Early Academic Pursuits
Prof. Kalfalla Awedat laid a strong academic foundation in Electrical and Communication Engineering, earning his B.Sc. and M.Sc. degrees from Tripoli University in Libya in 2001 and 2008, respectively. Driven by a passion for research and innovation, he pursued and completed his Ph.D. in Electrical and Computer Engineering at Western Michigan University in 2016. His doctoral studies honed his expertise in biomedical signal processing and electrical systems, setting the stage for a diverse and impactful career in academia and engineering.
Professional Endeavors
Prof. Awedat has cultivated a distinguished academic career with a focus on engineering education and hands-on instruction. He currently serves as a Tenure-Track Assistant Professor at SUNY Morrisville, where he teaches computer information technology and leads the development of a cutting-edge Virtual Reality/Augmented Reality (VR/AR) lab. Previously, he held a non-tenure track Assistant Professor position at Pacific Lutheran University, where he taught a broad spectrum of undergraduate courses including C++, Python, Java, microelectronics, data mining, and computer networking. His early academic appointments include serving as a Teaching Assistant at Western Michigan University and as a Lecturer at Aljabal Algrabi University in Libya. Beyond academia, he worked as a Communications Engineer at GECOL Company, where he applied fiber optic technologies and automated diagnostic systems in high-voltage environments.
Contributions and Research Focus
Prof. Awedat’s research spans across several innovative domains. His work focuses on applying deep learning networks for fault detection in solar panel systems, integrating compressive sensing with AI for big data analytics, and utilizing machine learning for cancer data classification and medical image modeling. He has developed supervised machine learning techniques for early cancer detection, contributed to the modeling and classification of medical images, and conducted significant research on signal and image processing, including object detection, face recognition, and data augmentation. His passion for solving real-world problems through intelligent systems continues to drive his academic output.
Impact and Influence
With a diverse academic and industry background, Prof. Awedat has significantly impacted both students and the broader scientific community. His leadership in developing new courses and laboratories—such as Biomedical Signal Processing, Microelectronics, and Engineering with 3D printing—has enhanced student learning and lab-based education. He also secured a $10,000 research grant for efficient face recognition methods and has applied for a $484,000 NSF grant in collaboration with North Carolina State University and Benedict College, highlighting his growing influence in the fields of AI and engineering education.
Academic Citations and Recognitions
Prof. Awedat’s scholarly work has been cited in areas related to biomedical signal processing, computer vision, and big data analytics. His research outputs are reflected in multiple funded projects and collaborative research initiatives. Notably, his contribution to the project titled “Efficient Face Recognition Using Regularized Adaptive Non-Local Coding” has received peer recognition and funding support, demonstrating the academic relevance and potential societal impact of his work.
Technical Skills
Prof. Awedat possesses a broad skill set across various software and platforms including MATLAB, OrCAD, PSpice, Python, C++, and Java. His practical knowledge extends to tools like LabChart, PowerLab, and advanced lab equipment such as FLUKE systems. He has undergone professional training in fiber optics, project management (PMP), and laboratory techniques, further enhancing his capacity to lead research and teaching innovation.
Teaching Experience
With more than a decade of academic experience, Prof. Awedat has taught and developed courses across the domains of engineering, programming, and data science. From digital logic and electronic circuits to data mining and biomedical engineering, his teaching portfolio is both deep and diverse. He has a proven track record of mentoring students, supervising design projects, and fostering a culture of inquiry and innovation in classroom settings.
Legacy and Future Contributions
Prof. Awedat’s legacy lies in his dedication to bridging theoretical knowledge with practical applications. Through curriculum development, research mentorship, and technological innovation, he continues to shape future-ready engineers. His ongoing work in autonomous vehicle object detection, AI-powered medical diagnostics, and immersive VR/AR education tools positions him as a forward-thinking leader in academic and technological spaces. Looking ahead, his collaborative efforts and interdisciplinary research promise to make substantial contributions to the fields of smart healthcare, renewable energy, and AI-enhanced engineering education