YASHWANTH H L | Composite samples | Best Researcher Award

Mr. YASHWANTH H L | Composite samples | Best Researcher Award

Researcher, Freelance, India

Yashwanth H L is a fresh graduate in Aeronautical Engineering with a strong passion for aircraft design and innovation. He possesses a solid understanding of mechanical principles, aerodynamics, and aircraft structures. Yashwanth is proficient in industry-standard software for design and analysis, including Ansys, CATIA, and Matlab. He has worked on various projects, such as characterizing reduced graphene oxide-filled glass fabric thermosets and analyzing the acoustic and vibrational properties of Calamus Rotang natural fiber composites. With a keen interest in research and development, Yashwanth has published papers in reputable journals and presented at international conferences. He is eager to contribute to the industry and continue learning and growing in his career. ๐Ÿš€

Profile

scholar

๐ŸŽ“ Education

Yashwanth H L holds a Bachelor’s degree in Aeronautical Engineering from Srinivas Institute of Technology, Valachil, Mangalore, with a CGPA of 7.3. He completed his pre-university education at St Mary’s P U College, H D Kote, with a percentage of 83.83%. Yashwanth’s academic background has provided a strong foundation for his research and industry work. Throughout his academic journey, he has demonstrated a commitment to excellence and innovation in the field of aeronautical engineering. ๐Ÿ“š

๐Ÿ‘จโ€๐Ÿ”ฌ Experience

Yashwanth H L has gained valuable experience through internships and projects. He worked as a Design and Analysis Intern at Brahmastra Aerospace, where he applied his skills in Ansys and other software. Yashwanth also completed internships in Matlab and Simulink simulations at Pegasus Aerospace and rocket design and analysis at Feynman Aerospace. These experiences have enabled him to develop practical skills and apply theoretical knowledge to real-world problems. ๐Ÿš€

๐Ÿ” Research Interest

Yashwanth H L’s research focuses on materials science, structural analysis, and aerodynamics. He has worked on projects involving reduced graphene oxide-filled glass fabric thermosets and Calamus Rotang natural fiber composites. Yashwanth’s research aims to develop innovative materials and solutions for aerospace applications. His work has potential implications for improving aircraft performance, safety, and efficiency. ๐Ÿ”

๐Ÿ† Awards

Yashwanth H L has received recognition for his research and academic achievements. He has published papers in reputable journals, including Nature’s Scientific Reports and Results in Engineering, Elsevier. Yashwanth has also presented at international conferences, such as the International Conference on Nanotechnology and the SME-2023 conference. These achievements demonstrate his potential as a researcher and innovator in the field of aeronautical engineering. ๐ŸŽ‰

๐Ÿ“š Publications

1. Mechanical characterization & regression analysis of Calamus rotang based hybrid natural fibre composite with findings reported on retrieval bending strength ๐Ÿ“Š
2. Characterization and Mechanical Studies of Reduced Graphene Oxide Filled Glass Fabric Thermosets ๐Ÿ”ฌ
3. Evaluation of Mechanical, Acoustic and Vibration characteristics of Calamus Rotang based Hybrid natural fiber composite

Conclusion

Yashwanth’s research experience, publication record, technical skills, and collaboration abilities make him a strong candidate for the Best Researcher Award. With further development and refinement, he has the potential to make significant contributions to the field of aeronautical engineering ยน

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.