Serdar Ozcan | Computer Science | Best Researcher Award

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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.

Perepi Rajarajeswari | Computer science | Best Researcher Award

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Dr. Perepi Rajarajeswari | Computer science | Best Researcher Award

Associate professor at Vellore Institute of Technology, India

Dr. Perepi Rajarajeswari, an accomplished academician and researcher, holds an impressive academic background, with a PhD in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad. She is currently an Associate Professor in the Department of Software Systems, School of Computer Science and Engineering at Vellore Institute of Technology (VIT), Tamil Nadu. With vast teaching experience in diverse computer science disciplines, Dr. Rajarajeswari has made notable contributions to fields like Blockchain technology, Software Engineering, Data Mining, Artificial Intelligence, and Internet of Things, among others. Over the years, she has garnered respect for her knowledge and expertise in both teaching and research.

Profile:

Google scholar

Education:

Dr. Rajarajeswari’s academic journey began with a Bachelor’s degree (B.Tech) in Computer Science from Sri Venkateswara University, Tirupati, in 2000. She then completed her Master of Technology (M.Tech) in Computer Science at Jawaharlal Nehru Technological University, Hyderabad, in 2008. Dr. Rajarajeswari earned her Ph.D. in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad, in 2017. Her educational background has equipped her with a solid foundation in the ever-evolving field of computer science.

Experience:

Dr. Rajarajeswari has a distinguished career as an educator and researcher. She began her career as a lecturer at Madanapalle Institute of Technology and Science in 2000. Over the years, she has progressively advanced in academia. From Assistant Professor to Associate Professor, she has worked at various reputed institutions, including Madanapalle Institute of Technology and Science, Aditya College of Engineering, Kingston Engineering College, and Sreenivasa Institute of Technology and Management Studies. Since 2022, Dr. Rajarajeswari has been serving as an Associate Professor at VIT, contributing significantly to both research and academic development. Her wide-ranging experience in teaching and research has made her a pivotal figure in her academic community.

Research Interests:

Dr. Rajarajeswari’s research interests are multi-disciplinary and encompass cutting-edge areas in computer science and engineering. Her expertise spans Blockchain technology, Software Engineering, Software Architecture, Data Mining, Artificial Intelligence, Cloud Computing, and the Internet of Things. She is particularly passionate about exploring the intersections of these technologies, such as Mobile Cloud Computing and Cyber-Physical Systems, and their real-world applications. Her focus on advanced computational techniques aims to address complex problems in fields such as healthcare, smart systems, and secure architectures.

Awards:

Dr. Rajarajeswari’s work has been recognized by various academic and professional organizations. While specific awards are not detailed, her commitment to excellence in education, research, and innovation has earned her the respect of peers and students alike. Her contributions to sponsored projects and her active participation in research have placed her at the forefront of her field.

Publications:

Dr. Rajarajeswari has authored several influential publications in reputed journals and conferences. Some of her key publications include:

  1. “Thermomagnetic Bioconvection Flow in a Semi trapezoidal Enclosure Filled with a Porous Medium Containing Oxytactic Micro-Organisms: Modeling Hybrid Magnetic Biofuel Cells,” ASME Journal of Heat and Mass Transfer, SCIE Journal, 2025.

  2. “Finite Element Numerical Simulation of Free Convection Heat Transfer in a Square Cavity Containing an Inclined Prismatic Obstacle with Machine Learning Optimization,” Heat Transfer-Wiley, 2025.

  3. “Magneto-convective flow in a differentially heated enclosure containing a non-Darcy porous medium with thermal radiation effects—a Lattice Boltzmann simulation,” Journal of the Korean Physical Society, 2025.

  4. “Deep Learning Techniques for Lung Cancer Recognition,” Engineering, Technology & Applied Science Research, 2024.

  5. “Prediction of Heart Attack Risk and Detection of Sleep Disorders Using Deep Learning Approach,” International Research Journal of Multidisciplinary Scope, 2024.

  6. “Object Oriented Design Approach for the Implementation of Secure Aircraft Management System Based on Machine Learning,” Nanotechnology Perceptions, 2024.

  7. “A Deep Learning Computational Approach for the Classification of COVID-19 Virus,” Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2022.

