Kanta Prasad Sharma | Computer Science | Best Innovation Award

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Dr. Kanta Prasad Sharma | Computer Science | Best Innovation Award

Associate Professor at Amity University Greater Noida Campus, India

Dr. Kanta Prasad Sharma is a seasoned academic and researcher with over 14 years of experience in the field of Computer Science and Engineering. Currently serving as an Associate Professor at Amity University, Uttar Pradesh, he has held various teaching positions across multiple esteemed institutions. His expertise spans a wide range of research areas, including Internet of Things (IoT), Machine Learning, and Artificial Intelligence, among others. In addition to his teaching, Dr. Sharma has made significant contributions to research, authoring numerous patents and publications. His dedication to education and research has earned him recognition from academic peers and institutions.

Profile

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Education

Dr. Sharma holds a Ph.D. in Information Technology from Amity University, Rajasthan, awarded in 2019. He completed his MCA from GLA Institute of Technology & Management, Mathura, in 2007, and his BCA from Rajiv Institute of Technology & Management, Mathura, in 2003. His academic background is rooted in a strong foundation in Computer Science, with a commitment to advancing technology through both teaching and research.

Experience

Dr. Sharma’s career in academia spans over a decade, during which he has held various teaching positions. He is currently an Associate Professor at Amity University, Greater Noida Campus, where he has been contributing to the academic community since September 2024. His previous roles include Assistant Professor positions at GLA University, Chandigarh University, GL Bajaj Group of Institutions, Rajiv Academy for Technology & Management, and several other prestigious institutions. He has also served as a Research Coordinator and Head of Departments, overseeing significant academic and research responsibilities. Additionally, Dr. Sharma has engaged with industry as an Industrial Spoc for Samsung Prism Research Project.

Research Interests

Dr. Sharma’s research interests are deeply entrenched in emerging technologies, focusing primarily on Internet of Things (IoT), Machine Learning, Artificial Intelligence, and their applications in real-world problems. His work explores the intersection of these technologies in areas such as smart healthcare, IoT-based systems, predictive models, and automation. Dr. Sharma is also deeply involved in the development of practical solutions through his innovative research, leading to the publication of patents and articles in reputable international journals. His academic work, especially in IoT and AI, aims to address global challenges by creating efficient and scalable solutions.

Awards

Dr. Sharma has been acknowledged for his contributions to both teaching and research in various capacities. His academic excellence is reflected in his strong research gate scores, citation counts, and the number of patents granted to him at national and international levels. In addition to his academic achievements, he has been nominated for multiple awards in recognition of his significant impact on the academic and research community, particularly in fields like Artificial Intelligence, IoT, and Machine Learning.

Publications

Dr. Sharma has contributed to a number of publications in well-known international journals. Below are some of his selected works:

Sharma, K., et al. (2021). “An IoT-Based Autonomous Firefighting Drone Using Machine Learning,” Journal of Internet of Things, 2021.

Sharma, K., et al. (2021). “IoT System for Monitoring Agriculture,” Agricultural Technology Journal, 2021.

Sharma, K., et al. (2021). “IoT-Based Automatic Door Control System,” Journal of IoT and Automation, 2021.

Sharma, K., et al. (2022). “Intelligent Face Recognition Using Deep Recurrent Neural Networks,” AI and Vision Technology Journal, 2022.

Sharma, K., et al. (2022). “IoT-Based Newborn Care System,” International Journal of Health Systems, 2022.

His work has garnered significant attention in the research community, evidenced by citations from other notable scholars in the fields of IoT, AI, and Machine Learning.

Conclusion

Dr. Kanta Prasad Sharma’s career is a testament to his unwavering dedication to education, innovation, and research. With a rich academic background and extensive professional experience, he continues to make significant contributions to the fields of Computer Science and Engineering. His research on IoT, Machine Learning, and Artificial Intelligence is pushing the boundaries of technological applications, and his work has far-reaching implications for industries such as healthcare, agriculture, and automation. As an academic and researcher, Dr. Sharma remains committed to advancing knowledge and nurturing future generations of engineers and researchers.

