Ali Javey (Advisor)

The concept of electronic nose first made its emergence in the 1980s. Recent advances in machine learning have led to a resurgence of research interest in this topic. However, state of the art sensors still lack selectivity and sensitivity when it comes to differentiating gases of similar compositions. In this work, we explore methods to create multiplexed gas sensors that can differentiate these mixtures with high accuracy and long-term stability.

Project currently funded by: Federal

Normal scenes captured by cameras involve light intensities spanning more than five orders of magnitude, which is often taken care of with auto-exposure/multiple exposures in high dynamic range (HDR) imaging technologies. Such technologies assign one or several uniform exposure levels and dynamic ranges for all pixels in the image, significantly squeezing the data precision for dimmer regions, causing fundamental information loss at the photodetection stage.

Ideally, each detector should independently decide its tradeoff between responsivity and speed. For...

Multispectral and hyperspectral imaging are important optical inspection technologies. They collect the spatial and spectral information of the incidental light into 3D hypercubes, which can be post-processed into material and structural mapping of the scene. However, acquiring and analyzing the 3D hypercubes set great challenges in data collection, transportation, storage, and computation. The much higher energy, bandwidth, and memory budgets limit the implementation of high-speed, high-resolution hyperspectral imaging to achieve intelligent machine vision. This project introduces an...