Her works have been cited by numerous scholars, contributing significantly to advancing research in computational intelligence, data mining, and machine learning.

Conclusion:

Dr. Perepi Rajarajeswari’s academic achievements and research contributions underscore her dedication to advancing the field of Computer Science and Engineering. Her diverse experience, coupled with her deep understanding of contemporary technological issues, places her as a leader in her domain. With a passion for teaching and a commitment to solving real-world problems, Dr. Rajarajeswari continues to inspire students and researchers alike. Through her ongoing work in research and development, she is poised to make further impactful contributions in the fields of AI, Blockchain, Cloud Computing, and more.

Zhenyu Gao | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Zhenyu Gao | Engineering | Best Researcher Award

Assoc. Prof. Dr. Zhenyu Gao | Engineering – Associate Professor at Northeastern University at Qinhuangdao, China

Zhenyu Gao is a distinguished Associate Professor at the School of Control Engineering, Northeastern University at Qinhuangdao. His academic journey is marked by groundbreaking research in control science and engineering, particularly in unmanned systems, autonomous intelligence, and intelligent transportation systems. Gao’s work is recognized globally for its innovative approaches to vehicular platoon control and multi-agent systems, contributing significantly to both theoretical advancements and practical applications in the field. His dedication to academic excellence is reflected in numerous prestigious awards, influential publications, and leadership roles in scientific communities.

Profile:

Orcid

Education:

Zhenyu Gao earned his Ph.D. in Control Science and Engineering from Dalian Maritime University, China, where he developed a strong foundation in advanced control theories. Prior to his doctoral studies, he completed his Bachelor’s degree in Automation at Shandong University of Technology. His educational background reflects a consistent trajectory of academic rigor, equipping him with the analytical skills and technical expertise necessary to excel in complex research areas.

Experience:

Currently serving as an Associate Professor, Gao has played a pivotal role in advancing research in control engineering. His professional journey includes leading several high-impact projects funded by national and provincial research foundations. Gao has also contributed as an Associate Editor for reputable journals and serves as a reviewer for top-tier publications in intelligent transportation systems and vehicular technology. His role as a mentor has guided numerous graduate students, fostering the next generation of researchers in his field.

Research Interests:

Gao’s research interests span unmanned systems, autonomous intelligence, collaborative control, multi-agent systems, and intelligent transportation systems. His work focuses on developing robust control strategies for vehicular platoons, addressing challenges related to actuator nonlinearities, sensor attacks, and real-time system performance. Gao’s innovative approaches have significantly advanced the understanding of dynamic systems and their applications in modern transportation and automation technologies.

Awards 🏆:

  • Wiley Top Downloaded Article Award (2023): Recognizing his highly cited publication in intelligent transportation systems.

  • Excellent Master Thesis Advisor of Northeastern University (2023): Honoring his mentorship and academic guidance.

  • Excellent Master Thesis Advisor of Liaoning Province (2024): Acknowledging his contributions to graduate education and research excellence.

Selected Publications 📚:

  1. Gao, Z., Li, X., Wei, Z., Liu, W., Guo, G., & Wen, S. (2025). Observer-based secure predefined-time control of vehicular platoon systems under attacks in sensors and actuators – IEEE Transactions on Intelligent Transportation Systems 📈 (Cited by 150+)
  2. Gao, Z., Liu, W., Wei, Z., & Guo, G. (2025). Adaptive finite-time prescribed performance control of vehicular platoons with multilevel threshold and asymptotic convergence – IEEE Transactions on Intelligent Transportation Systems 📊 (Cited by 120+)
  3. Gao, Z., Li, X., Wei, Z., Guo, G., Wen, S., Zhao, Y., & Mumtaz, S. (2025). Fixed-time secure control for vehicular platoons under deception attacks on both sensor and actuator via adaptive fixed-time disturbance observer – IEEE Internet of Things Journal 🚗 (Cited by 95+)
  4. Gao, Z., Li, X., Wei, Z., & Guo, G. (2024). Adaptive fuzzy finite-time asymptotic tracking control of vehicular platoons with nonsmooth asymmetric input nonlinearities – IEEE Transactions on Intelligent Transportation Systems 🚀 (Cited by 85+)
  5. Gao, Z., Wei, Z., Liu, W., & Guo, G. (2025). Adaptive finite-time prescribed performance control with small overshoot for uncertain 2-D plane vehicular platoons – IEEE Transactions on Vehicular Technology 🛰️ (Cited by 80+)
  6. Gao, Z., Sun, Z., & Guo, G. (2024). Adaptive predefined-time tracking control for vehicular platoons with finite-time global prescribed performance independent of initial conditions – IEEE Transactions on Vehicular Technology 🚦 (Cited by 75+)
  7. Gao, Z., Zhang, Y., & Guo, G. (2023). Adaptive fixed-time sliding mode control of vehicular platoons with asymmetric actuator saturation – IEEE Transactions on Vehicular Technology 🛣️ (Cited by 60+)

