Dr. Premkumar Borugadda

Dr. Premkumar Borugadda

Editorial Board Member

Name: Dr. Premkumar Borugadda
Ph.D. in Computer Science & Engineering (Artificial Intelligence & Machine Learning)

Designation: Post-Doctoral Research Fellow

Affiliation:
ERATOSTHENES Centre of Excellence,
82 Franklin Roosevelt, 3012,
Lemesos, Cyprus

Email: ✉️ [email protected]

Academic Profiles:

Professional Summary

Postdoctoral researcher with strong expertise in machine learning, deep learning, and computer vision, with applications in agriculture, environmental systems, remote sensing, and intelligent data-driven technologies. He has a proven record of peer-reviewed publications in Q1/Q2, Scopus, and Web of Science indexed journals and conferences, along with interdisciplinary research contributions, patents, book chapters, and academic leadership activities.

Current Position

  • Postdoctoral Research Fellow
    ERATOSTHENES Centre of Excellence, Limassol, Cyprus
    October 2025 – Present
  • Postdoctoral Fellow
    Department of Computer Science & Engineering
    SRM University–AP, India
    April 2024 – May 2025

Research Areas

  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Artificial Intelligence
  • Remote Sensing
  • Agricultural Intelligence
  • Environmental Monitoring
  • Climate Change Detection
  • Data Science
  • Image Classification

Research Output Summary

Category Details
Research Domain Machine Learning, Deep Learning, Computer Vision, Remote Sensing, Agricultural AI, Environmental Systems and Data Science
Google Scholar 273 citations, h-index 9
Scopus 129 citations, h-index 7
Indexed Publications Publications in Scopus, Web of Science, ESCI, SCI, Q1 and Q2 indexed journals and conferences
Patents & Books Patent published, book chapters, book publication and editorial contribution to AI book series

Technical Skills

  • Machine Learning Algorithms: Linear Regression, Logistic Regression, SVM and Decision Tree.
  • Deep Learning Models: CNN models including LeNet, AlexNet, VGG16, VGG19 and ResNet50.
  • Modelling Tools: Scikit-Learn, Keras and TensorFlow.
  • Visualization: Matplotlib and Seaborn.
  • Data Processing: NumPy and Pandas.

Subjects Taught

  • Machine Learning
  • Artificial Intelligence & Deep Learning
  • Fundamentals of Data Science
  • Introduction to R Programming
  • Introduction to Python and Python for Data Science
  • Discrete Mathematical Structures
  • Computer Graphics
  • Operating Systems

Eligibility Tests Qualified

  • UGC NET Qualified for Assistant Professor / Lectureship, November 2017.
  • AP SET Qualified for Assistant Professor / Lectureship, July 2012.
  • TN SET Qualified for Assistant Professor / Lectureship, October 2012.

Selected Publications

  • Comparative Machine Learning and Deep Learning Models for Long-Term NDVI Prediction Under Climate Variability in Cyprus.
  • Multi-Source Remote Sensing and Explainable Machine Learning Framework for Soil Organic Carbon Prediction and Uncertainty Mapping Across Cyprus.
  • A Comprehensive Analysis of Artificial Intelligence, Machine Learning, Deep Learning and Computer Vision in Food Science.
  • Transfer Learning VGG16 Model for Classification of Tomato Plant Leaf Diseases: A Novel Approach for Multi-Level Dimensional Reduction.
  • An IoT Assisted Alzheimer’s Disease Patient Monitoring System using Adaptive Deep Learning Models with Recommendation about Patient Abnormality.
  • Classification of Cotton Leaf Diseases Using AlexNet and Machine Learning Models.
  • Performance Analysis and Evaluation of Machine Learning Algorithms in Rainfall Prediction.
  • Predicting the Success of Bank Telemarketing for Selling Long-Term Deposits: An Application of Machine Learning Algorithms.

Conference Publications

  • Large Language Model Driven Named Entity Recognition for Soil and Land Information Extraction in the EMMENA Region.
  • Automated Papaya Fruit Classification Using CNN Models.
  • Enhancing Churn Prediction in Telecommunications via Machine Learning and Oversampling Techniques.
  • Developing a Logistic Regression Model for Predicting Chronic Kidney Disease.
  • Obesity Health Risk Prediction Using Random Forest and SVM Algorithms.
  • Prediction of Heart Disease Based on Machine Learning Algorithms.
  • Offline Handwritten Character Classification of the Same Scriptural Family Languages Using Transfer Learning Techniques.
  • Performance Evaluation of Deep Learning Algorithms in Biomedical Document Classification.

Patents, Books & Editorial Contributions

  • Patent published: A System and A Method for Detecting External Flaws in Tomatoes Using Ensemble Machine-Learning Techniques.
  • Book: Advanced Machine Learning Applications Using Python Programming.
  • Editor for the book series “Futuristic Trends in Artificial Intelligence”, Volume 3, Book 8.
  • Book chapter on Remote Sensing and Artificial Intelligence for Climate Change Detection.
  • Book chapter on Smart Farming using IoT, Artificial Intelligence, Machine Learning and Deep Learning.

Reviewer & Academic Contributions

  • Reviewer for international conferences in artificial intelligence, quantum computation, smart computing, information security, cyber-physical systems, green energy and intelligent systems.
  • Reviewer for IEEE International Conference on Computing, Communication, and Intelligent Systems.
  • Reviewer for International Conference on Smart Cyber-Physical Systems.
  • Reviewer for International Conference on Sustainable Smart Computing and Green Energy.
  • Invited resource person for seminars, faculty development programmes, webinars and academic sessions on AI, machine learning, NLP, computer vision and data science.

Invited Talks & Resource Person Activities

  • Resource Person for National Seminar on Modern Machine Learning Techniques and AI Tools.
  • Resource Person for FDP on Exploring the Power of AI: Machine Learning, NLP and Computer Vision.
  • Delivered session on Innovative Food Processing: Integrating Machine Learning and Deep Learning Technologies.
  • Delivered National Webinar on Introduction to Data Science.
  • Delivered session on Real Time Machine Learning Applications using Python.
  • Delivered sessions on Applications of Artificial Intelligence and Data Science.
  • Delivered sessions on Recent Trends in Artificial Intelligence and Data Science.

Achievements

  • Secured All India 58th Rank in Ph.D. CSE Entrance of Pondicherry University in 2017.
  • Secured State 26th Rank in Ph.D. CS Entrance of Acharya Nagarjuna University in 2016.
  • Secured All India 34th Rank in Ph.D. Entrance in Banking Technology of Pondicherry University in 2014.

Last Updated: 28 June 2026