Dr. Raveendra Gudodagi

About

Dr. Raveendra Gudodagi is an esteemed Associate Dean Corporate and Public Relations and Associate Professor in the department of Electronics and Communication Engineering at HKBK College of Engineering, Bengaluru. He holds a PhD from REVA University, complemented by an M.Tech and a Bachelor's degree in Engineering from Visvesvaraya Technological University (VTU), Belagavi. His academic journey is marked by a Post Doctoral Fellowship at City University of London, where he further honed his expertise. With over fifteen years of experience in academia, Dr. Gudodagi specializes in deep learning, computer vision, and genomics. His research contributions have significantly advanced the fields of machine learning and genomic data processing, focusing on innovative algorithms for data compression and secure genomic sequence analysis. He has published numerous papers in reputable journals, showcasing his commitment to advancing technology through research.

Employment

• HKBK College of Engineering Associate Professor and Associate Dean
  2025 - Present
• REVA University Associate Professor
  2010 - 2025

Education

• REVA University Doctor of Philosophy (PhD)
  2014 - 2022
• RITM Bengaluru (VTU) Master of Technology (MTech)
  2011 - 2013
• RITM Bengaluru (VTU) Bachelor of Engineering (BE)
  2006 - 2009

Projects & Funding

Projects & funding information is unavailable.

Publications (22)

• Quantum-Resistant Cryptography for Military Communications
  2025 IEEE Space, Aerospace and Defence Conference (SPACE) 2025 DOI: 10.1109/space65882.2025.11170996
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• Predicting Thyroid Dysfunction Using Machine Learning Techniques
  2023 12th International Conference on Advanced Computing (ICoAC) 2023 DOI: 10.1109/icoac59537.2023.10249516
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• Contention Based MAC Collision Avoidance Technique for Mobile Adhoc Networks
  2023 3rd International Conference on Intelligent Technologies (CONIT) 2023 DOI: 10.1109/conit59222.2023.10205739
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• A Novel Algorithm for Reconfigurable Architecture for Software-Defined Radio Receiver on Baseband Processor for Demodulation
  Sustainable Computing: Transforming Industry 4.0 to Society 5.0 2023 DOI: 10.1007/978-3-031-13577-4_11
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• A Review of AI-Based Diagnosis of Multiple Thoracic Diseases in Chest Radiography
  Sustainable Computing: Transforming Industry 4.0 to Society 5.0 2023 DOI: 10.1007/978-3-031-13577-4_14
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• Deep Learning Algorithms for Secure and Efficient Compression of Genomic Sequence Data
  3rd IEEE International Conference on Technology, Engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023 2023 DOI: 10.1109/TEMSMET56707.2023.10150044
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• Exploiting the Joint Potential of Instance Segmentation and Semantic Segmentation in Autonomous Driving
  2023 International Conference for Advancement in Technology, ICONAT 2023 2023 DOI: 10.1109/ICONAT57137.2023.10080167
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• Fuzzy-Based Hierarchical Routing Protocol for Wireless Sensor Networks
  Sustainable Computing: Transforming Industry 4.0 to Society 5.0 2023 DOI: 10.1007/978-3-031-13577-4_13
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• Improvement of Flat Plate Collector Performance Using Nano-additives
  Sustainable Computing: Transforming Industry 4.0 to Society 5.0 2023 DOI: 10.1007/978-3-031-13577-4_19
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• Metaverse-A Forthcoming Lifestyle
  3rd IEEE International Conference on Technology, Engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023 2023 DOI: 10.1109/TEMSMET56707.2023.10150038
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