, and many other top-tier conferences in AI and ubiquitous computing.
Prof Salim is a Chief Investigator on the Australian Research Council (ARC) Centre of Excellence for Automated Decision Making and Society (ADM+S), co-leading the Mobilities Focus Area. She is also a Key Chief Investigator in the ARC Training Centre for Whole Life Design for Carbon Neutral Infrastructure, leading the Program on Machine Learning for Carbon Performance. She has worked with many industry and government partners, and managed large-scale research and innovation projects, leading to several patents and deployed systems locally and globally.
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) in 2019-2020, and University of Cambridge (England) in 2019.
Group website: https://cruiseresearchgroup.github.io; LinkedIn
My Research Supervision
Supervision keywords
Areas of supervision
Available PhD Topics:
- Multimodal machine learning
- Continual multimodal learning
- Small LMs and VLMs
- 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
- Human-centric behaviour learning with AI+IoT/wearables for augmented reality, smart glasses, wearables
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
- On winning Women in AI Awards 2022 in Defence and Intelligence category (Interview with Campus Review)
- COVID-19 diagnostics from cough sounds(Startup Daily article; Research highlights by ARC)
- Our work with Mornington Peninsula Shire (interview with Pace Today)
- Our work on smart cities with City of Melbourne (IoT Hub article)
- AI sheds light on workplace productivity (Property Council of Australia's feature article)
- AI and sensing system to predict concentration at open-plan workplaces (article on TechXplore)
- Personality traits prediction using mobile sensor data (article on ZDNet)
- Microsoft Cortana Intelligence Institute's next generation productivity assistant (news release by Microsoft)
- Crime prediction in Australian and US cities (Brisbane Times; Herald Sun)
- On privacy and tracking (an interview with ABC)
- On Women in IT (SBS interview)
Contact
Publications
ORCID as entered in ROS
https://orcid.org/0000-0002-1237-1664