Vidwan-ID : 111337



  • Dr Balajee Jeyakumar

  • Associate Professor
  • Mother Theresa Institute of Engineering and Technology
Publications 2013 - 2024

Publications

  • 48
    Journal Articles
  • 3
    Book Chapter
  • 1
    Book
  • 6
    Conference
    Proceedings
  • 2
    Review
  • 1
    Book-chapter
  • 1
    Retracted
  • 1
    Projects
  • 6
  • 1
  • 17

Citations / H-Index

356 Citations
10 h-index
154 Citations

Google Scholar

Co-author Network


Expertise

Computer Science Artificial Intelligence

BlockChain, Deep Learning, IoT, Machine Learning, Quantum Computing.

Personal Information

Dr Balajee Jeyakumar

Male
Computer science and Engineering Department of Artificial Intelligence and Data Science, Mother Theresa Institute of Engineering and Technology
Chittoor, Andhra Pradesh, India - 517408


Experience

  • Associate Professor

    Department of Computer Science and Engineering

    Mother Theresa Institute of Engineering and Technology

  • Assistant Professor

    Computer Applications

    Sakthi Mariamman Engineering College

  • Assistant Professor

    Computer Science

    Shanmugha Industries Arts and Science College


Qualification

  • Ph.D

    Vellore Institute of Technology

  • M.Phil

    Thiruvalluvar Univeristy

  • MBA

    University of Madras

  • MCA

    Vellore Institute of Technology


Membership In Professional Bodies

2023

Computer Society of India

Life Time Member - 7162230004

2023

IAENG

Life Time Member - 346174

2023

Computer Society of India

Life Time Member - 7162230004

2023

IAENG

Life Time Member - 346174

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Membership In Committees

2024

SIH Hackathon 2024

Coordinator (Institute)

2023

Research and Development

Member (Institute)

2024

SIH Hackathon 2024

Coordinator (Institute)

2023

Research and Development

Member (Institute)

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Research Projects

Early detection of Alzheimer's disease analyzing retinal vein diameter and choroid thickness using smartphone camera-captured fundus images and hybrid neural network

Funding Agency : DST-SERB

Early detection of Alzheimer's disease analyzing retinal vein diameter and choroid thickness using smartphone camera-captured fundus images and hybrid neural network

Funding Agency : DST-SERB

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Patents




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