- 09/2017: I released a PyTorch implementation of Clickhere CNN and Render For CNN .
- 06/2017: I gave a talk at the 37th Soar workshop on my current research project.
- 06/2016: I gave a talk at the 36th Soar workshop on the block design task project.
- 07/2016: I presented a poster at CogSci 2016. (paper)
I am interested in the problems that lie at the intersection of computer vision and cognitive science.
I am currently working on tackling the following question;
Can an agent use its reasoning and interaction capabilities to improve its perception ? I am approaching this
question by exploring possible integrations between convolutional neural networks and the Soar cognitive architecture.
I organize the Computational Cognitive Science reading group.
A pilot study of a modified bathroom scale to monitor cardiovascular hemodynamic in pregnancy
Mohamed El Banani,
Journal of the American College of Cardiology, 2016
We showed that the ballistocardiogram (BCG) signal - the heart beat induced repetitive movements of the
body due to acceleration of blood as it is ejected into the large vessels - can be measured using a modified bathroom scale.
We used the scale to acquire serial measurements of BCG waveforms during pregnancy to assess maternal cardiovascular adaptation
, including changes in cardiac output (CO), cardiac contractility (CC) and heart rate (HR).
Three-Dimensional Particle Tracking in Microfluidic Channel Flow using In and Out of Focus Diffraction
Mohamed El Banani,
Journal of Flow Measurement and Instrumentation, 2015
Three-dimensional particle tracking is important to accurately understand the motion of particles within complex flow fields.
We show that three-dimensional trajectories of particles within microfluidic flow can be extracted from two-dimensional bright
field video microscopy. The method utilizes the defocusing that occurs as particles move out of the objective focal plane when
viewed through a high numerical aperture objective lens.