Dr. J T M Dhas

About

I am Dr. John T. Mesia Dhas, M.E. (CSE), Ph.D. (CSE), and PDF (CSE) professional with 16 years of teaching experience. My key skills are teaching all kinds of modern CSE subjects like Artificial Intelligence (AI), Machine Learning, the Internet of Things (IoT), Data Science, and Cyber Security; placement training; GATE training; admission-based marketing and administration activities; Anna University; AICTE and NAAC affiliation works; and MSME funded projects and their documentation works. I have published eleven books and 26 research articles in SCOPUS, WOS, and UGC-listed journals and presented at IEEE and Elsevier conferences. One of our MODROB proposals was accepted by AICTE and sanctioned for 20L. I was the convenor for IOS Press, Scopus Indexed, the International Conference on Advances in Parallel Computing Techniques and Applications (ICAPTA 2022), the International Workshop on International and National Patent Drafting and Filing (INPDF2022), and the AICTE-approved FDP on AWS. I have received an international patent and two national patents. I have guided 24 PG and UG-level projects. I am the coordinator for the Research & Development Cell of T. John Institute of Technology, Bangalore, India.

Employment

• T John Institute of Technology Associate Professor
  2021 - Present
• RVS Padmavathi College of Engineering and Technology Assistant Professor
  2011 - Present

Education

• Lincoln University College PDF
  2021 - 2023
• Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Ph.D.
  2013 - 2019
• Sathyabama University M.E.
  2009 - 2011
• Indira Gandhi National Open University M.B.A.
  2006 - 2009
• Bishop Heber College M.Sc
  2001 - 2003
• Nesamony Memorial Christian College B.Sc.
  1998 - 2001

Projects & Funding

Projects & funding information is unavailable.

Publications (39)

• Energy and Safety Optimization in Smart Cities Through Edge-AI-Driven Adaptive Street Lighting With Ambient Sensing and Traffic Pattern Prediction
  2026 DOI: 10.4018/979-8-3373-4962-6.ch004
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• A comprehensive impression on identifying plant diseases using machine learning and deep learning methodologies
  IAES International Journal of Artificial Intelligence (IJ-AI) 2025 DOI: 10.11591/ijai.v14.i6.pp4694-4702
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• Rose Doctor: Identification of Fungal Diseases in Rose Plants Using Convolutional Neural Networks
  2025 DOI: 10.1007/978-981-97-9926-8_19
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• Modern Metrics (MM): Functional Size Estimator for AI and BDA Software Applications
  2025 DOI: 10.1007/978-981-97-9926-8_25
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• A reliable and secure demand side control for an IoT-enabled smart power system using machine learning
  Indonesian Journal of Electrical Engineering and Computer Science 2025 DOI: 10.11591/ijeecs.v37.i3
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• A reliable and secure demand side control for an IoT-enabled smart power system using machine learning
  Indonesian Journal of Electrical Engineering and Computer Science 2025 DOI: 10.11591/ijeecs.v37.i3.pp1428-1434
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• Enhancing Cybersecurity Insurance Through AI and Blockchain for Proactive Risk Management
  2025 DOI: 10.4018/979-8-3373-1977-3.ch012
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• Integrating AI and Blockchain for Cybersecurity Insurance in Risk Management for Predictive Analytics in Insurance
  2025 DOI: 10.4018/979-8-3373-1882-0.ch013
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• A Proportional Analysis Study on Function Point Based Software Size Estimation Technique for Artificial Intelligence and Data Analytics Software Applications
  International Journal of Advances in Engineering Architecture Science and Technology 2023
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• Logistic Regression Model of Study of Identifying Population for Covid-19 Medical Test – Machine Learning Approach
  International Journal of Advances in Engineering Architecture Science and Technology 2023
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