Manar Hamza | Computer Science Data mining | Best Researcher Award

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

professor atย  Prince Sattam bin Abd El Aziz University, China

๐Ÿ‘ฉโ€๐Ÿซ Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. ๐Ÿ’ป 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. ๐ŸŒ Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

scopus

Education ๐ŸŽ“

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018โ€“2021). ๐ŸŽ“ Masterโ€™s Degree in Computer Science from Sudan University of Science and Technology (2003โ€“2005). ๐ŸŽ“ B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995โ€“1999). ๐Ÿ“š Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience ๐Ÿ–ฅ๏ธ

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013โ€“present). ๐Ÿ‘ฉโ€๐Ÿ’ผ Supervisor and Coordinator roles in quality, academic advising, and measurement (2014โ€“2020). ๐Ÿ‡ธ๐Ÿ‡ฉ Lecturer at Omdurman Islamic University, Sudan (2005โ€“2012). ๐Ÿ‘ฉโ€๐Ÿ”ฌ E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors ๐Ÿ†

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. ๐Ÿ™Œ Recognized for voluntary services, including extracurricular activities and technical support for students and staff. โญ Esteemed arbitrator in scientific and innovation conferences. ๐Ÿ“œ Active contributor to enhancing the learning environment with innovative solutions.

Research Focus ๐Ÿ”

Data mining, text mining, and information security are core research areas. ๐Ÿ“Š Interested in qualitative research, outcome-based education, and e-learning systems. ๐ŸŒ Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. ๐Ÿ›ก๏ธ Exploring cybersecurity methods and their application in education and industry.

โœ๏ธ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. 1889โ€“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. 176โ€“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. 15486โ€“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. 98โ€“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. 153โ€“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. 258โ€“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. 11147โ€“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 candidateโ€™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.

Prof Dr. Claudio Urrea | Robotics | Best Researcher Award | 2751

Prof Dr. Claudio Urrea | Robotics | Best Researcher Award

Prof Dr. Claudio Urrea,ย  Universidad de Santiago de, Chileย 

Mr. Carlos Domรญnguez Acosta is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

 

Professional Profiles:

Google scholar

ORCID

๐Ÿ‘จโ€๐ŸŽ“ Education and Experience

I earned my B.Eng. from Universidad Tecnolรณgica de La Habana, Havana, Cuba, in 2014. Following graduation, I served as a professor at Universidad Tecnolรณgica de La Habana, contributing to the Faults Diagnosis and Parameters Estimation for Industrial Processes research group. Our work, focused on fuzzy logic for faults diagnosis, was presented internationally and published in a reputable journal. Currently pursuing a Ph.D. in Electric Engineering at Universidad de Santiago de Chile since March 2021, my research interests span robotics, automation, process control, artificial intelligence, faults diagnostics, and fault-tolerant control.

๐ŸŒ Research and Innovations

I have completed three research projects, with a citation index of 1 in Scopus/Web of Science. My cumulative impact factor for the last three years stands at 20.5. Aiming to bridge gaps in robotics, I’ve developed a novel 4-arm Delta parallel manipulator for the food industry, incorporating intelligent control and fuzzy logic techniques. These contributions form a foundation for future industrial applications and guide the next generation of researchers.

๐Ÿ† Achievements

Two journals published in Scopus, Web of Science, and PubMed indexes.Graduated two research scholars.Organized and presented at one conference.Received one award.

๐Ÿš€ Contribution to R&D and Extension Activities

My research supports robotics development, specifically a 4-arm Delta manipulator for the food industry. Intelligent control and fuzzy logic techniques contribute to a space lacking attention, providing foundations for industrial applications and inspiring future researchers.

๐Ÿ“ Self Declaration

I affirm the accuracy and completeness of the provided information. Any concealment of material information may lead to the termination of my application. I have read and agreed to the terms, conditions, and policies of the International Research Awards.

๐Ÿ“Šย Citation Metrics (Google Scholar):

Citations by: All โ€“ 35, Since 2018 โ€“ 30

h-index: All โ€“ 1, Since 2018 โ€“ 1

i10 index: All โ€“ 1, Since 2018 โ€“1