saeed3@mail.usf.edu

ENB building

4202 E. Fowler Avenue
     Tampa, FL 33620 USA

Bio

I am a thrid year CSE Ph.D. candidate at the University of South Florida. I am part of the Computer Vision research group and Radiomics Group at MOFFITT CANCER CENTER . I am advised by Professor: Dmitry Goldgof and Professor: Lawrence Hall


Research Interests

My research interests include Computer vision, Medical Image processing, Machine learning, Deep learning,Data Mining,and Bioinformatics.


Dec 2018: Attended ICMLA18 - Orlando FL, Dec 2018: One paper accepted at Journal of Chemical Neuroanatomy, Oct 2018: One paper accepted at IEEE ICMLA conference, Sep 2018: One paper accepted at IEEE access journal, June 2018: Attended CVPR18- SaltLake City Utah

Projects

  • Determining nodule malignancy in National Lung Screening Trial CT screening images using Delta Radiomics
  • Determining nodule malignancy in National Lung Screening Trial CT screening images using Combined Radiomics of mutliple screens
  • Neurons segmentation and counting in NeuN-stained sections using unbaised stereology and deep learning
  • Deep learning ensemeble for Neurons segmentation and counting in NeuN-stained sections
  • Active Deep learning for Neurons segmentation and counting in NeuN-stained sections

Papers

  • Alahmari, S. S., Goldgof, D., Hall, L., Phoulady, H. A., Patel, R. H., & Mouton, P. R. (2018). Automated Cell Counts on Tissue Sections by Deep Learning and Unbiased Stereology. Journal of chemical neuroanatomy.
  • Alahmari, S. S., Cherezov, D., Goldgof, D. B., Hall, L. O., Gillies, R. J., & Schabath, M. B. (2018). Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. IEEE Access, 6, 77796-77806.
  • Alahmari, S. S., Goldgof, D., Hall,P., Dave L., Phoulady, H. A., Patel, R. H., & Mouton, P. R. (2018). Iterative Deep Learning Based Unbiased StereologyWith Human-in-the-Loop. International conference of Machine Learning and Application, 2018.