Manar Hamza | Computer Science Data mining | Best Researcher Award

Dr. Manar Hamza | Computer Science Data mining | Best Researcher Award

professor atΒ  Prince Sattam bin Abd El Aziz University, China

πŸ‘©β€πŸ« Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. πŸ’» Holds a strong track record in research and academia, leveraging innovation and teamwork. Aims to thrive in challenging, dynamic, and team-oriented environments that foster growth. 🌍 Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

scopus

Education πŸŽ“

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018–2021). πŸŽ“ Master’s Degree in Computer Science from Sudan University of Science and Technology (2003–2005). πŸŽ“ B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995–1999). πŸ“š Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience πŸ–₯️

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013–present). πŸ‘©β€πŸ’Ό Supervisor and Coordinator roles in quality, academic advising, and measurement (2014–2020). πŸ‡ΈπŸ‡© Lecturer at Omdurman Islamic University, Sudan (2005–2012). πŸ‘©β€πŸ”¬ E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors πŸ†

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. πŸ™Œ Recognized for voluntary services, including extracurricular activities and technical support for students and staff. ⭐ Esteemed arbitrator in scientific and innovation conferences. πŸ“œ Active contributor to enhancing the learning environment with innovative solutions.

Research Focus πŸ”

Data mining, text mining, and information security are core research areas. πŸ“Š Interested in qualitative research, outcome-based education, and e-learning systems. 🌐 Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. πŸ›‘οΈ Exploring cybersecurity methods and their application in education and industry.

✍️Publications Top Note :

1. Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

Published in: SN Computer Science, 2024, 5(5), 549

Summary: This paper proposes a novel classification model for urban-related tweets using arithmetic optimization integrated with deep learning to support sustainable urban living solutions.

2. Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems

Published in: IEEE Transactions on Consumer Electronics, 2024, 70(1), pp. 1889–1902

Summary: Introduces a Bi-LSTM approach enhanced with a Kalman filter for accurate traffic flow prediction, addressing challenges in intelligent cyber-physical systems.

Citations: 5

3. Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification

Published in: Mobile Networks and Applications, 2024, 29(1), pp. 176–186

Summary: Utilizes the Deer Hunting Optimization algorithm with deep learning to achieve high accuracy in detecting and classifying fabric defects.

Citations: 1

4. Automatic Recognition of Cyberbullying in the Web of Things and Social Media Using Deep Learning Framework

Published in: IEEE Transactions on Big Data, 2024

Summary: Develops a deep learning-based framework to detect and prevent cyberbullying within social media and IoT environments.

5. Artificial Rabbit Optimizer with Deep Learning for Fall Detection in IoT Environment

Published in: AIMS Mathematics, 2024, 9(6), pp. 15486–15504

Summary: Introduces the Artificial Rabbit Optimizer combined with deep learning to enhance fall detection systems for disabled individuals in IoT environments.

Citations: 1

6. Computational Linguistics-Based Arabic Poem Classification and Dictarization Model

Published in: Computer Systems Science and Engineering, 2024, 48(1), pp. 98–114

Summary: Proposes a computational linguistics model to classify Arabic poems and enhance their dictarization process.

7. Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

Published in: Intelligent Automation and Soft Computing, 2024, 38(2), pp. 153–168

Summary: Develops a deep neural network with hyperparameter tuning for effective abstractive summarization of Arabic texts.

Citations: 1

8. Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in IoT Environment

Published in: IEEE Access, 2024, 12, pp. 258–267

Summary: Presents a Chaotic Equilibrium Optimizer combined with deep learning to improve green communication and load prediction in IoT systems.

Citations: 2

9. Land Use and Land Cover Classification Using River Formation Dynamics Algorithm With Deep Learning on Remote Sensing Images

Published in: IEEE Access, 2024, 12, pp. 11147–11156

Summary: Leverages the River Formation Dynamics algorithm integrated with deep learning for efficient land use and land cover classification using remote sensing data.

Citations: 4

10. Prediction of Sleep Quality Using Wearable-Assisted Smart Health Monitoring Systems

Published in: Journal of King Saud University – Science, 2023, 35(9), 102927

Summary: Utilizes wearable technology and statistical data to predict sleep quality, providing insights into personalized smart health monitoring systems.

Citations: 1

Conclusion

The candidate’s extensive experience, academic qualifications, and contributions to computer science, particularly in data mining and information security, make them a strong contender for the Research for Best Researcher Award. With some strategic enhancements to highlight impactful research and global contributions, their profile could exemplify the qualities of an award-winning researcher in computer science.