Ameni Chetouane | Computer Science | Best Researcher Award

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Dr. Ameni Chetouane | Computer Science | Best Researcher Award

Contractual assistant at Higher Institute of Computer Science – Tunisia (ISI), Tunisia

Ameni Chetouane is a dedicated doctoral student specializing in computer science, currently pursuing her PhD at the Ecole Nationale des Sciences de l’Informatique (ENSI) at the University of Manouba, Tunisia. Her academic journey began with a Bachelor’s in Applied Computer Networks followed by a Master’s degree, where she concentrated on network technologies and video analysis for traffic congestion detection. She is deeply involved in research aimed at securing Software Defined Networking (SDN) systems against cyber-attacks using Artificial Intelligence (AI) methods.

Profile

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Education

Ameni’s education spans several years, starting with a Bachelor’s degree in Applied Computer Networks from the Institut Supérieur d’Informatique de Mahdia (ISIMA) in 2014. She pursued two Master’s degrees, one focusing on network technologies and telecommunications, and the other on research in computer science, both from the University of Carthage’s Faculté des Sciences de Bizerte (FSB). Her doctoral studies, commenced in 2021, are focused on the application of AI for intrusion detection systems (IDS) in SDN environments, with a goal to combat cyber-attacks.

Experience

Ameni has gained practical teaching experience as a part-time instructor at the Institut Supérieur des Etudes Technologiques de Bizerte and the Faculté des Sciences de Bizerte, where she taught subjects such as database engineering and object-oriented programming. Her internships, including research at LaBRI, University of Bordeaux, and her professional project at Millénia Engineering, have allowed her to apply theoretical knowledge in real-world network and software development projects.

Research Interests

Ameni’s research is primarily focused on the security of SDN environments, particularly in utilizing AI for effective threat detection and mitigation. Her doctoral thesis specifically explores AI-driven solutions for securing SDN systems against Distributed Denial of Service (DDoS) attacks. She aims to improve the performance of IDSs by incorporating machine learning (ML) and continual learning methods into SDN security architectures, ensuring adaptive and real-time defenses against evolving threats.

Awards

Ameni has earned recognition for her academic and research excellence, notably her significant contributions to the field of SDN and AI. Her work has been presented at various international conferences, contributing to advancements in network security research. While specific awards are not listed, her impact within the academic community, through her publications and conference participations, is considerable.

Publications

Ameni Chetouane, Sabra Mabrouk, Imen Jemili, and Mohamed Mosbah. “A comparative study of vehicle detection methods in a video sequence.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2019.

Ameni Chetouane, Sabra Mabrouk, Imen Jemili, and Mohamed Mosbah. “Vision-based vehicle detection for road traffic congestion classification.” Concurrency and Computation: Practice and Experience, 2022.

Ameni Chetouane, Sabra Mabrouk, and Mohamed Mosbah. “Traffic congestion detection: Solutions, open issues, and challenges.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2020.

Ameni Chetouane and Kamel Karoui. “A survey of machine learning methods for DDoS threats detection against SDN.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2022.

Ameni Chetouane, Kamel Karoui, and Ghayth Nemri. “An intelligent ML-based IDS framework for DDoS detection in the SDN environment.” International Conference on Advances in Mobile Computing and Multimedia Intelligence, Springer, 2022.

Ameni Chetouane and Kamel Karoui. “DDoS detection approach based on continual learning in the SDN environment.” International Conference on Hybrid Intelligent Systems, Springer, 2022.

Ameni Chetouane and Kamel Karoui. “Risk-based intrusion detection system in Software Defined Networking.” Concurrency and Computation: Practice and Experience, 2023.

Conclusion

Ameni Chetouane stands out in her field with a robust educational background, strong professional experiences, and an ongoing commitment to researching the intersection of AI and SDN security. Through her published works, she has made significant contributions to securing networks using intelligent methods, focusing on solving complex cyber threats in modern network infrastructures. As she continues her research, her work promises to shape the future of AI-driven cybersecurity in SDN environments.