Abhishek S. Rao
Canara Engineering College, NMAM Institute of Technology, Visvesvaraya Technological University, Maharastra Institute of Technology
0000-0002-3574-3571
About
Dr. Abhishek S. Rao is an Associate Professor in the Department of Information Science and Engineering at Canara Engineering College, Karnataka, India, and serves as the Chief R&D Coordinator of the institution. He holds a B.E. in Information Science and Engineering from Canara Engineering College, an M.Tech. from NMAM Institute of Technology, an MBA from MIT Pune, and a Ph.D. from Visvesvaraya Technological University (VTU). His research interests include Artificial Intelligence, Machine Learning, Data Science, Bioinformatics, Computational Healthcare, Predictive Modelling, and AI-enabled applications in healthcare and agriculture. His research work focuses on developing data-driven and intelligent models for solving real-world problems. He has authored around 40 research publications and holds multiple patents. He is a member of IEEE, ISTE, and IAENG. He is also actively involved in research coordination, faculty research initiatives, external funding, interdisciplinary collaborations, and technology-driven academic and research activities.
Employment
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Canara Engineering College Associate Professor2025 - Present
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NMAM Institute of Technology Assistant Professor Gd III2017 - 2025
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Canara Engineering College Assistant Professor2012 - 2017
Education
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Visvesvaraya Technological University PhD2021 - 2025
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Maharastra Institute of Technology MBA2012 - 2014
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NMAM Institute of Technology M.Tech2010 - 2012
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Canara Engineering College B.E2004 - 2008
Projects & Funding
Projects & funding information is unavailable.
Publications (46)
- A Multimodal Emotion-Aware Chatbot for Mental Well-Being Using Text and Facial Expression Analysis Save
- Enhancing Heart Disease Risk Prediction Through Robust Statistical Validation and Interpretability Save
- Statistical and Time-Dependent Survival Analysis of Mortality in Acute Febrile Illness with Thrombocytopenia Save
- Wavelet-Based Deep Neural Network with Attention for Interpretable Epileptic Seizure Prediction Using EEG Spectrograms Save
- Hybrid Deep Learning Approach for Accurate and Interpretable Chest X-ray Image Classification Save
- Comprehensive review and early detection strategies for severe fever with thrombocytopenia: insights from epidemiology, diagnostics, and evolving research with machine learning Save
- Identification of prognostic factors contributing towards mortality in leptospirosis patients: a statistical and score-based model approach Save
- Wearable Assistive Device for Enhanced Navigation in Visually Impaired Individuals Using YOLO-Based Object Detection Save
- Automated Energy Management for Sustainable and Cost-Efficient Households: A Forecasting and Optimization Approach Save
- Real-Time Automated Pothole Detection and Localization with Deep Learning and Geolocation Integration for Improved Road Safety and Maintenance Save