Serdar Ozcan | Computer Science | Best Researcher Award

Dr. Serdar Ozcan | Computer Science | Best Researcher Award

Dr. Serdar Ozcan | Computer Science – Canakkale Onsekiz Mart University, Turkey

Dr. Serdar Ozcan is an innovative researcher and seasoned industry professional whose work bridges the domains of artificial intelligence, energy sustainability, and digital transformation in manufacturing. With over three decades of leadership experience in Research & Development (R&D) and technological innovation, he has played a crucial role in shaping smart industry practices, particularly in ceramic and energy-intensive production lines. As an R&D Technology Development Manager at Kaleseramik, Türkiye’s leading ceramics manufacturer, Dr. Ozcan blends scientific inquiry with industry-scale implementation, making his research deeply impactful and immediately applicable. His expertise spans industrial automation, machine learning applications, piezoelectric energy harvesting, hydrogen energy systems, and predictive maintenance in smart factories.

Academic Profile

ORCID  |  Google Scholar

Education

Dr. Ozcan holds a Doctorate in International Business Administration, awarded in 2024 by Çanakkale Onsekiz Mart University, where he specialized in the integration of supervised artificial intelligence algorithms into predictive quality analysis in ceramic production lines. He earned his Master’s degree in Computer Engineering from the same university, where his thesis addressed the application of machine learning techniques to industrial process optimization. His undergraduate studies were completed in Electronics and Telecommunication Engineering at Yıldız Technical University, providing a robust foundation in control systems, embedded technologies, and communication protocols that later shaped his multidisciplinary career.

Experience

Over the course of more than 30 years, Dr. Ozcan has held a range of senior roles in the Turkish industrial and technology sectors, including General Manager, CTO, and Factory Manager. He currently leads cross-functional research and innovation teams, integrating academic research into commercial solutions in fields like robotics, IoT, and green manufacturing. His experience includes managing national and EU-funded projects, guiding more than 200 engineers and technicians, and aligning industrial output with carbon reduction and sustainability goals. He has also served as a mentor to junior researchers, providing guidance in both academic publishing and applied research design.

Research Interest

Dr. Ozcan’s research is deeply focused on artificial intelligence in manufacturing, energy efficiency, and behavioral digital transformation strategies. He is particularly passionate about Industry 4.0 technologies, hydrogen-based energy systems, and predictive analytics using machine learning and deep learning techniques. His recent projects focus on developing AI-supported decision systems to optimize quality control and reduce energy consumption in ceramic tile production. He is also exploring hybrid renewable energy systems involving piezoelectric generators, microgrid optimization, and smart factory integration. His ability to merge theoretical constructs with real-world applications makes his work highly relevant to industry leaders and academic peers alike.

Awards

Dr. Ozcan’s pioneering work has earned him several awards, most notably 1st Prize at the 2024 ISO Green Transformation Awards for his innovative R&D project on energy harvesting using piezoelectric ceramics. He was also recognized by the Turkish Ministry of Industry and Technology for his contributions to digital transformation in the manufacturing sector. His leadership in EU-funded sustainability initiatives has received commendations from project steering committees for outstanding technological impact and cross-border collaboration. These recognitions highlight his role as a key figure in both scientific innovation and practical implementation.

Publications

📘 “Supervised Artificial Intelligence Application in Ceramic Production Quality Forecasting” (2023), published in Journal of Intelligent Manufacturing – cited by 12 articles.
⚙️ “Energy Harvesting via Piezoelectric Ceramics for Sustainable Infrastructure” (2022), Renewable Energy Advances – cited by 17 articles.
🤖 “AI-Based Fault Detection in Industrial Motors Using Sensor Fusion” (2021), IEEE Access – cited by 24 articles.
🔋 “Hydrogen Integration in Smart Factory Grids” (2022), International Journal of Energy Research – cited by 9 articles.
🧠 “Deep Learning in Predictive Maintenance for Ceramic Production” (2023), Applied Soft Computing – cited by 14 articles.
🌱 “Digital Transformation Models for Sustainable Manufacturing” (2021), Technovation – cited by 18 articles.
🛰️ “Robotic Path Optimization Using Reinforcement Learning” (2020), Journal of Industrial Robotics – cited by 20 articles.

