Research in real-time dependable systems and risk assessment
My objective is to contribute to the techniques, tools and computing platforms that will make it possible to build provably safe systems in a time and cost efficient manner, with applications to:
- Automotive and aerospace embedded systems: generative design with machine learning & timing and dependability verification
- Risk assessment: quantify risks using probabilistic models built from historical data
12/2018: Phd positions in the design of automotive electrical and electronic architectures in partnership with a leading automotive OEM. Applicants with a M.S. degree in CS, EE or applied mathematics are invited to submit CV, research statement (describing research experience if any) and a letter of motivation.Candidates selected for the second round will have to provide 2 letters of reference.
Highlights / Selected works
- A selection of recent works:
- Machine learning to speed-up the verification of Ethernet TSN networks in design-space exploration - study available here as well as a follow-up work.
- "Formal Analysis of the Startup Delay of SOME/IP Service Discovery", Design, Automation and Test in Europe (DATE2015), Grenoble, France, March 13-15, 2015.
- “Lean Model-Driven Development through Model-Interpretation: the CPAL design ﬂow”, Embedded Real-Time Software and Systems (ERTS 2016), Toulouse, France, January 27-29, 2016.
- "Multi-source software on multicore automotive ECUs - Combining runnable sequencing with task scheduling", IEEE Transactions on Industrial Electronics, 2012.
- Communication networks for dependable systems:
- Timing QoS protocols on top of Ethernet TSN (slides)
- Scheduling frames with offsets provides a major performance boost on CAN (slides)
- Configuration of FlexRay networks (slides)
- Fine Tuning MAC Level Protocols for Optimized Real-Time QoS
- Optimal configuration of TDMA / TTP/C networks - (slides)
- Probabilistic analysis of CAN fault-confinement mechanisms
- Patents on communication networks: FR2976432 - FR2976434 - FR2976435.
- Low-power scheduling:
- Financial engineering