Expertise and Research Interests:

Ghada Zamzmi joined the Communication Engineering Branch at Lister Hill National Center for Biomedical Communications (LHNCBC) in February 2019. She received her PhD degree from University of South Florida in 2018. She focuses on using computational sciences and engineering techniques toward advancing healthcare of vulnerable populations (e.g., infants, minority groups). Ghada research interests include medical imaging, affective and cognitive computing, human behavior analysis, and healthcare application. She has >12 journal papers published in top tier journals (e.g., Transactions on Affective Computing), >15 conference publications and two patents. She served in the program committee in several top conferences in Computer Vision including CVPR, NeurIPS, and MICCAI. She chaired several academic workshops and events in her area of interests, led and participated in several mentoring programs. Ghada received different prestigious awards such as MIT Innovator under 35 and IEEE Computational Life Sciences best PhD Thesis Award (2019). She’s selected as the North America Ambassador for the international organization Women in AI.

Publications:

Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani SK. Semantically redundant training data removal and deep model classification performance: A study with chest X-rays. Computerized Medical Imaging and Graphics. Volume 115, 2024, 102379, ISSN 0895-6111, https://doi.org/10.1016/j.compmedimag.2024.102379.

Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani SK. Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric chest X-ray images. PLOS Digital Health 3(1): e0000286. https://doi.org/10.1371/journal.pdig.0000286.

Rajaraman S, Yang F, Zamzmi G, Xue Z, Antani S. Can deep adult lung segmentation models generalize to the pediatric population? Expert Systems with Applications, Volume 229, Part A, 2023, 120531, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2023.120531.

Zamzmi G, Hsu LY, Rajaraman S, Li W, Sachdev V, Antani S. Evaluation of an artificial intelligence-based system for echocardiographic estimation of right atrial pressure. Int J Cardiovasc Imaging. 2023 Sep 8. doi: 10.1007/s10554-023-02941-8. Epub ahead of print. PMID: 37682418.

More...