Flora Salim is an Associate Professor at RMIT University, Melbourne, Australia. She leads the Context Recognition and Urban Intelligence (CRUISE) group, working on context and behaviour recognition, time-series and spatio-temporal data mining, and applied machine learning (and deep learning) for smart cities, smart buildings, and smart mobility, using IoT, sensor, and multimodal data. She is a Deputy Director of the RMIT Centre for Information Discovery and Data Analytics. She is a Humboldt Fellow, awarded by Alexander von Humboldt Foundation. She is also a Victoria Fellow 2018, a highly-competitive merit-based award from the Victorian Government. She is the recipient of the RMIT Award for Research Impact - Technology 2018. She received the RMIT Vice-Chancellor's Award for Research Excellence – Early Career Researcher in 2016. Previously, she was an Australian Research Council (ARC) Postdoctoral Industry (APDI) Fellow in 2012-2015. Prior to that, she was a postdoc in Spatial Information Architecture Lab. She obtained her PhD from Monash University in 2009. Prior to her PhD, she was a Senior Software Engineer at mediaproxy. She is an Editorial Board member (Area Editor) of Pervasive and Mobile Computing. She is an Associate Editor of the PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), the journal publication of Ubicomp.
Investigate crowd monitoring and situation
recognition techniques, efficiently leveraging
UAV videos and complementary urban sensors.
Scenarios: FIFA World Cup 2022
Cortana Intelligence Institute (CII) is driving the next-generation of capabilities for Microsoft’s digital assistant, Cortana. Focused on researching work-related tasks and using sensors in mobile phones, the CII team builds a complex multidimensional data set, used to model and predict user’s work-related tasks.
Measure multiple dimensions of high school student’s emotional, behavioural and cognitive learning engagement with sensing data in the wild
Derive activity, physiological, and environmental factors contributing to various dimensions of student learning engagement
This project will deploy machine learning to human behaviour and building operational data obtained through Activity Based Working (ABW), aimed at providing insights towards optimising and personalising ABW. The outcome is a cloud-based integrated platform, with tailored ABW apps, for capturing and analysing occupancy behaviour and building performance data.
In response to the urgent need for more site specific and vertical environmental information to inform the design of sustainable urban design, this project investigates the use of Micro Air Vehicles (drones) equipped with diverse lightweight sensing equipment to gather site specific environmental sensor data.
Today, we are faced with the increasing growth of ubiquitous sensors in various fields, generating an enormous amount of time-series. This growing number of sensor-based time-series applications require new approaches in data mining, knowledge discovery, and ubiquitous computing.
Cortana Intelligence Institute is a co-funded initiative between Microsoft Research, Cortana Research and RMIT University, which will drive the next-generation of capabilities for Microsoft’s digital assistant, Cortana.
This research aims to develop a framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services. - ARC Discovery Project DP190101485
This project that is funded by Northrop Grumman Corporation investigates the patterns of ground vehicles and aircraft trajectories, combining the analysis of their spatial movement behaviours and contextual information. We utilise state-of-the-art artificial intelligence and big data analytics techniques to clean, preprocess, and analyse sizeable on-ground aircraft GPS data. We also establish a context-aware system to predict the delay time of each aircraft by developing a novel Airport Traffic Complexity (ATC) model.
The Mornington Peninsula Shire (MPS) will develop a Smart Technology project to address growing demand on parking and amenity facilities in towns particularly with high tourist attraction. There is an increasing pressure to understand the volume of pedestrians, public transport users, and road users (in particular, private vehicle drivers) throughout the major townships in MPS and meet the increasing demand.
The modeling of social and mobility networks continues to gain importance in a variety of fields ranging from epidemiology social group and community detection, to user movement and behavior understanding.
Flora is on research leave from RMIT. She is currently on the Humboldt-Bayer Fellowship (experienced fellow / visiting prof), supported by Alexander von Humboldt Foundation and Bayer Foundation, at University of Kassel, Germany, from August 2019 to Feb 2020. More info..
© 2021 Flora Salim - CRUISE Research Group.