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Postdoctoral Researcher
Mohammad Shafkat Islam
Postdoctoral Research Associate
School of Data Science
Email: vwp4tr@virginia.edu
Shafkat is a data scientist, with expertise in deep learning and machine learning. He applies deep learning and machine learning to solve real-life medical imaging problems. Shafkat’s educational background is in electrical and computer engineering.
Shafkat joined the school of data science as a postdoctoral research associate in 2022. He previously worked as a postdoctoral fellow at the Children’s Hospital of Philadelphia. His research interests include deep learning, machine learning, medical imaging, image segmentation, and object detection. Currently he is developing vision transformer and semi-supervised approach for neuronal morphology detection and segmentation.
Shafkat holds a Ph.D. in Electrical and Computer Engineering from The University of Iowa and a B.Sc. in Electrical and Electronic Engineering from Chittagong University of Engineering and Technology, Bangladesh.
Education
- Ph.D. in Electrical and Computer Engineering, University of Iowa
- M.S. in Electrical and Computer Engineering, University of Iowa
- B.S. in Electrical and Electronics Engineering, Chittagong University of Engineering & Technology
Data Science Domains
Analytics, Design
Methodologies
Deep Learning, Machine Learning
Selected Publications
Islam, M.S., Wang, J.K., Johnson, S.S., Thurtell, M.J., Kardon, R.H. and Garvin, M.K., 2020. A deep-learning approach for automated OCT en-face retinal vessel segmentation in cases of optic disc swelling using multiple en-face images as input. Translational vision science & technology, 9(2), pp.17-17.
Islam, M.S., Wang, J.K., Deng, W., Thurtell, M.J., Kardon, R.H. and Garvin, M.K., 2020. Deep-learning-based estimation of 3D optic-nerve-head shape from 2D color fundus photographs in cases of optic disc swelling. In Ophthalmic Medical Image Analysis: 7th International Workshop, OMIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings 7 (pp. 136-145). Springer International Publishing.
Johnson, S.S., Wang, J.K., Islam, M.S., Thurtell, M.J., Kardon, R.H. and Garvin, M.K., 2018. Local estimation of the degree of optic disc swelling from color fundus photography. In Computational Pathology and Ophthalmic Medical Image Analysis: First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018, Proceedings 5 (pp. 277-284). Springer International Publishing.
Bhuiyan, M.A.M., Islam, M.S. and Datta, A.J., 2012. Modeling, simulation and optimization of high-performance CIGS solar cell. International Journal of Computer Applications, 57(16).