I am a researcher at Inception Institute of Artificial Intelligence in Abu Dhabi, UAE, and a research collaborator with the Imagine group (imagine.med.harvard.edu) led by Prof. Ali Gholipour. With Imagine lab, I am working on in utero motion-robust diffusion imaging of the developing fetal white matter. At Inception, I am working on Machine Learning problems that are interesting from the medical imaging perspective, such as learning from low amount of data, and modeling the uncertainty in neural network outputs.
Update: Our paper on using extreme points derived confidence map to do interactive segmentation using neural networks was accepted (early accept) at MICCAI 2019.
Update: Our NeuroImage paper on fetal brain DTI atlas computed using in utero images is now online.
Update: Our MICCAI 2018 paper on methods to compute group differences in DTI of in utero fetal cohorts is now online. We compared a fetal cohort diagnosed with some form of congenital heart disease against a healthy fetal chorot.
My research interests are in the area of Medical Image Computing and Machine Learning in Medicine. At present, I am working on development of high performance computing algorithms for motion-robust diffusion-weighted and structural imaging to study fetal brain development. This research work will potentially enable us to detect abnormalities in fetal brain development that can help prepare the clinicians and parents for dealing with baby's health issues upon birth. In addition, I am applying Deep Learning techniques for solving segmentation and registration problems arising in fetal MR imaging, among other problems.
Previously, I obtained my Ph.D. in Engineering Sciences from Thayer School of Engineering at Dartmouth College in June 2016. During my Ph.D., I was advised by Prof. Ryan Halter at The Center for Clinical Applications of Bioimpedance. At Dartmouth, I was fortunate to be a recipient of the Neukom Graduate Fellowship, and Outstanding Graduate Research in Computational Sciences award. For my Ph.D. work, I used an electrical impedance tomography system that I developed to spectroscopically analyze the impedance contrast between benign and cancerous prostatic tissues. Additionally, I developed computer vision tools to assist an image-guided cancer resection procedure during robot-assisted radical prostatectomy. My PhD research exposed me to Medical Instrumentation, Medical Imaging, Statistical Analysis of Clinical Data, as well as Computational Science research. To further my experience in computational work, I joined the Computational Radiology Lab in Sept. 2016.
During 2006-2010, I was an undergraduate student at Manipal University, India, where I obtained a B.E. degree in Electrical Engineering from Manipal Institute of Technology, India. I did my Bachelors' thesis research work at Instituto Superior Tecnico, in Lisbon, Portugal, with Prof. Joao Sanches and Prof. Rodrigo Ventura in the area of computational pathology.
I can be reached at: skhan [dot] shadab [at] gmail for any questions or comments.