Dr. Shreyas Rajendra Hole
Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune, India, VIT-AP Campus, PRMIT&R,Badnera
0000-0002-1432-2196
About
Dr. Shreyas Rajendra Hole is a distinguished researcher with a Ph.D. from the School of Electronics Engineering (SENSE) at VIT-AP University, Andhra Pradesh. He holds a B.E. in Electronics and Telecommunication Engineering from Sant Gadge Baba Maharaj Amravati University (2015) and an M.E. in Electronics & Communication Engineering from PRMIT&R, Badnera (2019). Dr. Hole's research expertise spans Renewable Energy, Machine Learning, and DC-DC Converters. His academic contributions include 03 SCI-indexed papers, 03 SCOPUS-indexed papers, and 07 conference presentations. During his Ph.D., he published 07 patents and received prestigious accolades, including the Chatrapati Shahu Maharaj National Research Fellowship (CSMNRF-2021), the VIT-AP University Research Awards for Patents in 2022 and 2024, and the 2nd Prize in the Patent Category at V-INN EXPO'24. He also earned the Best Poster Presentation Award at V-Samshodh 2023 and the Junior Research Fellowship from VIT-AP University in 2021. Dr. Hole's prolific contributions to his field underscore his dedication and innovative approach to advancing technology and research.
Employment
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Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune, India Assistant Professor2025 - Present
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VIT-AP Campus Assistant Professor Jr.2021 - Present
Education
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VIT-AP Campus PHD2020 - Present
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PRMIT&R,Badnera Master Of Engineering2015 - 2019
Projects & Funding
Projects & funding information is unavailable.
Publications (23)
- Evolutionary algorithm for optimizing DG in radial distribution systems Save
- AI enabled geospatial intelligence for the energy transition: A comparative CNN study on CCUS, geothermal siting, and NetZero strategies Save
- AI—Prediction of Neisseria gonorrhoeae Resistance at the Point of Care from Genomic and Epidemiologic Data Save
- Optimizing Solar Radiation Forecasting for Renewable Energy Systems: Save
- Efficient Quantum-Enhanced Ensemble Fault Detection for Solar Energy Integration using an Iterative Game-Theoretic Approach with Adaptive Neuro-Fuzzy Inference and Energy Storage Save
- A Design of Hybrid Model and Bayesian Neural Networks for Smart Grid Stability Prediction Save
- Hybrid Approach of TabNet and Transformer-XGBoost for Predicting Traffic Flow in Smart Cities Save
- Hybrid PCA-Based Machine Learning Models for Predictive Analytics in Urban Health Monitoring Systems Save
- Empirical analysis of control models for different converter topologies from a statistical perspective Save
- Design of a novel hybrid soft computing model for passive components selection in multiple load Zeta converter topologies of solar PV energy system Save