Conclusion:

Zhenyu Gao’s distinguished career reflects an exceptional blend of academic rigor, innovative research, and impactful mentorship. His contributions to control science and engineering, particularly in autonomous systems and intelligent transportation, have set new benchmarks in the field. Gao’s extensive publication record, combined with his leadership in research projects and academic communities, underscores his suitability for the “Best Researcher Award.” His work continues to influence and inspire advancements in control engineering, making him a worthy candidate for this prestigious recognition.

Madhusmita Das | software engineering | Best Researcher Award

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Ms. Madhusmita Das | software engineering | Best Researcher Award

Research Scholar, National Institute of Technology Karnataka, Surathkal, India

Madhusmita Das is a Ph.D. candidate at the Institute of Technology Karnataka, Surathkal, focusing on reliability assessment of safety-critical systems through advanced machine learning models and bio-optimization algorithms. With a solid foundation in data science, she excels in analyzing user behavior and engagement, translating insights into impactful business strategies and research outcomes.

Profile

Scopus

Strengths for the Award

Diverse Research Interests and Publications: Madhusmita Das has a broad range of research interests encompassing machine learning, bio-optimization algorithms, reliability analysis, and verification methods. Her work spans numerous relevant topics, including safety-critical systems, software defect prediction, and reliability assessment of drone systems. This wide-ranging expertise is evident in her substantial number of high-impact publications across various prestigious conferences and journals.

Impactful Contributions: Her research on “Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models” and other related works demonstrates her ability to apply complex algorithms to practical problems, making significant contributions to the field of machine learning and system reliability.

Recognition and Awards: The provisional selection for the “Best Researcher Award” for her work in hybrid bio-optimized algorithms reflects her recognition in the academic community. Her technical paper presentation at state levels and qualified GATE also underscore her expertise and commitment to her field.

Extensive Experience and Skills: Madhusmita’s background in programming, big data technologies, machine learning, and data visualization tools is robust. Her skills in managing research from inception to publication further demonstrate her comprehensive approach and capability.

Areas for Improvement

Research Diversity and Novelty: While her research is extensive, focusing on a few emerging or less explored areas could enhance the novelty of her contributions. This might involve delving into cutting-edge topics like quantum computing applications in machine learning or the integration of AI with emerging technologies.

Broader Impact and Collaboration: Strengthening collaborations with other researchers or institutions could broaden the impact of her work. Collaborations can lead to interdisciplinary research opportunities, potentially increasing the scope and application of her findings.

Public Engagement: Expanding efforts to disseminate research findings to non-specialist audiences or through popular science platforms could enhance the visibility and impact of her work. Engaging in public lectures, webinars, or media could further her influence.

Education 🎓

Madhusmita is pursuing her Ph.D. in Computer Science/Information Technology at the Institute of Technology Karnataka, Surathkal (2019-Present), with a CGPA of 8.67. Her research covers topics such as verification & validation, reliability analysis, and bio-optimization algorithms. She completed her M.Tech. with honors from NIT Raipur in 2012 and her B.Tech. from SOA University, Bhubaneswar, in 2008.

Experience 💼

Madhusmita has served as an Assistant Professor at MVJ College of Engineering, Bangalore (Nov 2013 – Nov 2016), and Sanjeevani College of Engineering, Pune (Jul 2012 – Nov 2013). Her work spans teaching, research, and project mentoring, contributing significantly to the academic and research communities.

Research Interests 🔬

Her research interests include verification and validation methods, formal techniques, risk analysis, system reliability, and software defect prediction. She is also passionate about machine learning and computational intelligence, focusing on bio-optimization algorithms and optimization techniques.

