Inayet burcu Toprak | Manufacturing simulation | Best Researcher Award

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Dr. Inayet burcu Boprak | Manufacturing simulation | Best Researcher Award

Lecturer PhD at akdeniz university Turkey

Dr. İnayet Burcu Toprak is a passionate mechanical engineer and academic at Akdeniz University, specializing in advanced manufacturing and automation technologies. 🛠️✨ Her innovative research focuses on enhancing production techniques, particularly through additive manufacturing and powder metallurgy. She skillfully applies optimization strategies like the Taguchi method and multi-objective optimization to improve material characteristics such as tensile strength and precision. 📊🔍 Dr. Toprak also explores cutting-edge ultrasonic atomization to create high-quality metal powders, pushing forward the frontiers of 3D printing and aerospace engineering. 🚀🔧 Dedicated to sustainable and intelligent manufacturing, she bridges theoretical knowledge with practical applications to foster eco-friendly industrial growth. 🌱⚙️ As an active contributor in international scientific forums, she collaborates globally to advance automation and material science. Her work continues to inspire innovation in mechanical engineering, blending creativity with technology for a smarter, greener future. 🌍💡

Professional Profile

Education

Dr. İnayet Burcu Toprak pursued her academic journey in mechanical engineering, culminating in a Ph.D. from Akdeniz University in Antalya, Turkey. Her rigorous training laid the foundation for her expertise in advanced manufacturing and automation technologies. This academic background has been instrumental in her subsequent research and professional endeavors.

Professional Experience

Dr. Toprak has been serving as a faculty member at Akdeniz University’s Technical Sciences Vocational School, Department of Electronics and Automation, since 2002. In her role, she imparts knowledge on control and automation technologies, blending theoretical concepts with practical applications. Her extensive teaching experience underscores her commitment to nurturing the next generation of engineers.

Research Interests

Dr. Toprak’s research is centered on optimizing manufacturing processes, with a particular focus on additive manufacturing and powder metallurgy. She employs advanced methodologies like the Taguchi approach and multi-objective optimization to enhance material properties such as tensile strength and dimensional accuracy. Additionally, her exploration into ultrasonic atomization techniques aims to innovate metal powder production, advancing 3D printing and aerospace applications.

Awards and Honors

While specific awards and honors for Dr. Toprak are not publicly detailed, her contributions to the field are evident through her active participation in international scientific conferences and collaborations. Her work continues to influence the fields of automation, material science, and mechanical engineering, reflecting the recognition she has garnered within the academic community.

Publications Top Notes

1. Automatic recognition of Parkinson’s disease from sustained phonation tests using ANN and adaptive neuro-fuzzy classifier

Authors: MF Çağlar, B Çetişli, İB Toprak

Year: 2010

Citation: 89

Source: Mühendislik Bilimleri ve Tasarım Dergisi 1 (2), 59-64

2. EEG sinyallerinin dalgacık dönüşümü ve yapay sinir ağları ile analizi

Authors: İB Toprak

Year: 2007

Citation: 16

Source: Fen Bilimleri Enstitüsü

3. Ti-6Al-4V Süper Alaşiminin Yüksek Basinçli Soğutma Kullanilarak Frezelenmesinde Yüzey Pürüzlülüğünün Taguchi Yöntemi ile Optimizasyonu

Authors: İB Toprak, MF Çağlar, O Çolak, K Kıran, M Bayhan

Year: 2012

Citation: 6

Source: SDU International Technologic Science 4 (2), 30-39

4. Optimization of Surface Roughness by Using Taguchi Method in Milling of Ti-6Al-4 V Super-Alloy at High-Pressure Cooling Conditions

Authors: İB Toprak, MF Çağlar, O Çolak, K Kıran, M Bayhan

Year: 2012

Citation: 4

Source: Uluslararası Teknolojik Bilimler Dergisi 4 (2), 30-39

5. Ayrık dalgacık dönüşümü ve yapay sinir ağları kullanarak EEG sinyallerinden otomatik epilepsi teşhisi

Authors: İB Toprak, MF Çağlar, M Merdan

Year: 2007

Citation: 4

Source: IEEE 15, 11-13

6. Meslek yüksekokullarında akademik başarıya etki eden faktörler: Akdeniz Üniversitesi Teknik Bilimler Meslek Yüksekokulu örneği

Authors: İB Toprak, N Doğdu, M Öztürk

Year: 2017

Citation: 3

Source: Çankırı Karatekin Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 8 (1), 150-163

