Thippa Reddy Gadekallu
Also known as G Thippa Reddy, G. Thippa Reddy, Gadekallu Reddy, Gadekallu Thippa Reddy
Thippa Reddy Gadekallu is a researcher whose AI work connects machine learning with blockchain security, crop-disease classification and connected health. He earned computer science and engineering degrees at Nagarjuna University in 2003 and Anna University in 2011, then completed a Ph.D. at Vellore Institute of Technology in 2017. His research includes blockchain protection for IoT health data, a survey of blockchain in the metaverse, CNN-SVM classification of paddy disease and a remote patient-monitoring framework. Elsevier included him among the world's top 2% of scientists in 2021, and Clarivate named him a Highly Cited Researcher in its Young Scientist category in 2023; he joined Scientific Reports' editorial board in 2022 and was an Associate Professor at VIT's School of Information Technology and Engineering by 2024. In September 2026, he delivered an IHCONCS keynote on blockchain's impact on key-enabling technologies for the metaverse; as of October 2026, he is a Professor at Zhejiang A&F University and Chief Engineer at Zhongda Group in China.
- Now at
- Vellore Institute of Technology University, Zhejiang A & F University and Zhongda Group
- Works
- 550
- Citations
- 29,851
- h-index
- 87
Publication numbers from OpenAlex, as of 22 October 2026.
Timeline
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2003–2017
Computer science degrees
He earns a bachelor's degree in computer science and engineering at Nagarjuna University in 2003 and a master's degree in the field at Anna University in 2011. He completes a Ph.D. at Vellore Institute of Technology in 2017.
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2020
Blockchain for e-health data
In 2020, he coauthors a blockchain-based system to secure machine-learning datasets generated by IoT devices for e-health applications.
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2021
An Elsevier top 2% listing
Elsevier includes him among the world's top 2% of scientists in 2021.
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2022
Blockchain for the metaverse
In 2022, he coauthors a survey of blockchain applications for metaverse data, storage, sharing, interoperability and privacy. He joins Scientific Reports' editorial board in 2022.
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2023
Clarivate Young Scientist recognition
Clarivate recognizes him as a Highly Cited Researcher in its Young Scientist category in 2023 for the 2017–2022 period.
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2023
A paddy leaf disease classifier
In 2023, he coauthors a model that combines a convolutional neural network and an SVM to classify paddy infections by type and severity.
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2025
A remote patient-monitoring framework
In 2025, he coauthors DeW-IoMT, a remote patient-monitoring framework with a roof computing layer between dew and fog that improves data security and reduces communication latency.
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As of October 2026
Professor and chief engineer
By 2024, he is an Associate Professor in the School of Information Technology and Engineering at Vellore Institute of Technology. In September 2026, he delivers an IHCONCS keynote on blockchain’s impact on key-enabling technologies for the metaverse. As of October 2026, he is a Professor at Zhejiang A&F University and Chief Engineer at Zhongda Group in China.
Career
- Since 2024Zhejiang A & F UniversityProfessor
- Since 2016Vellore Institute of Technology UniversityAssociate Professor
- NowZhongda GroupChief Engineer
- 2024–2026Chitkara University
- 2023–2025Jiaxing University
- 2023–2026Lovely Professional University
- 2022–2025Lebanese American University
Education
- 2017Vellore Institute of Technology UniversityPhD
- 2011Anna UniversityMaster's degree in computer science and engineering
- 2003Acharya Nagarjuna UniversityBachelor's degree in computer science and engineering
Sources and credits
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- 2026 6th International Conference on Electronic Information Engineering and Computer Communication (EIECC 2026)
- CIISC 2027 | International Conference on Computational Intelligence, Intelligent Systems And Cybernetics in 2027 COMMITTEE
- [2011.01457] Blockchain based Attack Detection on Machine Learning Algorithms for IoT based E-Health Applications
- [2203.09738] Blockchain for the Metaverse: A Review
- About the Guest Editors | Federated learning
- Frontiers | A novel fine-tuned deep-learning-based multi-class classifier for severity of paddy leaf diseases
- A secured remote patient monitoring framework for IoMT ecosystems | Scientific Reports
- Artificial intelligence enhanced edge server placement for workload balancing and energy efficiency in B5G networks
- IHCONCS - International Conference on Computer Sciences

