The development of internet of things and artificial intelligence induces the rapid growing of sensory nodes which generates a large portion of unstructured and redundant raw data. In the conventional design, the analogue sensory data are initially transformed into digital data with analogue-to-digital conversion, then stored in memory unit. The computational task is further performed by transferring the digital data between memory and local computation unit. The architecture of separated sensor, memory and data processing units results in the data-accessing latency and relatively high-power consumption. Alternatively, biomimetic sensor computing inspired by the biological sensory system have been proposed to improve energy, area and time efficiency. The focus of Prof. Su-Ting Han‘s research is to address this challenge by computing with the emerging functional devices.