Educational research projects include:
•Electric circuits and EKGs
•Bioelectrical Impedance Analysis
We are developing and assessing innovative curriculum for introductory physics for the life science (IPLS) with a particular focus on pre-health students. Some guidelines that address the need for such a curriculum can be found for example in the IPLS Conference Report and the AAPT Recommendations for the Undergraduate Physics Laboratory Curriculum. We try to address some fundamental challenges and opportunities in undergraduate STEM education:
Digital sensors are ubiquitous in today's society and found in place ranging from the Hubble space telescope to cell phones.There are two main types of digital sensors:
Charge-Coupled Devices (CCDs) and Complementary Metal–Oxide–Semiconductors (CMOS).
Dr. Widenhorn studies the performance of these sensors with the goal to understand the characteristics better and improve image quality. We investigate the characteristics and performance of CMOS active pixel sensors and CCD imagers used in cell phones, regular consumer cameras, and scientific applications. Past and current projects include:
Since the advent of digital cameras a source of noise due to heat, called dark current, has been a pernicious unwanted signal in images taken by astronomers, scientists, and photographers. We study this noise, what causes it, its peculiarities, and maybe most importantly, how best to remove it. Our publications include an algorithm that removes the dark current based upon the pixels with the greatest amounts of dark current. These pixels, so called hot pixels, can essentially be used as thermometers to predict the amount of noise that should be removed from all the other pixels. Additionally, we have reported on a particular type of pixel that actually produces different amounts of dark noise when illuminated with light than when the shutter is closed. These pixels produce dark current non-linearly with respect to exposure time, a complication as scientists and astronomers rely upon the linear signal to make accurate measurements. We have produced a model that attempts to explain how this behavior can be explained by the presence of an impurity located in a very particular region of the pixel.