Awards 🏆

Madhusmita was provisionally selected for the “Best Researcher Award” for her work on hybrid bio-optimized algorithms in machine learning, set to be awarded in 2024. She also earned recognition for her state-level presentation on AI in 2011 and qualified GATE in 2010.

Publications Top Notes📚

Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models: A Software Defect Prediction Case Study, Mathematics, 2024, MDPI.

Formal Specification and Verification of Drone System using TLA+: A Case Study, 2022 IEEE/ACIS 23rd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2022, pp. 156-161.

Reliability Assessment of a Drone Communication System using Truncated Markov Analysis, 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023, pp. 1-6.

Fault Tree Analysis: A Review on Analysis, Simulation Tools, and Reliability Dataset for Safety-critical Systems, International Conference on Mining for a Greener Future: Technological developments and Sustainable Practices (ICMFGF 2024), 2024, NITK Surathkal, India.

Safety Assessment of Railway Crossing Junction Via Petri Nets, 5th International Conference on Innovative Trends In Information Technology ICITIIT’24, 2024, IIIT Kottayam, India, pp. 1-8.

Conclusion

Madhusmita Das is a strong candidate for the Best Researcher Award due to her significant contributions to machine learning, data science, and system reliability. Her extensive publication record, impactful research, and recognized achievements highlight her as a leading figure in her field. Addressing areas for improvement, such as exploring novel research avenues and enhancing public engagement, could further strengthen her candidacy and broaden the impact of her work.

Jawad Khan | Software Engineering | Best Researcher Award

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Prof Dr.Jawad Khan | Software Engineering | Best Researcher Award

Assistant Professor Gachon University  South Korea

Dr. Jawad Khan is an Assistant Professor at Gachon University, South Korea. With extensive experience in data science and artificial intelligence, Dr. Khan’s work focuses on semantic learning, machine learning, and natural language processing. He has made significant contributions to the fields of text mining, software engineering, and cloud computing. Dr. Khan is dedicated to advancing research in these areas through innovative approaches and interdisciplinary collaboration.

Profile

Scopus

Education

🎓 Dr. Khan completed his Ph.D. in Computer Science and Engineering from Kyung Hee University, South Korea, in 2020. His thesis, “An Ensemble-based Effective Features Engineering and Intelligent Unified Framework for Sentiment Analysis,” was supervised by Prof. Young-Koo Lee. He holds an M.Sc. in Computer Science from Kohat University of Science and Technology, Pakistan, where he developed a computerized hotel management system under the guidance of Mr. Qadeem Khan. He earned his B.Sc. in Computer Science from the University of Malakand, Pakistan.

Experience

💼 From October 2020 to February 2023, Dr. Khan served as a Postdoctoral Fellow in the Department of Applied Artificial Intelligence at Hanyang University, South Korea, focusing on big data mining and sentiment analysis. Prior to this, he was a Research Associate at Kyung Hee University, South Korea, from March 2014 to September 2020, where he worked on social media analytics and sentiment classification.

Research Interests

🔍 Dr. Khan’s research interests encompass data science, artificial intelligence, natural language processing, semantic learning, machine learning, deep learning, text mining, data mining, software engineering, computer vision, cloud computing, and IoT. He is particularly focused on developing intelligent frameworks for sentiment analysis and enhancing feature engineering techniques.

Awards & Honors

🏆 Dr. Khan has been honored with a fully funded Ph.D. scholarship from Kyung Hee University, which he held from March 2014 to September 2020. This prestigious award supported his doctoral studies and research in computer science and engineering.

Publications

📝 Dr. Khan has numerous publications in esteemed journals and conferences. Here are some of his notable works:

  1. Factors influencing vendor organizations in the selection of DevOps for global software development: an exploratory study using a systematic literature review. Cognition, Technology & Work (2023).
  2. Investigating the dynamic relationship between stigma of fear, discrimination and employees performance among healthcare workers during Covid-19 pandemic. Cognition, Technology & Work (2023).
  3. An empirical study for prioritizing issue of software project management team. Cognition, Technology & Work (2023).
  4. Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection. IEEE Access 11 (2023).
  5. Monkeypox detection using CNN with transfer learning. Sensors 23, no. 4 (2023).