We investigate a large area in the hardware/software co-design methodology for mobile embedded systems. In particular, we are interested in the model-based temperature-, power- and reliability-aware design of such multi-core embedded systems.

We study the analysis and optimization of the transiently powered systems with NVM/NVP. In particular, we are interested in guaranteeing the real-time schedulability even with the existence of uncertainty in power supply.

We study the optimization of machine learning (ML) workloads on top of embedded or cyber-physical systems, which are typically associated with a number of non-functional design concerns such as limited power/memory budgets or real-time constraints. 

We study the cost effective solution to the enhancement of the reliability and life-time of the satellite embedded systems. Further, we seek to find a SW solution to maintain the battery healthiness, which is known to be the bottleneck of life-time of satellite systems.