profiles

Fahmi Khalifa received his BS and MS degrees in Electronics and Electrical Communication Engineering from Mansoura University, Egypt in 2003 and 2007, respectively. He received his PhD degree in 2014 in Electrical Engineering from the Electrical and Computer Engineering Department (ECE), University of Louisville (UofL), USA. Dr. Khalifa has more than 14 years of hands-on experience in the fields of Artificial Intelligence, image/signal processing, machine learning, biomedical data analysis, and computer-aided diagnosis.

 Dr. Khalifa's honors and awards include Mansoura University scholarship for distinctive undergraduate students for four consecutive years, Theobald Scholarship Award in 2013 (ECE, UofL), the ECE Outstanding Student award for two times in 2012 and 2014 (ECE, UofL), the John M. Houchens award for the outstanding dissertation (UofL), the second-place Post-Doctoral Fellow award in 2014 Research! Louisville, UofL. He was the recipient of the PowerLIVE Award for Faculty commitment to students and their academic success, and final list for the “Instructional Innovator of the Year”, Morgan State University, 2023

Dr. Khalifa has more than 190 peer-reviewed publications. Particularly, he has authored/co-authored 75+ peer-reviewed articles appearing in prestigious high-impact journals, 85+ conference papers in extremely selective peer-reviewed, top-rank international conferences, 13+ chapters in leading edited books, and six US patents. A complete list of publications and identifiers can be accessed here: GoogleScholar; WoS; Scoups; Research Gate; Loop; and ORCID

Recent Publication

• Peer–Reviewed Journal Articles
• Abdelhaiem, A. Alkasas, H. Balaha, M. Badawy, N. Alghamdi, M. Ghazal, S. Contractor, E. van Bogaert, D. Gondim, S. Silva, F. Khalifa, and A El-Baz, “Incorporating imaging, clinical, pathology, and demographic markers for hormonal therapy prediction in prostate cancer,” IEEE Access, vol. 11, pp. 195960–195973, 2024
• Abdelhaiem, M. A. Badawy, M. Abou El-Ghar, M. Ghazal, S. Contractor, E. van Bogaert, D. Gondim, S. Silva, F. Khalifa, and A El-Baz, “Multi-branch CNNFormer: a novel framework for predicting prostate cancer response to hormonal therapy,” BioMedical Engineering OnLine, vol. 24, no. 131, pp. 1-15, 2024.
• Elnakib, F. Khalifa, A. Soliman, A. Shalaby, and M. Elhosseini, “Editorial: Emerging Artificial Intelligence Technologies for Neurological and Neuropsychiatric Research,” Frontiers in Neuroscience: Brain Imaging, vol. 18: 1518442 (3 pp), 2024.
• Razzak, S. Naz, H. Alinejad-Rokny, T. N. Nguyen, and F. Khalifa, “A cascaded mutliresolution ensemble deep learning framework for large scale Alzheimer’s disease detection using brain MRIs,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 21, no. 4, pp. 573–581, 2024.
• Aina, O. Akinnyi, Md. M. Rahman, V. Odero-Marah, and F. Khalifa, “A hybrid learning architecture for mental disorder detection using emotion recognition,” IEEE Access, vol. 12, pp. 91410–91425, 2024.
• Ismail, P. Okwan, F. Khalifa, A. Lawson, and F. Lacy, “Improving the practical skills of STEM students at a historically black college and university (HBCU),” J. Infrastructure, Policy, Develop., Vol. 8, no. 6–3507 (19 pp.), 2024.
• Dixon, O. Akinniyi, A. Abdelhamid, G. A. Saleh, Md. M. Rahman, and F. Khalifa, “A hybrid learning-architecture for improved brain tumor recognition,” Algorithms, vol. 17, no. 16(221)–17 pp., 2024.
• Essel, A. Abdelhamid, M. Darwich, F. Khalifa, F. Lacy, and Y. Ismail, “High-Fidelity machine learning techniques for driver drowsiness detection,”Int. J. Comput. Digital Sys., vol. 16, no. 1, pp. 1444–1454, 2024. DOI: http:// dx. doi. org/ 10. 12785/ ijcds/ 1601106.
• Abdelhamid, O. Akinniyi, G. A. Saleh, W. Deabes, and F. Khalifa, “An ensemble neural architecture for lung diseases prediction using chest X-rays,” Int. J. Comput. Digital Sys., vol. 16, no. 1, pp. 1019–1028, 2024. DOI:http: // dx. doi. org/ 10. 12785/ ijcds/ 160174.
• Khalifa, I. Razzak, M. A. Kamal, and A. Soliman, “Guest editorial advanced machine learning and artificial intelligence tools for Computational Biology: Methodologies and Challenges,” IEEE J. Biomed. Health Inform., vol. 28, no. 4, pp. 1883-1885, 2024.
• Elsharkawy, A. Sharafeldeen, F. Khalifa, A. Soliman, A. Elnakib, A. Mahmoud, M. Ghazal, E. El-Daydamony, A. Atwan, H. Singh, and A. El-Baz, “A clinically explainable AI-based grading system for age-related macular degeneration using optical coherence comography,” IEEE J. Biomed. Health Inform., vol. 28, no. 4, pp. 2079–2090, 2024.
• [9] S. Naz, I. Kamran, S. Gul, F. Hadi, and Khalifa, “Multi-model fusion of CNNs for identification of Parkinson’s Disease using handwritten samples,” IEEE Access, vol. 11, pp. 135600–135608, 2023.
• Khalifa, A. Shalaby, A. Soliman, S. Elaskary, A. Refaey, and M. Abdelazim, “Artificial intelligence based computer-aided diagnosis applications for brain disorders from medical imaging data Volume II” Frontiers in Neuroscience: Brain Imaging, vol. 17: 1241926 (5 pp), 2023.
• Akinniyi, Md M. Rahman, H. S. Sandhu, A. El-Baz, and F. Khalifa, “Multi-stage classification of retinal OCT using multi-scale ensemble deep architecture” Bioengineering, vol. 10, no. 7 (16 pp.), 2023.
• Sharma, A. Naglah, S. Aslan, F. Khalifa, A. El-Baz, S. Harkema, and J. D’Amico, “Preservation of functional descending input to paralyzed upper extremity muscles in motor complete cervical spinal cord injury,” Clinical Neurophysiology, vol. 150, no. 1, pp. 56–68, 2023.
• Razzak, M. K. Khan, G. Xu, and F. Khalifa, “Guest Editorial Open and interpretable AI in computational pathology,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 4, pp. 1657–1660, 2023.
• Shalaby, A. Soliman, S. Elaskary, A. Refaey, M. Abdelazim, and F. Khalifa, “Editorial: Artificial intelligence based computer-aided diagnosis applications for brain disorders from medical imaging data,” Frontiers in Neuroscience: Brain Imaging, vol. 37: 998818 (4 pp), 2023.
• Elgeneedy, F. Khalifa, H. E. Moustafa, H. Khater, and E. AbdElhalim, “An MRI-based deep learning approach for accurate detection of Alzheimer’s disease,” Alexandria Engineering Journal, vol. 63, no. 1, pp. 211–221, 2023.
• Hammouda, F. Khalifa, N. S. Alghamdi, H. Darwish, and A. El-Baz, “Multi-Stage classification based deep learning for Gleason system grading using histopathological image” Cancers, vol. 14, 23 (23 pp.), 2022.