7. Multi-Objective Optimization Study on Production of AlSi10Mg Alloy by Laser Powder Bed Fusion

Authors: İB Toprak, N Dogdu

Year: 2024

Citation: 2

Source: Applied Sciences 14 (22), 10584

DOI: 10.3390/app142210584

8. Automatic Recognition of Epilepsy from EEG using Artificial Neural Network and Discrete Wavelet Transform

Authors: İB Toprak, MF Çağlar, M Merdan

Year: 2007

Citation: 2

Source: 2007 IEEE 15th Signal Processing and Communications Applications, 1-4

9. Optimization of tensile strength of AlSi10Mg material in the powder bed fusion process using the Taguchi method

Authors: İB Toprak, N Doğdu

Year: 2024

Citation: 1

Source: Scientific Reports 14, 1-9

10. Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches

Authors: İB Toprak

Year: 2025

Source: Scientific Reports 15 (1), 1-9

DOI: 10.1038/s41598-025-03307-x

11. Numerical Optimization of Laser Powder Bed Fusion Process Parameters for High-Precision Manufacturing of Pure Molybdenum

Authors: İB Toprak, N Dogdu, MU Salamci

Year: 2025

Source: Applied Sciences 15 (10), 5485

DOI: 10.3390/app15105485

Conclusion

Dr. İnayet Burcu Toprak stands as a dedicated academic and researcher in the realm of mechanical engineering. Her commitment to advancing manufacturing technologies and her active engagement in the scientific community underscore her pivotal role in shaping the future of engineering practices. Through her work, she continues to inspire innovation and excellence in the field.

Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

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Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

Dr. Abdulrahman Alnaim | Technology – Associate Professor at King Faisal University, Saudi Arabia

Dr. Abdulrahman Khalid Alnaim is an accomplished academic and researcher specializing in computer science and information security. With a strong foundation in computer information systems and management information systems, he has dedicated his career to advancing research in emerging technologies such as cybersecurity, cloud computing, and network architecture. His work is characterized by innovative approaches to securing next-generation networks and optimizing system performance, reflecting a commitment to both academic excellence and practical applications in the tech industry.

Profile:

Google Scholar

Education:

Dr. Alnaim earned his Ph.D. in Computer Science from Florida Atlantic University, USA, where he focused on developing secure and efficient computing models. He also holds a Master’s in Management Information Systems from Nova Southeastern University, USA, which enriched his understanding of integrating technology with business strategies. His academic journey began at King Faisal University, Saudi Arabia, where he completed his Bachelor’s degree in Computer Information Systems, laying the groundwork for his passion for research and technology. This diverse educational background has enabled him to approach complex problems with a multidisciplinary perspective.

Experience:

Dr. Alnaim has served at King Faisal University, Saudi Arabia, in various academic roles. Starting as a Teacher Assistant in 2012, he quickly advanced to become a Lecturer and later an Assistant Professor in the Management Information Systems Department within the School of Business. Throughout his tenure, he has contributed significantly to curriculum development, academic research, and student mentorship. His professional journey reflects a consistent commitment to fostering an environment of academic growth, research innovation, and knowledge dissemination.

Research Interests:

Dr. Alnaim’s research interests lie in the domains of cloud technologies, cybersecurity, and network architecture, with a particular focus on emerging trends like 5G/6G networks, network function virtualization (NFV), and edge computing. His work explores the development of robust security frameworks, optimized resource management strategies, and innovative architectures for next-generation networks. His research not only addresses theoretical challenges but also provides practical solutions for enhancing cybersecurity, system efficiency, and data integrity in complex digital environments.

Awards:

While Dr. Alnaim’s distinguished academic career is marked by numerous achievements, his contributions to research have earned him recognition within the academic community. His work has been cited extensively, reflecting its influence on contemporary studies in cybersecurity and network technologies. His dedication to research excellence is evident through his continuous pursuit of knowledge, innovative problem-solving, and commitment to advancing the field of computer science.

