0000-0003-1934-4535 About
Dr. Yogesh Kumar Sharma is an esteemed academic and researcher with over 18 years of experience in teaching, research, and educational leadership in Computer Science and Engineering (CSE). He holds a Ph.D. in Computer Science and an MTech in Software Engineering. Dr. Sharma is currently serving as the Professor and Cohort Professor Incharge of Computer Science and Engineering at Koneru Lakshmaiah Education Foundation (K L Deemed to be University), Vaddeswaram, Guntur District, AP., where he has demonstrated outstanding leadership in both education and research.
With a strong research focus on IoT, Cloud Computing, and AI & ML, Dr. Sharma has made significant contributions to the academic community. He completed his Ph.D. in Computer Science in 2014. He has published more than 200 papers in national and international reputed journals during his research career. He has published over 90 articles in Scopus-indexed journals, with more than 20 publications in SCI journals, and his work has been cited over 1500 times. His research excellence is reflected in his h-index of 20, signifying the high impact and relevance of his work in the field.
Additionally, Dr. Sharma holds over 12 patents in India and the UK, 11 Books, and 25 Book Chapters in National & International Publications, further showcasing his innovative technological contributions. Dr. Sharma was also invited as a Guest Lecturer for Students in the Master's Program in Information Technology on behalf of the National University of Science and Technology, Muscat, Oman. Dr. Sharma is a Paper Setter, Answer Sheet Evaluator, and Practical Examiner in many Private & Government Universities. Dr. Sharma enrolled for a Ph.D. Evaluator and Final Viva-Voce Examiner in Private & Government Universities. Dr. Sharma is a life member of ACM, IAENG, IACSIT, CSTA, and UACEE. Dr Sharma organised 3 International & National Conferences.
Dr. Sharma has a distinguished record of academic service. He is an editor for Springer Nature’s BMC Information and Decision Making and serves on the editorial boards of several prestigious journals, including those published by Springer and Elsevier. His editorial responsibilities reflect his deep expertise and influence in shaping contemporary research.
Dr Sharma has dedicated himself to mentoring over 15 PhD candidates and 35+ MTech students, helping them develop critical research skills and contributions. His students have achieved significant academic and professional success under his guidance. His leadership as the Cohort Professor in Charge and Research Coordinator of the CSE department has fostered an environment conducive to research excellence and innovation.
Dr. Sharma is also an active participant in the academic community, serving as a peer reviewer for several high-impact journals, including IEEE, Wiley, Springer, and ScienceDirect. His thorough reviews and thoughtful feedback have helped shape the quality of academic work in his field.
Having served on the organising committees of numerous international conferences, Dr. Sharma continues to contribute to developing research initiatives and industry-academia collaboration. His work has advanced academic theory and significantly impacted the practical application of technologies in the industry.
Employment
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Koneru Lakshmaiah Education Foundation Professor2022 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (89)
- A comparative analysis of PoS tagging tools for Hindi and Marathi Save
- Innovative Approaches in Differential Equation Analysis Using the Enhanced Differential Transform and Homotopy Perturbation Method Save
- A Hybrid Deep Learning Framework for High-Precision and Efficient Cervical Cancer Detection Save
- A Modified Chaos-Driven Enhanced Cryptographic Framework for Lightweight and Robust IoT Security in Resource-Constrained Devices Save
- A hybrid chaos-based cryptographic framework for lightweight IoT security: enhancing efficiency and security in low-power devices Save
- A hybrid deep learning and fuzzy logic framework for robust tomato disease detection and classification Save
- Blockchain-enabled federated learning framework with hybrid CNN-LSTM anomaly detection for secure edge IoT networks Save
- Harris Hawks-tuned severity-aware YOLOv8 instance segmentation framework for vehicle damage assessment Save
- Hybrid Model for Freezing of Gait Detection in Parkinson's Disease: Integrating Manual Features and Deep Learning Save
- Optimized LightGBM model for predictive defect detection in manufacturing within industry 4.0 Save