VISHNU VARDHANA RAO M
Vignan's institute of management and technology for women, Acharya Nagarjuna University
0000-0002-8157-8650
About
Dr M VISHNU VARDHANA RAO working as Associate Professor & Head of the Department, Department of CSE (AI & ML) at VIGNAN'S INSTITUTE OF MANAGEMENT AND TECHNOLOGY FOR WOMEN, kondapur (V), Hyderabad, Medchal Dist-501301. He obtained Ph.D. Degree from the Department of Computer Science and Engineering, at the Acharya Nagarjuna University, Guntur and AP, INDIA in 2022. He obtained M. Tech Degree in Computer Science and Engineering, at the University College of Sciences, Acharya Nagarjuna University, Guntur, and AP, INDIA. He qualified "UGC-NET (2018) and AP-SET (2017)" in Computer Science and Applications for both Assistant Professor and Lectureship. His Ph.D. research focuses on Optimized Hybrid Machine Learning Techniques, Data Mining methods for Predicting, Assessing and Estimating for applications in Building Damage Prediction. He has 13 years of teaching experience, has authored and published international journal publications including SCI, SCOPUS, UGC Journals, international conferences like IEEE, Springer, etc.
Employment
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Vignan's institute of management and technology for women2012 - Present
Education
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Acharya Nagarjuna University PhD2014 - 2022
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Acharya Nagarjuna University M.Tech2009 - 2011
Projects & Funding
Projects & funding information is unavailable.
Publications (17)
- Pharma - AI: Decoding Drug with AI Save
- AI-based Identification of Financial Services Save
- Development and Implementation of Face Recognition Technology for Criminal Identification and Public Safety Save
- AI-based Suspicious Behaviour Detection and Alert System using Surveillance Video Save
- An Efficient Hybrid Machine Learning Methodology for Predicting Medicine Overdose Save
- GIS-Integrated Convolutional Neural Network Framework for Real-Time Border Threat Detection Save
- Detecting Dysgraphia in Children Through Handwriting Image Analysis Using Hybrid Machine Learning Methodology Save
- Evaluation of Machine Learning and Genetic Algorithms for Water Quality Prediction Save
- A Novel Feature-Based SHM Assessment and Predication Approach for Robust Evaluation of Damage Data Diagnosis Systems Save
- A Machine Learning-based Damage Prediction Techniques for Structural Health Monitoring Save