The Electrical Engineering department at KFUPM came into existence with the establishment of the University of Petroleum & Minerals in 1967. It is one of the largest departments in the University with an average number of students being approximately 900, 16% of whom are in the graduate program. The department provides 2 four-year undergraduate programs, Bachelor of Science in Electrical Engineering and Bachelor of Science in Electrical Engineering and Physics. The graduate program offers Master of Science and Master of Engineering in Electrical Engineering, Master of Science in Telecommunication Engineering, Master of Sustainable and Renewable Energy, Master of Wireless Communication Networks, and Ph.D. in Electrical Engineering.
The department has about 61 full-time faculty members in 6 specialized areas of research. The Groups in the department are: Energy Systems, Communications, Electronics, Control Systems, Electromagnetics, and Digital Signal Processing. Additionally, a pool of experienced engineers and technicians maintain more than 30 laboratories in the department.
To be globally known for skillful graduates and quality research with focus on national needs.
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On March 19, 2025, the Learning Theory and Algorithms Research Area hosted a seminar titled "Multi-modal and Multi-model Approaches for Medical Image Analysis: Applications to Tumor and Cancer Detection," led by Dr. Abdullah Al-Battal.
The seminar highlighted groundbreaking advancements in integrating multi-modal imaging techniques such as MRI, CT, and PET with state-of-the-art AI models. Experts explored how these innovations are transforming tumor and cancer detection by enhancing diagnostic accuracy, segmentation, and classification. The session covered key methodologies, challenges, and real-world applications, emphasizing the pivotal role of AI-driven multi-modal approaches in improving cancer diagnosis.
Attendees actively participated in insightful discussions, gaining valuable perspectives on the future of medical imaging and its growing impact on healthcare.
The following are the highlights of the event:
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Advancements in medical imaging and artificial intelligence have revolutionized the field of tumor and cancer detection. However, single-modality imaging and conventional analysis models often face limitations in capturing complex pathological features. This seminar explores cutting-edge multi-modal and multi-model approaches for medical image analysis, leveraging diverse imaging techniques—such as MRI, CT, PET, and histopathology—along with deep learning and machine learning models to enhance diagnostic accuracy. By integrating complementary information from different imaging modalities and fusing insights from multiple AI-driven models, these approaches aim to improve early detection, segmentation, and classification of tumors. We will discuss key challenges, methodologies, and real-world applications, highlighting how multi-modal fusion and ensemble learning contribute to more robust and precise cancer diagnosis. This seminar is designed for researchers, clinicians, and AI practitioners interested in the intersection of medical imaging and computational intelligence for enhanced healthcare solutions.
Building 59-2004
19 Mar, 2025
11:00 AM - 11:50 AM
The Electrical Engineering Department (EE) at KFUPM provides a world-class education and innovative learning experiences for both undergraduate and graduate students.
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