Use geospatial data and develop data products to help cities adapt to climate change, reduce exposure to climate hazards, effectively manage their natural resources and reduce their greenhouse gas emissions.

Responsibilities include:

• Research, design, prototype and deploy scalable data products and platforms by providing insights related to climate risks impacts, climate actions, biodiversity monitoring and urban development challenges.
• Guide development, maintenance and updates of multiple data products and tools

Responsibilities include:

• Build an open source project for standardizing climate open data at multiple geospatial scales.
• Build and manage a community of 30 data specialists volunteers
• Data Product management (roadmap, issues, tasks…)
• Project description

Responsibilities include:

• Accompanying companies in the design, development and deployment of Data and AI products
• Working with Data Architects/Scientists/Engineers to design robust data pipelines: integration, storage, analytics and visualization
• Specification and documentation of Data Product’s features
• Feeding backlog with prioritized features/USs and managing product roadmap

Responsibilities include:

• Leading Data Science team and responsible of Data Analytics products
• Deployment of Location Intelligence and Smart Building Analytics solution providing our clients with insights about building usage and occupancy, visitors behaviors and environmental quality
• Conception and development of Data Science product based on big data technologies: real time data collection and profiling, data catalog management, automated data cleaning, spatio-temporal modeling and aggregation, KPI’s Geo-visualization…
• Defining product roadmap and strategies, feature prioritization based on clients needs, Backlog management and User stories definition, sharing product vision
• Technical and functional documentation and communication about our product features

Responsibilities include:

• Develop several data science POCs and produce statistical analysis and reports to our clients for extracting reliable insights from their raw geospatial data
• Anomaly and noise detection in wifi geolocation data
• Trajectory interpolation: map matching, kd-tree, dijkstra shortest path implementation, graph theory
• Trajectories aggregation and clustering: sequence mining, Dynamic Time Wrapping implementation

Responsibilities include:

• Participation to European Research project “ANYWHERE”: EnhANcing emergencY management and response to extreme WeatHER and climate Event funded within EU’s Horizon 2020 research and innovation program: http://anywhere-h2020.eu/
• Statstical analysis of population exposure to Natural Hazards

Publications:

• Floods: Anticipating or Coping: Behaviors in the Face of Flash Floods (https://www.sciencedirect.com/science/article/pii/B9781785482694500184)
• Mobility in the Face of Extreme Hydrometeorological Events 2: Assigning Travel-Activity Patterns Based On Socio-Demographics for Flood Risk Assessment (https://www.sciencedirect.com/science/article/pii/B9781785482908500055)
• Mobility in the Face of Extreme Hydrometeorological Events 2: When Driving to Work Becomes Dangerous (https://www.sciencedirect.com/science/article/pii/B9781785482908500043)

Responsibilities include:

• Data management: collecting socio-environmental data and managing geospatial data base: national census data, national mobility and traffic data, social interviews, roads and hydrographic networks, hydrological simulation outputs, weather forecast data, precipitation, weather alerting data…
• Statistical analysis: descriptives statistics, data cleaning and anomaly detection, time series analysis, pattern recognition, spatio-temporal aggregation, text mining, sequence mining, graph analysis, geo-visualization, geo-statistics, probability propagation, inference systems
• Development of a mobility simulation model within R: agent-based simulation, activity-based modeling, discrete-event simulation, regression tree, machine learning
• Development of a model of decision_making under risk and uncertainty: risk modeling, decision theory, bayesian network, probabilistic models

Scientif papers:

• MobRISK: a model for assessing the exposure of road users to flash flood events (https://hal.archives-ouvertes.fr/hal-01698477)
• Assessment of commuters’ daily exposure to flash flooding over the roads of the Gard region, France (https://www.sciencedirect.com/science/article/pii/S002216941630004X)
• Extrêmes hydro-météorologiques et exposition sur les routes : Contribution à MobRISK : modèle de simulation de l’exposition des mobilités quotidiennes aux crues rapides (https://tel.archives-ouvertes.fr/tel-01562815/document)