Flora Salim is a Professor in the School of Computing Technologies, RMIT University, Melbourne, Australia, the co-Deputy Director of RMIT Centre for Information Discovery and Data Analytics (CIDDA), and an Associate Investigator of ARC Centre of Excellence in Automated Decision Making and Society.
Flora leads the IoT Analytics node, or the Context Recognition and Urban Intelligence (CRUISE) group.
Her research interests include human behaviour modelling, time-series and spatio-temporal data mining, machine learning on stream and sensor data, ubiquitous computing, and smart cities.
She was a Humboldt-Bayer Fellow (from Bayer Foundation GmbH), Humboldt Fellow -experienced researcher (from Alexander von Humboldt Foundation), Victoria Fellow 2018 (from Victorian government).
She was the recipient of the the RMIT Vice-Chancellor's Award for Research Excellence–Early Career Researcher 2016; the RMIT Award for Research Impact - Technology 2018; Victorian iAwards (2014), Australian Research Council (ARC) Postdoctoral Research Industry (APDI) Fellow (2012-2015); IBM Smarter Planet Industry Skills Innovation Award (2010). She serves as an Associate Editor of the PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), an Area Editor of Pervasive and Mobile Computing journal, and a Steering Committee member of ACM UbiComp.
Prof. Salim has received several ARC Linkage, a Discovery, and numerous international industry grants, including from Microsoft Research, Northrop Grumman Corporations, and Qatar National Research Funds. She was a Visiting Professor at University of Kassel, Germany, and University of Cambridge, UK, in 2019.
- Saeed, A.,Salim, F.,Ozcelebi, T.,Lukkien, J. (2021). Federated Self-Supervised Learning of Multisensor Representations for Embedded Intelligence In: IEEE Internet of Things Journal, 8, 1030 - 1040
- Ali, A.,Salim, F.,Kim, D.,Neia, A.,Bouguettaya, A. (2021). (In Press) Drone-as-a-Service Composition Under Uncertainty In: IEEE Transactions on Services Computing, , 1 - 14
- Gao, N.,Shao, W.,Saiedur Rahaman, M.,zhai, j.,David, K.,Salim, F. (2021). Transfer learning for thermal comfort prediction in multiple cities In: Building and Environment, 195, 1 - 12
- Bedogni, L.,Rumi, S.,Salim, F. (2021). Modelling Memory for Individual Re-identification in Decentralised Mobile Contact Tracing Applications In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 5, 1 - 21
- Dong, B.,Liu, Y.,Salim, F.,Xue, H., et al, . (2021). Occupant behavior modeling methods for resilient building design, operation and policy at urban scale: A review In: Applied Energy, 293, 1 - 17
- Shao, W.,Chan, J.,Salim, F. (2020). Approximating Optimisation Solutions for the Travelling Officer Problem with Neural Networks In: Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, United Kingdom, 19-24 July 2020
- ., M.,Salim, F.,Ren, Y.,Chan, J.,Tomko, M.,Sanderson, M. (2020). Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors In: ACM Transactions on Sensor Networks, 16, 1 - 25
- Gao, N.,Shao, W.,Saiedur Rahaman, M.,Salim, F. (2020). N-Gage: Predicting in-class Emotional, Behavioural and Cognitive Engagement in the Wild In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4, 1 - 26
- Deldari, S.,Smith, D.,Sadri, A.,Salim, F. (2020). ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for Processing Heterogeneous Sensor Data In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4, 1 - 24
- Schwee, J.,Sangogboye, F.,Salim, F.,Kjærgaard, M. (2020). Tool-chain for supporting Privacy Risk Assessments In: BuildSys 2020 - Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Japan, 18-20 November 2020
- C4NET Demand Response initiative – Industrial and Commercial Demand Flexing to Increase Overall Benefit (“INFLEXION”) (Administered by Federation University). Funded by: Centre for New Energy Technologies (C4NET) from (2021 to 2022)
- 53. Precinct level (or city level) energy use prediction using building data and other data sources. Funded by: Centre for New Energy Technologies (C4NET) from (2021 to 2022)
- NEXUS: Explainable and Unified Spatial Reasoning and Sensor Fusion (Phase 2). Funded by: Defence Science and Technology Group - Contract from (2020 to 2022)
- Drone-based crowd monitoring Qatar National Research Fund Application - DroneCMS: Flying Infrastructure for Intelligent Crowd Management and Security for Mega Events (Administered by Qatar University).. Funded by: Qatar National Research Fund (ONGOING) from (2020 to 2022)
- Mornington Peninsula Smart Parking and Amenities for High Demand Areas (administered by Mornington Peninsula Shire Council). Funded by: Smart Cities and Suburbs Program - 2017 onwards from (2019 to 2020)
10 PhD Completions10 PhD Current Supervisions