Ali Oter | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Ali Oter | Artificial Intelligence | Best Researcher Award 

Assist. Prof. Dr. Ali Oter, Kahramanmaras Sutcu Imam University, Turkey

Ali Öter is a dedicated scholar and interdisciplinary researcher specializing in Electrical and Electronics Engineering, Biomedical Engineering , and Artificial Intelligence . He holds academic positions at both the Department of Electronics and Automation at Kahramanmaras Sutcu Imam University and the Department of Energy Systems Engineering at Gazi University. His work bridges foundational engineering with advanced computational intelligence, with key interests in sustainable and smart energy systems , solar PV technologies, machine learning , explainable artificial intelligence (XAI), and big data analytics. Dr. Öter’s career reflects a strong commitment to integrating innovative AI methodologies with practical applications in technology and healthcare.

Profile

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Education 🎓

Dr. Öter earned his Ph.D. in Electrical and Electronics Engineering from Kahramanmaras Sutcu Imam University in 2016. During his doctoral studies, he focused on the development of intelligent systems and analytical models for use in complex engineering tasks. His academic training provided a solid foundation in electronic circuit design, signal processing, and algorithmic modeling 🔧, which naturally evolved into the adoption of AI-driven solutions. The combination of rigorous engineering education and modern computational approaches shaped his ability to address multi-domain challenges with high technical precision and scientific depth.

Experience 🏢

Professionally, Dr. Öter has served as a faculty member in both electronics and energy engineering departments, contributing significantly to curriculum development and academic mentorship. At Kahramanmaras Sutcu Imam University, he teaches and guides students in automation systems, embedded technologies, and AI integration. At Gazi University, his research focuses on the optimization of energy systems and renewable energy forecasting using artificial intelligence. He also collaborates on interdisciplinary projects that explore AI applications in biomedicine, such as diagnostic modeling and medical data interpretation. Through these roles, he has cultivated a balance between theoretical instruction and impactful applied research, engaging with industrial stakeholders and academic peers alike.

Research Interests 🤖

Dr. Ali Öter’s research focuses on the integration of artificial intelligence with engineering and biomedical applications. His work explores the practical use of machine learning and deep learning techniques for solving complex problems in energy systems, medical diagnostics, and intelligent automation. He is particularly interested in explainable artificial intelligence (XAI) methods, which aim to provide transparency and interpretability in AI-driven healthcare solutions. Dr. Öter also investigates the optimization of sustainable energy systems, with a specific focus on solar photovoltaic (PV) systems, as well as the application of AI in the modeling and simulation of semiconductor devices and materials. Additionally, his research includes the exploration of data mining and big data analytics to enhance decision-making in technological and biomedical fields.

Publication Top Note 📄

Artificial intelligence-driven data generation for temperature-dependent current-voltage characteristics of diodes
FlatChem – Chemistry of Flat Materials, 2025. DOI: 10.1016/J.FLATC.2025.100847
Cited by articles focused on AI-based semiconductor modeling .

Deep learning-based LDL-C level prediction and explainable AI interpretation
Computers in Biology and Medicine, April 2025. DOI: 10.1016/j.compbiomed.2025.109905
Referenced in biomedical AI studies for cholesterol prediction.

An artificial intelligence model estimation for functionalized graphene quantum dot-based diode characteristics
Physica Scripta, 2024. DOI: 10.1088/1402-4896/AD3515
Cited in studies related to nanomaterials and AI-based diode simulation.

Explainable artificial intelligence for LDL cholesterol prediction and classification
Clinical Biochemistry, 2024. DOI: 10.1016/J.CLINBIOCHEM.2024.110791
Mentioned in research on XAI and medical diagnostic models.

Kardiyovasküler Hastalıkların Derin Öğrenme Algoritmaları İle Tanısı
Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, December 2024. DOI: 10.29109/gujsc.1506335
Referenced in Turkish-language studies on cardiovascular disease detection using deep learning.

Conclusion 🌟

Ali Öter stands at the intersection of engineering innovation and artificial intelligence application. His multidisciplinary approach has yielded contributions in both theoretical development and practical solutions, particularly in areas like sustainable energy systems  and medical diagnostics. Through his work, Dr. Öter continues to drive progress in next-generation intelligent systems while fostering academic excellence and technological advancement. His research is not only academically valuable but also socially impactful, addressing real-world challenges with clarity, precision, and foresight.

Akshaya Kumar Mandal | Machine learning | Best Researcher Award

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Dr. Akshaya Kumar Mandal | Machine learning | Best Researcher Award

Research Scholar, Assam University, India

Dr. Akshaya Kumar Mandal is a highly accomplished academic and researcher in the field of computer science. Currently serving as a Research Fellow at the Department of Computer Science, Assam University, India, he specializes in bio-inspired computing, machine learning, big data analytics, and bioinformatics. His research contributions span various interdisciplinary domains, focusing on solving complex problems in areas like disease detection, classification, and anomaly detection using innovative machine learning techniques. Dr. Mandal has an extensive educational background, holding a Ph.D. in Computer Science, along with M.Phil., M.Tech., and various other degrees, which have paved the way for his notable research career. His work is driven by a passion for developing practical, technology-driven solutions to pressing challenges in healthcare and beyond.