Conclusion

Dr. Serdar Ozcan stands as a beacon of translational research and sustainable innovation in the intersection of industry and academia. His expertise, spanning artificial intelligence, energy systems, and digital transformation, positions him as a frontrunner in the global movement toward smart and sustainable manufacturing. His recognition through awards, publications, and leadership roles reflect not just past accomplishments but a future-oriented trajectory filled with promise and continued impact. As such, he is an outstanding nominee for the Best Researcher Award, a testament to his lifetime commitment to innovation, academic excellence, and industrial advancement.

Preeti Sharma | Deep Learning | Women Researcher Award

Mrs . Preeti Sharma | Deep Learning | Women Researcher Award 

Assistant Professor , DIT University, Dehradun, Uttrakhand , India

Preeti Sharma is a dedicated researcher and educator currently pursuing a Ph.D. in Computer Science and Engineering at the University of Petroleum and Energy Studies, Dehradun. With a distinguished academic background including gold medals and high honors in her MTech and MCA degrees, Preeti has demonstrated excellence in her field. She is passionate about advancing the field of artificial intelligence and machine learning, focusing on generative adversarial networks (GANs) and deepfake detection.

Profile

Google Scholar

Education 

Preeti Sharma is pursuing a Ph.D. in Computer Science and Engineering at the University of Petroleum and Energy Studies, Dehradun, with her thesis submitted. She holds an MTech in Computer Science and Engineering from Uttarakhand Technical University, where she graduated as a gold medalist with an impressive 85%. Preeti completed her M.C.A. from M.D.U. (Campus), Rohtak, with a strong academic record of 82%.

Experience 

Preeti Sharma currently serves as a Junior Research Fellow and Teaching Assistant at the University of Petroleum and Energy Studies, Dehradun, where she has been contributing since April 2021. Prior to this, she was a Non-Teaching Staff member at the same university from September 2015 to March 2021. She also gained valuable experience as a Guest Lecturer at Arihant Institute of Technology, Haldwani, and an intern at the National Informatics Center (NIC).

Research Interests 

Preeti Sharma’s research interests include the application of Generative Adversarial Networks (GANs) in image and deepfake detection, robust CNN models, and advancements in digital forensics. Her work explores innovative methods for deepfake detection and image forgery using GAN-based models, contributing significantly to the field of multimedia tools and applications.

Awards 

Preeti Sharma has been recognized for her exceptional research and presentations. She received a certification for the best oral presentation at the International Young Researcher Conclave (IYRC-2024). Her paper on generative adversarial networks won first prize in the Research Conclave IYRC 2024 at UPES.

Publications 

  • Sharma, P., Kumar, M., Sharma, H.K. et al. Generative adversarial networks (GANs): Introduction, Taxonomy, Variants, Limitations, and Applications. Multimedia Tools and Applications (2024). Link
  • Sharma, P., Kumar, M., & Sharma, H.K. Robust GAN-Based CNN Model as Generative AI Application for Deepfake Detection, EAI Endorsed Trans IoT, vol. 10 (2024).
  • Sharma, P., Kumar, M., & Sharma, H.K. A generalized novel image forgery detection method using a generative adversarial network. Multimedia Tools and Applications (2023). Link
  • Sharma, P., Kumar, M., & Sharma, H.K. A GAN-based model of deepfake detection in social media. Procedia Computer Science, 218, 2153-2162 (2023).
  • Sharma, P., Kumar, M., & Sharma, H.K. Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation. Multimedia Tools and Applications, 82(12), 18117-18150 (2023).
  • Sharma, P., Kumar, M., & Sharma, H.K. A Guide to Digital Forensic: Theoretical to Software-Based Investigations. Perspectives on Ethical Hacking and Penetration Testing, IGI Global (2023). Link
  • Sharma, P., Kumar, M., & Sharma, H.K. CNN-based Facial Expression Recognition System Using Deep Learning Approach. Conference on Computational Intelligence and Information Retrieval CIIR (2021).
  • Sharma, P. Real Time Tracking System for Object Tracking using the Internet of Things (IoT). Conference on Computational Intelligence and Information Retrieval CIIR (2021).
  • Sharma, P. Leach and Improved Leach: A Review. International Journal of Advanced Research in Computer Science, Vol 10 (2019).

Conclusion

Preeti Sharma’s profile shows a strong foundation in research and technical expertise, with notable contributions to GANs and deepfake detection. Her academic achievements, innovative patents, and recognition in the field underscore her qualifications. To strengthen her candidacy for the Research for Women Researcher Award, she could emphasize the broader impact of her research and highlight her leadership or mentorship roles. Overall, her qualifications and achievements make her a strong contender for the award.