Zafar Iqbal
Education
- Ph.D. in Computer Science, Georgia State University, USA (2025) — Dissertation: Time Permutation Approaches to Self-Supervised Dynamic Neuroimaging
- Ph.D. Coursework in Robotics and Intelligent Machine Engineering, NUST, Pakistan (2019)
- M.S. in Software Engineering, NUST, Pakistan (2017) — Thesis: Improved Predictive Models for Thoracic Surgery using Data Mining Techniques
- B.S. in Software Engineering, University of Azad Jammu and Kashmir, Pakistan (2014)
Research Interests
- fMRI data analysis and computational modeling
- Self-supervised learning and model interpretability
- Artificial intelligence in neuroscience
Biography
Dr. Zafar Iqbal is a computational neuroscientist and machine learning researcher with expertise in fMRI data analysis, self-supervised learning, and interpretable AI. He earned his Ph.D. in Computer Science from Georgia State University, where he developed a pioneering “Time Reversal” pre-training methodology for modeling temporal neuroimaging data, enhancing performance on biomedical datasets with limited samples, as a Graduate Research Assistant at the Center for Translational Research in Neuroimaging and Data Science (TReNDS, 2019–2025).
He has published in leading venues including IEEE IJCNN, Brain Sciences, and High-Confidence Computing, and has presented at forums including the Organization for Human Brain Mapping and ICCABS. He has taught Machine Learning, Computer Networks, and Digital Logic & Design at Georgia State University and Karakorum International University.
Selected Publications
- Iqbal, Z., et al. “Self-Supervised Mental Disorder Classifiers via Time Reversal.” IJCNN, 2023.
- Iqbal, Z., et al. “Explainable Self-Supervised Dynamic Neuroimaging Using Time Reversal.” Brain Sciences, 2025.
- Zia, Q., et al. “Hierarchical Federated Transfer Learning in Digital Twin-based Vehicular Networks.” High-Confidence Computing, 2025.
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