Profile

Education

Dr. Mandal’s academic journey reflects his deep commitment to learning and advancing knowledge in computer science. He obtained his Ph.D. from Assam University in 2024, with a thesis titled “Application of Bio-inspired Computing Techniques in Select Areas of Bioinformatics.” Prior to this, he completed his M.Phil. in Computer Science from F.M. University, Odisha in 2019, focusing on Ant Colony Optimization for solving NP-hard problems. He also holds an M.Tech. degree in Computer Science from Utkal University, Bhubaneswar, earned in 2007, where he conducted research on the comparison of multiple sequence alignment in DNA sequences. His educational foundation was laid with a Bachelor’s in Mathematics & Computer Applications from F.M. University, where he graduated with distinction. Dr. Mandal’s varied and comprehensive academic background has greatly contributed to his expertise in machine learning and bioinformatics.

Experience

Dr. Mandal has over 15 years of experience in teaching, research, and academic leadership. He served as a Senior Lecturer and Assistant Professor in the Department of Computer Science & Engineering at KIST, Bhubaneswar, from 2007 to 2018. During this time, he played a key role in delivering undergraduate and postgraduate courses, contributing to curriculum development, and mentoring students. Prior to this, he held lecturer positions at the Department of IT CET, Bhubaneswar, and the Department of Computer Science at NIIS Bhubaneswar. In addition to his teaching career, Dr. Mandal has an active research profile, with several years of experience as a Research Fellow in prominent institutions like Assam University, F.M. University, and Utkal University. His academic leadership and research endeavors have shaped his career trajectory in academia and research.

Research Interests

Dr. Mandal’s research interests are diverse, yet interconnected through a common theme of leveraging computational intelligence to solve real-world problems. His primary research areas include machine learning, bio-inspired computing, big data analytics, and bioinformatics. His work focuses on using machine learning for pattern recognition, anomaly detection, and disease classification, with applications in healthcare, such as heart disease prediction, skin disease detection, and disease diagnostics. Additionally, Dr. Mandal explores the intersection of biology and computation, particularly through bio-inspired algorithms like Ant Colony Optimization and Particle Swarm Optimization, to develop innovative solutions for bioinformatics problems, including DNA sequence alignment and codon selection. His interdisciplinary research aims to push the boundaries of artificial intelligence and computational biology.

Award

Based on the provided Curriculum Vitae, Dr. Akshaya Kumar Mandal appears to be a highly qualified and accomplished individual in the field of Computer Science, particularly in the areas of machine learning, bio-inspired computing, big data analytics, and bioinformatics. Below is a comprehensive evaluation of Dr. Mandal’s qualifications and contributions that make him a strong candidate for the Best Researcher Award.

Publication

Mandal, A.K., Dehuri, S., & Sarma, P.K.D. (2025). “Analysis of Machine Learning Approaches for Predictive Modeling in Heart Disease Detection Systems.” Biomedical Signal Processing and Control.

Mandal, A.K., & Sarma, P.K.D. (2024). “Usage of Particle Swarm Optimization in Digital Images Selection for Monkeypox Virus Prediction and Diagnosis.” Malaysian Journal of Computer Science.

Mandal, A.K., Sarma, P.K.D., & Dehuri, S. (2023). “A Study of Bio-inspired Computing in Bioinformatics: A State-of-the-art Literature Survey.” The Open Bioinformatics Journal.

Mandal, A.K., Sarma, P.K.D., & Dehuri, S. (2023). “Image-based Skin Disease Detection and Classification through Bioinspired Machine Learning Approaches.” International Journal on Recent and Innovation Trends in Computing and Communication.

Mandal, A.K., Mansur Barbhuiya, N., & Sarma, P.K.D. (2023). “A Hybrid Ant Colony Optimization Algorithm for Human Monkeypox DNA Codon Selection.” Journal of Propulsion Technology.

Mandal, A.K., Sarma, P.K.D., & Dehuri, S. (2024). “A Hybrid Machine Learning Based Cuckoo Search Clustering with Application of Image Recognition Techniques for Tomato Flu Skin Lesion Detection.” Machine Intelligence, Tools, and Applications.

Mandal, A.K., & Dehuri, S. (2020). “A Survey on Ant Colony Optimization for Solving Some of the Selected NP-Hard Problem.” Springer International Publishing.
These publications have been cited in various international articles, reflecting their significant contribution to the fields of machine learning and bioinformatics.