• Book Chapters
• Hammouda, F. Khalifa, A. Soliman, A. Mahmoud, M. Ghazal, F. Taher, M. Abou El-Ghar, M. A. Badaway, H. Darwish, and A. El-Baz,“A radiomic features–based pipeline for accurate bladder cancer staging,” Handbook of Texture Analysis: Generalized Texture for AI-Based Industrial Applications, A. El-Baz, M. Ghazal, and J. Suri, Eds, CRC Press, 2023, Vol. 1, ch. 12, pp. 12–25, ISBN 978-0-3674-8609-9.
• Elsharkawy, A. Sharafeldeen, A. Soliman, F. Khalifa, A. Mahmoud, A. El-Baz, M. Ghazal, H. Sandhu, and A. El-Baz,“Early identification of diabetic retinopathy through a computer-assisted diagnostic system and a higherorder spatial appearance model of 3D-OCT,” Photo Acoustic and Optical Coherence Tomography Imaging, A. El-Baz and J. Suri, Eds, IOP Publishing, 2023, Vol. 1, ch. 1, pp. 12–25, ISBN 978-0-7503-2052-8.
• Naglah, F. Khalifa, R. Khaled, A. A. K. A. Razek, M. Ghazal, G. Giridharan, A. Mahmoud, and A. El-Baz,“A review of texture-centric diagnostic models for thyroid cancer using convolutional neural networks and visualized texture patterns,” State of the Art in Neural Networks and Their Applications, A. El-Baz and J. Suri, Eds, Academic Press, 2023, Vol. 2, ch. 12, pp. 265–295, ISBN 978-0-12-819872-8.
• Abdeltawab, F. Khalifa, F. Taher, M. Ghazal, A. Mahmoud, and A. El-Baz, “Left ventricle segmentation for cine MR using deep learning,” Cardiovascular and Coronary Artery Imaging, A. El-Baz and J. Suri, Eds, Academic Press, 2023, ch. 8, pp. 113–147, ISBN 978-0-12-821983-9.

