0000-0003-0549-6757 About
Jayavardhanarao Sahukaru is currently working with the Aditya Institute of Technology and Management, Tekkali, Andhra Pradesh and has an excellent academic background. He has 16 years of teaching experience. He holds a postgraduate degree in Computer Applications from JNTU Hyderabad and a Master of Technology from JNTU Kakinada and is now pursuing a Ph.D. in Computer Science and Engineering from the Centurion University, Bhubaneswar, Odisha in Machine Learning and Deep Learning domains. His areas of research interest include Artificial Intelligence, Image Processing, Data Mining, Machine Learning, and Deep Learning. He has published papers in national, international, UGC, SCOPUS and SCI/SCIE journals. He is associated with many professional bodies like ISTE, IAENG, AMIEE and IEI. He has many NPTEL certifications in various subjects. He has attended many national and international conferences, seminars, workshops, and FDPs. He has authored many books. He has also been involved as a paper setter, checking and moderating several papers in various autonomous colleges and Private and government Universities.
Employment
Employment history is unavailable.
Education
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Publications (15)
- A Detailed Study: Application of Big Data Analytics in Health Care Sector and Treatment of Cancer Disease Save
- Integration of Classical and Quantum Cryptography in IoT Save
- Cyberbullying Detection on Twitter Social Media Platform Using Deep Learning Algorithms Save
- A Comparative Study of Cardiac Disease Classification Methods, Systematic Literature Reviews, Open Challenges and Future Directions Save
- A Typical Neural Network-Based Automated System for Number Plate Recognition and Detection Save
- AI-Driven Quarrel Detection in Surveillance Footage Save
- Adaptive Liver Cancer Prediction Using Liquid Neural Networks and Multi-Modal Clinical Data Save
- Basic Structure for Sentiment and Emotion Analysis-Based Hate Speech Recognition and Integrating of Unstructured Data on Facebook, or Fadohs Save
- Challenges of Learner Engagement in E-Learning Environments Save
- Development of Hybrid Deep Learning Network for Precise Segmentation of Cardiac Disease with Adaptive Nested Dilated Residual Densenet-Based Classification Save