Conclusion

Dr. Akshaya Kumar Mandal’s academic and research journey demonstrates a deep commitment to advancing the field of computer science through innovative research and effective teaching. His work in bio-inspired computing, machine learning, and bioinformatics continues to make a notable impact on healthcare, bioinformatics, and computational biology. With an extensive teaching background and a solid record of research publications, Dr. Mandal is poised to contribute significantly to future developments in his areas of expertise. His passion for solving real-world problems using advanced computational techniques makes him a valuable asset to both academia and the broader scientific community.

Ramachandran | Machine Learning | Best Researcher Award

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Dr. Ramachandran | Machine Learning | Best Researcher Award

Assistant Professor | Parul institute of Engineering and technology-MCA | India

Dr. Ramachandran P is an esteemed Assistant Professor in the Department of Computer Science at Parul University, Vadodara, Gujarat, with over 11 years of experience in teaching and research. With a robust academic background, he holds a Ph.D. in Computer Science, along with an M.Sc. in Information Technology, an M.Phil. in Computer Science, and a B.Ed. in Computer Science. His passion for technology and innovation has led him to focus on areas such as machine learning, AI, cybersecurity, and software development. He has contributed significantly to the academic community, holding membership in the International Association of Engineers (IAENG) and the Computer Society of India (CSI). His technical expertise spans AWS, Microsoft certifications, Python, MATLAB, and various other cutting-edge technologies.

Profile

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Education

Dr. Ramachandran P’s academic journey reflects his dedication to advancing knowledge in the field of computer science. He completed his Ph.D. in Computer Science and holds multiple degrees, including an M.Sc. in Information Technology, M.Phil. in Computer Science, and B.Ed. in Computer Science. His foundational education began at institutions like Bharathiar University, Periyar University, and Tamilnadu Teacher Education University, shaping his academic trajectory. Throughout his career, Dr. Ramachandran has remained committed to continuous learning, always staying at the forefront of emerging technological trends and tools.

Experience

Dr. Ramachandran has held various academic roles over the years, with his most recent position as Assistant Professor at Parul Institute of Engineering and Technology, Parul University. His professional experience spans teaching, research, and development, including his previous roles at institutions such as KG College of Arts and Science and J.J College of Arts and Science. He has consistently demonstrated leadership in guiding students and colleagues, helping them develop essential technical and research skills. With a strong focus on delivering high-quality education, Dr. Ramachandran has worked with diverse technological platforms, contributing to the growth and development of the institutions where he has taught.

Research Interests

Dr. Ramachandran’s research interests lie primarily in the domains of machine learning, artificial intelligence (AI), cloud computing, and data mining. He has contributed to research on network security, cyber threats, IoT-based solutions, and deep learning techniques for predictive models. His innovative work often involves developing hybrid frameworks to address complex challenges in fields such as health diagnostics, cybersecurity, and real-time data analysis. His published papers and ongoing research focus on enhancing the accuracy and efficiency of machine learning models and exploring new techniques in AI to drive technological advancements.

Award

Dr. Ramachandran has earned recognition for his outstanding contributions to research and education. His work has led to multiple award nominations, including recognition for his work in machine learning and its applications in healthcare. His dedication to research and development in AI and cybersecurity continues to attract attention, and he is nominated for several prestigious awards, including the “Best Researcher Award” at the Cryogenicist Global Awards. His accolades reflect his commitment to advancing knowledge and fostering innovation within the academic and professional communities.

Publication Top Note

“Proactive Detection of Malicious Webpages Using Hybrid Natural Language Processing and Ensemble Learning Techniques”
Journal of Information and Organizational Sciences (2024)

“Proactive Detection of Malicious Webpages Using Hybrid Natural Language Processing and Ensemble Learning Techniques”
Journal of Information and Organizational Sciences (2024-12-18)

“Enhanced Cryptographic Performance and Security Using Optimized Edward-ElGamal Signature Scheme for IoT and Blockchain Applications” International Journal on Smart Sensing and Intelligent Systems (2024-11-10)

“Deep Learning-Based Detection of IoT Botnet Attacks: An Exploration of Residual Networks” International Journal of Safety and Security Engineering (2023)

Conclusion

Dr. Ramachandran P’s contributions to the academic and research fields have been both substantial and impactful. With a diverse range of skills in machine learning, AI, and cybersecurity, he continues to inspire the next generation of technology professionals. His work in enhancing machine learning models and his dedication to improving real-world applications in fields like healthcare and cybersecurity underscore his commitment to innovation. As an educator and researcher, Dr. Ramachandran’s contributions serve as a model for future advancements in technology. His work in AI, particularly in the development of hybrid frameworks and models for improved diagnostic accuracy, showcases his ability to make meaningful changes in both academic and applied research domains. Through his publications, awards, and ongoing efforts in research, Dr. Ramachandran remains a key