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Dr. Premkumar BORUGADDA

Post-Doctoral Research Fellow

Biography

ORCID: https://orcid.org/0000-0002-6506-6647 

Dr. Premkumar Borugadda is a Post-Doctoral Research Fellow in the Department of Environment and Climate at the ERATOSTHENES Centre of Excellence. He obtained his Ph.D. in Computer Science and Engineering (Artificial Intelligence & Machine Learning) from Pondicherry University, India, where his doctoral research focused on “A Novel Approach for Multi-Level Dimensional Reduction for Classification of Tomato Plant Leaf Diseases using Transfer Learning on the VGG16 Model.” Prior to joining ERATOSTHENES CoE, Dr. Borugadda served as a Post-Doctoral Fellow at SRM University-AP, India, and as an Assistant Professor at leading academic institutions including Ashoka School of Business, Hyderabad, and Bapatla Engineering College, Andhra Pradesh, India. His research interests encompass Machine Learning, Deep Learning, and Computer Vision, with particular emphasis on their applications in agriculture, food science, and environmental monitoring. He has published numerous papers in Q1 and Q2 international journals such as Journal of Future Foods (Elsevier) and Discover Sustainability (Springer) and presented his research at several IEEE and Springer international conferences. In addition to his academic work, Dr. Borugadda is a passionate educator and YouTuber, running the YouTube channel “Machine Learning Lectures for Beginners” (YouTube Link), where he provides accessible tutorials and lectures on machine learning and artificial intelligence concepts for students and researchers worldwide. He is also an author and book editor in the field of Artificial Intelligence, having contributed to and co-edited volumes on AI and Data Analytics for Sustainable Development. Moreover, he actively serves as a reviewer for IEEE and Scopus-indexed international conferences. 

This project has received funding from the Government of the Republic of Cyprus through the “Directorate General for European Programmes, Coordination and and Development”.
This project has received funding from the European Union’s “Horizon 2020 Research and Innovation Programme” under Grant Agreement No 857510”.
This project is co-funded by the Cyprus University of Technology.
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