###Developing High Speed Retinomorphic Sensors
Project ID: 2228bd1216 (You will need this ID for your application)
Research Theme: Advanced Materials
UCL Lead department: Electronic and Electrical Engineering (EEE)
Lead Supervisor: John Labram
Project Summary:
Why this research is important: Conventional image sensors are designed to reproduce every aspect of the visual field, for example representing brighter regions of a scene as brighter regions in an image. While the benefits of detecting and representing light in this way are obvious, limitations imposed by processing power and frame rate place a fundamental limit on the speed at which this paradigm can be used to identify moving objects. An alternative strategy is to use so called retinomorphic sensors, which output a signal only in response to changes in light intensity, not to constant light intensity, hence inherently identifying movement by design.
What you will be doing: In this project you will design, develop, and characterise new retinomorphic sensors based on thin-film semiconductors. You will deposit semiconductors, dielectrics, and metals to form the device. You will undertake a series of opto-electronic experiments on these retinomorphic sensors. Your objective will be to generate knowledge on their operating principles, and to develop strategies to improve their response speed. Additionally, you will exploit contactless microwave conductivity measurements to enhance understanding of electronic properties of the semiconductor used in these devices. This information will advance reliability and predictability in these devices, and help the community move them towards commercial viability.
Who you will be working with: You will be working with Dr John Labram in the department of Electronic and Electrical Engineering, with strong collaboration at Imperial College London.
Who we are looking for: Candidates must be self-motivated and have received a 2:1 in Electrical Engineering, Materials Science, or Physics, by September 2023.
Further Reading: BBC Science Focus: https://www.sciencefocus.com/news/an-eye-for-an-ai-optic-device-mimics-human-retina/ New Scientist, https://www.newscientist.com/article/2259491-ai-vision-could-be-improved-with-sensors-that-mimic-human-eyes/ Trujillo Herrera et. al. Appl. Phys. Lett., 117, 233501 (2020). Trujillo Herrera and Labram, et. al ACS Appl. Elec. Mater., 4(1) 92–98 (2021).