taghreed Ibrahim | Cell Structure Analysis | Best Researcher Award

Ms. taghreed Ibrahim | Cell Structure Analysis | Best Researcher Award

Ms. taghreed Ibrahim , Mansoura University , Egypt

Taghreed Elsayed is an Assistant Lecturer in the field of Computer Science and Control Systems Engineering. She holds a Bachelor’s degree in Computers and Control Systems Engineering from Mansoura University, and has completed a Master’s degree in the same field with a focus on E-learning and Fog Computing. Taghreed is passionate about teaching and research, particularly in the areas of artificial intelligence, cybersecurity, and cloud computing. She has a deep understanding of systems programming, databases, and modern teaching software. Taghreed is also proficient in supervising both undergraduate and master’s students and has designed and implemented curricula for computer science courses. With diverse teaching experience, she has worked at Delta University for Science and Technology, Midocean University, and other academic institutions, providing online and face-to-face instruction in various programming languages and technologies. Her publications and research further showcase her expertise and dedication to the field.

Publication Profile:

Scopus

Strengths for the Award:

  1. Research Excellence: Taghreed Elsayed has demonstrated a strong track record of research, particularly in the fields of E-learning, AI, and healthcare. Her publication on the “Fog-Based Recommendation System for Promoting the Performance of E-Learning Environments” showcases her ability to innovate in educational technologies. Additionally, her work in deep learning techniques for accurate breast cancer diagnosis and predicting bladder cancer recurrence further highlights her multidisciplinary research expertise.

  2. Comprehensive Knowledge: Taghreed has extensive knowledge in critical domains such as artificial intelligence, cybersecurity, image processing, and cloud computing, all of which are highly relevant to current technological trends. This wide-ranging knowledge base contributes significantly to her ability to approach research from various angles.

  3. Industry and Teaching Experience: She has a strong combination of teaching experience and real-world application of computer science in both academia and industry. Her work as an assistant lecturer in various universities, as well as her extensive experience in networking, security, and programming, demonstrates her well-rounded expertise.

  4. Publications and Contributions: Taghreed’s research publications in prestigious journals underline her capacity to contribute valuable knowledge to the academic community. The citations and recognition of her work are a testament to her impact on the field.

Areas for Improvement:

  1. Broader Industry Collaborations: While Taghreed has made notable contributions in both academia and research, her collaboration with the industry could be further expanded. Developing partnerships with tech companies or health organizations could elevate her research impact, particularly in applied fields like healthcare.

  2. Interdisciplinary Research: Although her work bridges the gap between AI and E-learning, there is an opportunity for more interdisciplinary research, especially in the integration of AI with other domains like IoT, smart cities, and robotics. Exploring these intersections may lead to groundbreaking innovations.

  3. Mentorship and Research Leadership: While she supervises students, further mentoring of PhD candidates or leading large-scale research projects would help solidify her position as a leader in the research community.

Education:

Taghreed Elsayed completed her Bachelor’s degree in Computers and Control Systems Engineering at Mansoura University in 2010, with her graduation project on a Smart Elevator, receiving an excellent grade. Following that, she pursued a Pre-Master’s program in the same department in 2014, studying topics like cloud computing, cybersecurity, and artificial intelligence. Taghreed’s Master’s degree, completed in 2020, focused on enhancing E-learning environments using Fog-based Recommendation Systems (FBRS). She published research on this topic, demonstrating her commitment to advancing education technology. Between 2021-2022, Taghreed embarked on Pre-PhD studies, covering advanced topics in AI, cybersecurity, and deep learning, with a particular focus on using AI techniques to detect cancerous tumors. Her academic excellence is reflected in her A+ scores in various subjects, and her publications demonstrate her active contributions to the field.

Experience:

Taghreed Elsayed has extensive experience in teaching and research within the field of Computer Science. She served as an Assistant Lecturer at Delta University for Science and Technology, where she developed and taught computer science courses focused on AI, programming languages (C#, C++, Java, Python), databases, and more. She has also taught at Midocean University, focusing on online courses in information security, cybersecurity, and Internet of Things (IoT). Additionally, Taghreed worked as an instructor at Harvest Training Center, specializing in Cisco networking courses such as CCNA and CCNA Security, and at Elsewedy Technical Academy, where she taught the principles of networking. Her experience extends beyond academia to the industry, where she worked as an IT Engineer at Quick Air Company for Tourism and as a Technical Support Engineer at Exceed in Smart Village, managing and maintaining IT systems, troubleshooting network issues, and ensuring smooth operations.

Research Focus:

Taghreed Elsayed’s research interests lie primarily in the fields of E-learning, artificial intelligence, cybersecurity, and fog computing. Her work explores how emerging technologies can be used to enhance the performance of E-learning environments, focusing on personalized learning experiences through recommendation systems. In her Master’s research, she developed a Fog-based Recommendation System (FBRS) that significantly improves the performance and personalization of E-learning platforms. Her Pre-PhD research centers on applying AI techniques to medical diagnosis, specifically for detecting cancerous tumors using deep learning methods. Taghreed’s interdisciplinary approach bridges technology and education, striving to improve learning outcomes through innovative technological solutions. Her future research goals include advancing AI applications in healthcare and education and exploring new methods for optimizing cybersecurity protocols in the context of smart environments and IoT.

Publications Top Notes:

  • “A Fog-Based Recommendation System for Promoting the Performance of E-Learning Environments” 📘

  • “Accurate Breast Cancer Diagnosis Strategy (BCDS) Based on Deep Learning Techniques” 🩺

  • “CNN-LSTM for Prediction of Bladder Cancer Recurrence and Response to Treatments” 🏥

Conclusion:

Taghreed Elsayed is a deserving candidate for the Best Researcher Award due to her profound contributions to the fields of AI, cybersecurity, and E-learning. Her academic achievements, coupled with her extensive teaching experience and interdisciplinary research, make her a standout figure. By expanding her industry collaborations and fostering deeper interdisciplinary research, she could further solidify her impact and recognition as a leading researcher in her field.