email: h a s s a n at wayne dot edu
office: 1132 Faculty/Administration Building
I am a Ph.D. student in Mathematics at Wayne State University interested in algebraic topology and geometry. My advisor is Dr. Andrew Salch. This Summer (2022), I am working as a Ph.D. intern in the Machine Intelligence Group at Lawrence Livermore National Laboratory under the mentorship of Dr. Timo Bremer.
I am particularly drawn to problems in pure math that have implications for mathematical physics or data science. Previously, I completed a B.S. in Mathematics and M.A. in Applied Mathematics at Wayne State University, where I focused on topological data analysis. I have also worked on problems and remain interested in machine learning and bioinformatics.
My CV can be found here. My Google Scholar page is here.
Papers and Preprints
Statistical Inference for Persistent Homology applied to simulated fMRI time series data
H. Abdallah, A. Regalski, M. Kang, M. Berishaj, N. Nandi, A. Chowdur, V. Diwadkar, A. Salch. (2021)
To appear in Foundations of Data Science.
From Mathematics to Medicine: A practical primer on topological data analysis (TDA) and the development of related analytic tools for the functional discovery of latent structure in fMRI data.
A. Salch, A. Regalski, H. Abdallah, R. Suryadevara, M. Catanzaro, V. Diwadkar.(2021)
PLOS One. https://doi.org/10.1371/journal.pone.0255859
CXR-Net: An Artificial Intelligence Pipeline for Quick Covid-19 Screening of Chest X-Rays
H. Abdulah, B. Huber, S. Lal, H. Abdallah, H. Soltanian-Zadeh, D. Gatti. (2021)
Lung Segmentation in Chest X-rays with Res-CR-Net
H. Abdulah, B. Huber, S. Lal, H. Abdallah, L. Palese, H. Soltanian-Zadeh, D. Gatti. (2020)
Res-CR-Net, a residual network with a novel architecture optimized for the semantic segmentation of microscopy images.
H. Abdallah, A. Liyanaarachchi, M. Saigh, S. Silvers, S. Arslanturk, D. Taatjes, L. Larsson, B. Jena, D. Gatti. (2020)
Machine Learning: Science and Technology 1 045004