Dr Raghavendra M Ichangi
Central University of Karnataka, Sphoorthy Engineering College, Visvesvaraya Technological University, National Institute of Technology Karnataka, Guru Nanak Institutions
About
Presently working as an Assistant Professor in Computer Science and Engineering at Central University of Karnataka Kalaburagi, has more than 18 years of Teaching Experience at Undergraduate and Postgraduate levels. Dr Raghavendra is M.Tech graduate from National Institute of Technology Karnataka (NITK) Surathkal from the department of Computer Science and Engineering during the year 2013. He has handled many subjects like Theory of Computations, Operating Systems, Operations Research, Optimization Techniques, Artificial intelligence and Machine Learning. He has cleared many competitive exams like Graduate Aptitude Test in Engineering (GATE), National Eligibility Test (NET) and Karnataka State Eligibility Test(K-SET). He was awarded Ph.D in the area of Social Media Analytics from Visvesvaraya Technological University Belagavi Karnataka, India.
Employment
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Central University of Karnataka Assistant Professor2026 - Present
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Sphoorthy Engineering College Assistant Professor2024 - 2026
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Guru Nanak Institutions Assistant Professor2023 - 2024
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Karnataka State Rural Development and Panchayat Raj University Programme Co-ordinator (Head)2019 - 2023
Education
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Visvesvaraya Technological University Doctor of Philosophy2021 - 2026
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National Institute of Technology Karnataka M.Tech2011 - 2013
Projects & Funding
Projects & funding information is unavailable.
Publications (17)
- Deep Learning and IoT Enabled Real-Time Water Quality Surveillance and Decision Support Systems Save
- Deep Transfer Learning with Dual Attention for Reliable Diabetic Retinopathy Screening Save
- Automated Brain Tumour Classification and Segmentation using Deep Neural Networks Save
- A Lightweight CNN Framework for Automated Diabetic Retinopathy Detection and Severity Grading Using Fundus Images Save
- A Discretized Recurrent Deep Learning Classifier based on Stochastic Gradient ChatGPT to Improve Lead Conversion Rate Save
- Revolutionizing Brain Tumor Classification with Fusion-Driven Deep Learning Models Save
- Deep Transfer Learning with Dual Attention for Reliable Diabetic Retinopathy Screening Save
- Deep Learning Applications for Improving Early Detection and Staging Accuracy in Alzheimer’s Disease Save
- A Discretized Recurrent Deep Learning Classifier based on Stochastic Gradient ChatGPT to Improve Lead Conversion Rate Save
- QEMF for spatial domain pre-processing in iris biometrics: advancing accuracy and efficiency in recognition systems Save