• Peer-Reviewed Conference Proceedings
• Hoque, Md R. Hasan, Md I. S. Emon, F. Khalifa, and Md. M. Rahman, “ Medical image interpretation with large multimodal models,” In: Proc. Conference and Labs of the Evaluation Forum (CLEF’24)-CEUR workshop., Grenoble, France, Sept. 9–12, 2024 (Accepted).
• Md I. S. Emon, M. Hoque, Md R. Hasan, Khalifa, and Md. M. Rahman, “Fingerprint Identification of Generative Models Using a MultiFormer Ensemble Approach,” In: Proc. Conference and Labs of the Evaluation Forum (CLEF’24)-CEUR workshop., Grenoble, France, Sept. 9–12, 2024 (Accepted)
• Akinniyi, J. Dixon, F. Khalifa, G. Saleh, and W. Deabes, “A vision transformer-based intelligent system for brain tumor diagnosis,” In: Proc. Int. Conf. Intelli. Sys., Blockchain Commun. Techn. (ISBCom), Sharm El-Sheikh, Egypt, July 13–14, 2024 (Accepted)
• Abdelhameed, O. Akinniyi, G. Saleh, and F. Khalifa, “lung disease detection using scale-invariant weighted ensemble neural architecture,” In: Proc. Int. Conf. Intelli. Sys., Blockchain Commun. Techn. (ISBCom), Sharm El-Sheikh, Egypt, July 13–14, 2024 (Accepted)
• Abdeltawab, Md R. Jani, Md R. Hasan, I. Yasser, and F. Khalifa, “A hybrid adversarial-Transunet architecture for improving LV segmentation using cardiac cine images,” In: Proc. Int. Conf. Intelli. Sys., Blockchain Commun. Techn. (ISBCom), Sharm El-Sheikh, Egypt, July 13–14, 2024 (Accepted)
• Yasser, and F. Khalifa, “Role of ERP as integrative intelligent system for business enterprises,” In: Proc. Int. Conf. Intelli. Sys., Blockchain Commun. Techn. (ISBCom), Sharm El-Sheikh, Egypt, July 13–14, 2024 (Accepted)
• Deabes, F. Khalifa, A. E. Abdel-Hakim, and K. E. Bouazza, “Advancing ECT imaging: residual UNet deep neural network approach,” In: Proc. Int. Conf. Intelli. Sys., Blockchain Commun. Techn. (ISBCom), Sharm El-Sheikh, Egypt, July 13–14, 2024 (Accepted)
• Abdelhalim, A. Alksas,H. M. Balaha, M. Badawy, M. Abou El-Ghar, N. S. Alghamdi, M. Ghazal, S. Contractor, E. V. Bogaert, D. Gondim, S. R. Silva, F. Khalifa, and A. El-Baz, “Advancing personalized prostate cancer therapy
• through hormonal treatment: Promising findings,” In: Proceedings of International Symposium on Biomedical Imaging: From Nano to Macro (ISBI’24), Athens, Greece, May 27–30, 2024, accepted.
• Akinniyi, I. Razzak, Md M. Rahman, H. S. Sandhu, A. El-Baz, and F. Khalifa, “Multi-classification of retinal diseases using a pyramidal ensemble deep framework,” In: Proc. IEEE Int. Conf. Image Process. (ICIP), Kuala Lampur, Malaysia, October 8–11, 2023, pp. 1945–1949. (Oral presentation)
• Aboudessouki, K. M. Ali, M. Elsharkawy, A. Alksas, A. Mahmoud, F. Khalifa, M. Ghazal, J. Yousaf, H. Abu Khalifeh, and . El-Baz, “Automated diagnosis of breast cancer using deep learning-based whole slide image analysis of molecular biomarkers,” In: Proc. IEEE Int. Conf. Image Process. (ICIP), Kuala Lampur, Malaysia, October 8–11, 2023, pp. 2965–2969.

Invited Talks

• Keynote Speaker: 1st International Conference on Intelligent Systems, Blockchain, and Communication Technologies, Sharm El-Sheikh, Egypt, July 2024,   https://www.isbcomtech.com/speaker.html
• Keynote Speaker: 3rd International Conference on Computing and Machine Intelligence (ICMI), Central Michigan University, April 2024, https://www.icmiconf.com/  
• Invited Speaker: National Symposium on Equitable AI, Pikesville, Maryland, USA, April 2024, https://equitableaisymposium.com/#speakers