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Yasmine Mustafa

Brief Biography

Yasmine Mustafa is joining The American University in Cairo as a tenure-track assistant professor of data science. She holds a Doctor of Philosophy in computer science from Missouri University of Science and Technology and master's and bachelor's degrees in digital media engineering and technology from the German University in Cairo. Her research interests span artificial intelligence, multimodal machine learning, explainable AI and interdisciplinary applications of data science.

Her doctoral research involved developing interpretable and clinically meaningful AI models that integrate neuroimaging and clinical data to advance the understanding and detection of neurological disorders, particularly Alzheimer's disease. Mustafa contributes to the international research community as a reviewer for leading conferences, including the International Conference on Medical Image Computing and Computer-Assisted Intervention and the AAAI Conference on Artificial Intelligence.

Her accomplishments include receiving the John W. Claypool Fund for Medical Research Fellowship, winning first place in the Three Minute Thesis competition and receiving the Best Paper Award at the PAKDD 2025 Workshop on Pattern Mining and Machine Learning for Bioinformatics.

Research Interest
  • Explainable and interpretable AI for healthcare
  • Multimodal machine learning for imaging, clinical and behavioral data 
  • Generative AI for disease classification, prognosis and progression modeling 
  • AI applications in behavioral science and healthcare 
  • Medical image analysis and computer-aided diagnosis
Education
  • Doctor of Philosophy in Computer Science, Missouri University of Science and Technology
  • Master of Science in Digital Media Engineering and Technology, German University in Cairo
  • Bachelor of Science in Digital Media Engineering and Technology, German University in Cairo
  • Holloway, J., Gans, D., Akram, N., O’Brien, D., Vincent, A., Johnson, L., Mustafa, Y., Sayeed, O. and Tan, Z. S. (2026). "Lessons Learned from an Intergenerational Health Promotion Program Focused on Virtual Community Engagement." Discover Public Health, 23, Article 844.
  • Mustafa, Y., Elmahallawy, M. and Luo, T. (2025). "Unlocking Neural Transparency: Jacobian Maps for Explainable AI in Alzheimer’s Detection." In Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2025 Workshops, Lecture Notes in Computer Science, 15835, 229–242. Springer.
  • Mustafa, Y., Elmahallawy, M. and Luo, T. (2024). "Efficient Brain Imaging Analysis for Alzheimer’s and Dementia Detection Using Convolution-Derivative Operations." Paper presented at the 2024 IEEE International Conference on Big Data, 6420–6429.
  • Mustafa, Y. and Luo, T. (2024). "Unmasking Dementia Detection by Masking Input Gradients: A JSM Approach to Model Interpretability and Precision." In Advances in Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, 14647, 75–90. Springer.
  • Mustafa, Y. and Luo, T. (2023). "Diagnosing Alzheimer’s Disease Using Early-Late Multimodal Data Fusion with Jacobian Maps." Paper presented at the 2023 IEEE International Conference on E-health Networking, Application and Services, 49–55.
  • Mustafa, Y., Elmahallawy, M., Luo, T. and Eldawlatly, S. (2023). "A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition." Paper presented at the 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, 799–804.