Publications 📚:

  1. “Zero Trust Strategies for Cyber-Physical Systems in 6G Networks” (2025) – Mathematics
    This paper discusses advanced security models tailored for cyber-physical systems in 6G environments. 🚀

  2. “Securing 5G Virtual Networks: A Critical Analysis of SDN, NFV, and Network Slicing Security” (2024) – International Journal of Information Security
    The article provides an in-depth analysis of security vulnerabilities and countermeasures in 5G networks. 🔐

  3. “Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework” (2024) – Sensors
    This research introduces the CyberGuard framework for enhancing trust management in edge and fog computing environments. 🌐

  4. “Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities” (2024) – Sensors
    A strategic approach to optimizing network slicing for IoT applications in smart cities. 🏙️

  5. “Classification of Alzheimer’s Disease Using MRI Data Based on Deep Learning Techniques” (2024) – Journal of King Saud University – Computer and Information Sciences
    This study leverages deep learning models to improve the early detection of Alzheimer’s disease using MRI data. 🧠

  6. “Machine-Learning-Based IoT–Edge Computing Healthcare Solutions” (2023) – Electronics
    Focuses on integrating machine learning with IoT and edge computing to enhance healthcare services. 💡

  7. “A Misuse Pattern for Modifying Non-Control Threats in NFV” (2022) – Future Internet
    Proposes a model to identify and mitigate non-control threats in network function virtualization environments. 🖥️

These publications have collectively garnered significant citations, underscoring their impact on academic research and industry practices. 📈

Conclusion:

Dr. Abdulrahman Khalid Alnaim exemplifies the qualities of an outstanding researcher, with a robust academic background, extensive research contributions, and a commitment to advancing the field of computer science and information security. His work in cybersecurity, cloud technologies, and network architecture has not only enriched academic discourse but also provided practical solutions to real-world challenges.

His innovative approach, combined with a strong publication record and active involvement in academic and research communities, makes him a deserving candidate for the Excellence in Research Award. Dr. Alnaim’s contributions reflect the values of academic rigor, intellectual curiosity, and a relentless pursuit of knowledge that this prestigious award seeks to honor.

Mr. Runyi Yang | 3D and Robotics | Best Researcher Award

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Mr. Runyi Yang | 3D and Robotics | Best Researcher Award

Mr. Runyi Yang, Imperial College London, United Kingdom

Mr. Runyi Yang is a promising researcher specializing in computer vision, robotics, and artificial intelligence, currently pursuing a Ph.D. in Computer Vision and Robotics at INSAIT, Bulgaria, under the mentorship of Prof. Luc Van Gool and Dr. Danda Pani Paudel. He holds a Master of Research (MRes) in AI and Machine Learning from Imperial College London, where he focused on camera relocalization and uncertainty quantification. His research encompasses Neural Radiance Fields (NeRFs), Gaussian Splatting, 3D reconstruction, and scene understanding, with notable contributions that have led to state-of-the-art results on public datasets. Recognized with the CICAI 2023 Best Paper Runner-up Award and several accolades in AI, robotics, and mathematics competitions, Runyi is dedicated to enhancing performance and efficiency in 3D rendering and scene understanding.

Professional Profile

Google Scholar

Suitability for the Best Researcher Award:

While Mr. Yang is still at an early stage in his career, his groundbreaking research in computer vision, robotics, and AI, along with his recognitions and publications, demonstrate his potential to become a leader in these fields. His expertise in NeRFs, 3D reconstruction, and autonomous driving simulation is highly relevant to modern technological challenges, making him a strong contender for the Best Researcher Award.

Education & Expertise:

Mr. Runyi Yang is a talented researcher with a focus on computer vision, robotics, and AI. He is pursuing a PhD in Computer Vision and Robotics at INSAIT, Bulgaria, under the guidance of Prof. Luc Van Gool and Dr. Danda Pani Paudel. He holds a Master of Research (MRes) in AI and Machine Learning from Imperial College London, where he worked on camera relocalization and uncertainty quantification.

Research Focus:

Runyi’s research spans Neural Radiance Fields (NeRFs), Gaussian Splatting, 3D reconstruction, and scene understanding. He has contributed to advancing 3D implicit representation and compositional zero-shot learning, achieving state-of-the-art results on public datasets.

Achievements & Honors:

He has been recognized with the CICAI 2023 Best Paper Runner-up Award and multiple other accolades in AI, robotics, and mathematics competitions.

Current Research Interests:

His interests include camera relocalization, NeRFs, and 3D vision, with a focus on improving performance and efficiency in 3D rendering and scene understanding.

Publication Top Notes:

  • “Mars: An instance-aware, modular and realistic simulator for autonomous driving”
    • Citations: 63
    • Published: 2023
  • “GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping”
    • Citations: 10
    • Published: 2024
  • “SUNDAE: Spectrally Pruned Gaussian Fields with Neural Compensation”
    • Citations: 4
    • Published: 2024
  • “City-scale continual neural semantic mapping with three-layer sampling and panoptic representation”
    • Citations: 4
    • Published: 2023
  • “Self-Aligning Depth-regularized Radiance Fields for Asynchronous RGB-D Sequences”
    • Citations: 2
    • Published: 2022