What I do
- Visualization prototyping, design and toolkits
- Exploratory analysis techniques, data quality assessment
- Geo-spatial data, trajectories, urban data, sports data, deep learning
- Art, design, and creative visualization designs
I’m hiring! Check out my current job openings:
2-year Post-Doc / Research engineer in video tracking (Projet Neptune)
1-year Engineer in video storage and sharing architecture (Projet Neptune)
1-year Engineer in Network and Data Management (Projet DataGora)
- » April 2020 - I was involved in building a dataviz dashboard for researchers behind the COVID NMA dataset to monitor current trials on COVID-19.
- » March 2020 - our paper on 3D shapes intearactions in VR was (virtually) presented at IEEE VR 2020 by François Homps and Yohan Beugin.
- » March 2020 - our paper on space-time occupation models in Basket was presented at MIT Sloan paper in Boston by Gabin Rolland.
- » January 2020 - a new project "NEPTUNE" on visualization and video tracking to improve elite swimmers just kicked off.
NEPTUNE - Improving Swimming Performance
DataGora - experimenting new modalities of interaction, understanding and decision support around data.
MI2 - Improving urban mobility
Amigo - Collaborative platform
Theo Jaunet (2018 - 2021 French ministry PhD fellowship)
Transparency and Explainability for Machine Learning
Liqun Liu (2018 - 2022 CSC Fellowship)
Visualizing Traffic Light Strategies in Smart Cities
Nicolas Jacquelin (2019 - 2022 CNRS scholarship)
Video Analysis for Sport Movement Analysis
Urban Mobility (MI2): A major current and future challenge for cities is to improve human urban mobility. Both for reasons of comfort, well-being and public health (stress, accidents, pollution). LIRIS is involved over the period 2017-2020 in a consortium of companies expert in the collection and storage of data related to passenger mobility in public transport, cars and bicycles. Learn more about the project here. It started in Fall 2017 and has numerous open positions available right now.
Visual Analytics (VisTics): We chrome-vs-code at pushing the envelope of Visual Analytics tools and methods, by building a high performance infrastructure for visual exploration and steering of predictive models. The funding comes from a research starting grant Impulsion 2017 and will last one year (starting January 2017).
3D Motion Capture Visualization & Analysis (Amigo): École Centrale de Lyon has just acquired a state-of-the-art motion capture platform. We are interested in finding motion patterns and building predictive models, using interactive visualizations. Details on the platform and preliminary results are available. We are also interested in building benchmark datasets of annotated motions.