Professor Flora Salim
Professor

Professor Flora Salim

Engineering
Computer Science and Engineering

Professor Flora Salim is the inaugural CISCO Chair of Digital Transport, UNSW Sydney. Her research sits in the cross-cutting areas of ubiquitous computing, machine learning, and data science, with specific interests on representation learning of spatio-temporal and mobility behaviours and data-efficient learning with multimodal sensor data. Her recent research focus includes self-supervised learning, machine learning for multimodal time-series, explainable AI, fair machine learning, with specific applications on mobility data science and personalised recommender systems for smart cities/buildings/transport/energy, smart environments, and intelligent task assistants. Her research has been funded by Australian Research Council (ARC), Victorian Government, Microsoft Research US, Northrop Grumman Corporation US, Rheinmetall Defence Australia, Qatar National Priorities Research Program, IBM Research, Alexander von Humboldt Foundation, Bayer Foundation, several city councils, and many other industry and government partners/funders. She is the recipient of Women in AI Awards 2022 Australia New Zealand in the Defence and Intelligence category. She has received several fellowships in the past, including Humboldt Fellowship,  Humboldt-Bayer Fellowship, Veski Fellowship, and ARC Postdoctoral Industry (APDI) Fellowship. She obtained her PhD from Monash University in 2009.

She serves as a member of the Australian Research Council (ARC) College of Experts. She is an Associate Investigator of the ARC Centre of Excellence in Automated Decision Making and Society. She serves as a Steering Committee member of ACM UbiComp, Associate Editor of the PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Area Editor of Pervasive and Mobile Computing. She has served as a senior PC member of premier AI and data science conferences including AAAI, CIKM, WWW. She was the PC Co-Chair of UbiComp 2020 and PerCom 2018.

She holds an Honorary Professor appointment at RMIT University. Until recently, she was the co-Deputy Director of RMIT Centre for Information Discovery and Data Analytics. She was a Visiting Professor at University of Kassel, Germany, and University of Cambridge, England, in 2019. 

Personal website: florasalim.com ; Twitter: @flosalim ; LinkedIn

Location
K17
  • Journal articles | 2022
    Hamdi A; Shaban K; Erradi A; Mohamed A; Rumi SK; Salim FD, 2022, 'Spatiotemporal data mining: a survey on challenges and open problems', Artificial Intelligence Review, vol. 55, pp. 1441 - 1488, http://dx.doi.org/10.1007/s10462-021-09994-y
    Journal articles | 2020
    Kaur M; Salim FD; Ren Y; Chan J; Tomko M; Sanderson M, 2020, 'Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors', ACM Transactions on Sensor Networks, vol. 16, http://dx.doi.org/10.1145/3393692
    Journal articles | 2020
    Shao W; Tan S; Zhao S; Qin KK; Hei X; Chan J; Salim FD, 2020, 'Incorporating LSTM Auto-Encoders in Optimizations to Solve Parking Officer Patrolling Problem', ACM Transactions on Spatial Algorithms and Systems, vol. 6, http://dx.doi.org/10.1145/3380966
    Journal articles | 2018
    Arief-Ang IB; Hamilton M; Salim FD, 2018, 'A scalable room occupancy prediction with transferable time series decomposition of CO2 sensor data', ACM Transactions on Sensor Networks, vol. 14, http://dx.doi.org/10.1145/3217214
    Journal articles | 2018
    Hashem T; Hasan R; Salim F; Mahin MT, 2018, 'Crowd-enabled Processing of Trustworthy, Privacy-Enhanced and Personalised Location Based Services with Quality Guarantee', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 2, pp. 1 - 25, http://dx.doi.org/10.1145/3287045
  • Conference Papers | 2021
    Xue H; Salim FD, 2021, 'TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 741 - 753, http://dx.doi.org/10.1007/978-3-030-75762-5_58
    Preprints | 2020
    Kaur M; Salim FD; Ren Y; Chan J; Tomko M; Sanderson M, 2020, Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors, http://dx.doi.org/10.1145/3393692

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