Albandari Alrowaily | Material Science | Best Researcher Award

Assist. Prof. Dr Albandari Alrowaily | Infectious diseases | Best Researcher Award

Assist Prof atΒ  Princess Nourah bint Abdulrahmman University, Saudi Arabia

πŸŽ“ Assist. Prof. Dr Albandari Alrowaily is an Assistant Professor of Physics at Princess Nourah Bint Abdurrahman University, Saudi Arabia. She specializes in theoretical nuclear and atomic physics with a Ph.D. from the University of North Texas. Starting her career as a high school physics teacher, she progressed through roles such as lecturer, committee member, and advisor. Passionate about education quality, she now serves as the Teaching and Learning Quality Manager. Assist. Prof. Dr Albandari Alrowaily is an advocate for empowering women in science, holding memberships in ISMWS and APS. Her contributions to academia include teaching a wide range of physics courses, mentoring students, and participating in critical departmental activities. Outside work, she actively supports cultural and environmental initiatives.

Professional Profiles:

Education πŸŽ“

Ph.D. in Theoretical Nuclear and Atomic Physics (2021): University of North Texas, Denton, TX, USA. Master’s in Theoretical Nuclear Physics (2008): Princess Nourah Bint Abdurrahman University, Riyadh, Saudi Arabia. Bachelor’s in Physics (1999): Princess Nourah Bint Abdurrahman University, Riyadh, Saudi Arabia. Additional Certificates: Management, document organization, research ethics, teamwork, professional basics, and ESL.

Experience πŸ‘©β€πŸ«

High School Physics Teacher (1999–2000): Al-Jouf City. Teaching Assistant (2001–2007): Princess Nourah University. Committee Member: Grades Monitoring & Interviews (2001–2007). Lecturer (2008–2021): Princess Nourah University. Assistant Professor (2021–Present): Physics Department. Quality Manager (2022–Present): Teaching & Learning, College of Science. Additional Roles: Academic advisor, training supervisor, committee leader, and lab organizer.

Awards and HonorsπŸ…

Ideal Student Awards (1992 & 1995): Al-Jouf Region. Distinguished Student (2000): Princess Nourah University. Travel Awards (2018–2019): DAMOP, UNT, and COS for research presentations.Β Recognized for exceptional contributions to academic excellence and community engagement.

Research Focus πŸ”¬

Theoretical studies on nuclear and atomic physics, focusing on quantum mechanics, particle interactions, and advanced simulations.Β Proficient in computational methods using Matlab, Python, and Mathematica for modeling complex systems. Β Research on nuclear reactions, atomic energy levels, and spectroscopic analysis. Advocates for interdisciplinary applications of physics to solve global challenges.

✍️Publications Top Note :

High-Performance Supercapacitors (ZnSe/MnSe)

Study: Development of ZnSe/MnSe composites for supercapacitor electrodes using hydrothermal techniques.

Publication: Journal of Physics and Chemistry of Solids, 2024, 49 citations.

Impact: Enhanced capacitive performance through novel material synthesis.

2. g-C3N4/NiIn2S4 for Supercapacitors

Study: Hydrothermal fabrication of g-C3N4/NiIn2S4 composite materials.

Publication: Ceramics International, 2024, 35 citations.

Impact: Promising electrode material with high efficiency.

3. Nonlinear Plasma Waves

Study: Interaction of solitons in pair-ion–electron plasmas using the Hirota method.

Publication: Physics of Fluids, 2023, 30 citations.

Impact: Advances theoretical understanding of electrostatic plasma dynamics.

4. SrCeO3/rGO for Oxygen Evolution Reaction

Study: Hydrothermal synthesis of SrCeO3 nanocomposites for electrocatalysis.

Publication: Fuel, 2024, 27 citations.

Impact: Enhanced catalytic efficiency for clean energy applications.

5. BiFeO3 Supercapacitor Applications

Study: Mn-doped BiFeO3 as an electrode material for supercapacitors.

Publication: Journal of Energy Storage, 2024, 20 citations.

Impact: Novel application of perovskite materials for energy storage.

6. Radiation Shielding Polymers

Study: Optical and mechanical improvements in polyvinyl alcohol composites.

Publication: Journal of Rare Earths, 2023, 18 citations.

Impact: Optimized materials for gamma-ray attenuation.

7. NiS2@SnS2 Nanohybrids

Study: Water-splitting applications of NiS2@SnS2 nanohybrids.

Publication: Materials Chemistry and Physics, 2024, 15 citations.

Impact: Low-cost, efficient electrocatalysts for sustainable energy.

8. Ce-doped SnFe2O4 Supercapacitors

Study: Hydrothermal synthesis enhancing electrochemical performance.

Publication: Electrochimica Acta, 2024, 13 citations.

Impact: Improved energy storage capabilities of supercapacitors.

Conclusion

The candidate has a robust academic background, extensive teaching experience, and proven leadership capabilities, making them a strong contender for the Research for Best Researcher Award. Strengthening the portfolio with focused research publications and demonstrating broader impacts of their work will further enhance their prospects for this prestigious recognition.