Sensing and Processing for IoT and AI — Research


Our research focuses along two main lines (pages include MS thesis topics):

  1. Indoor human localization and identification using low-power low-cost long-distance capacitive sensors
  2. Acceleration of software applications via high-level synthesis on FPGAs

The research is funded both from internal sources and from European projects, such as:

  • ECOSCALE – Energy-efficient heterogeneous COmputing at exaSCALE
  • WSN-DPCM – WSN Development, Planning and Commissioning & Maintenance Toolset
  • PHARAON – Parallel and Heterogeneous Architecture for ReAl-time cOmputiNg
  • COMPLEX – COdesign and power Management in PLatform-based design space EXploration
  • MODERN – MOdeling and DEsign of Reliable, process variation aware Nanoelectronic devices, circuits and systems
  • HEAP – Highly Efficient Adaptive multi-Processor framework
  • FastCUDA  – Open Source FPGA Accelerator and Hardware-Software Co-design Toolset for CUDA Kernels