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Dr. Anitha J.

Assistant Professor(Sl. Gd), Department of Computer Science and Engineering, School of Computing, Chennai

Qualification: Ph.D., M.Tech
j_anitha@ch.amrita.edu
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Research Interest: Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Medical Image Analysis

Bio Publications Qualifications Professional Awards Skills Courses Workshops
Bio

Dr. Anitha J, is an Assistant Professor (Sl. Gd) in the Department of Computer Science and Engineering, School of Computing, Amrita Vishwa Vidyapeetham, Chennai Campus. She has 19 years of experience, including 16 years of academic teaching and 3 years of full-time research in the field of Computer Science and Engineering. Her research interests include Artificial Intelligence, Machine Learning, Deep Learning, Medical Image Analysis, and Computer Vision. She has published high-impact research articles in peer-reviewed SCIE and Scopus-indexed international journals. She has successfully completed funded consultancy projects, including CCCL ERP Documentation, Weld-R, and V-art Gallery, contributing to project planning, reverse engineering, client coordination, web application development, and user interface design. She has also contributed to academic administration through NBA, NAAC, and ISO coordination, examination management, and the organization of academic events. She has actively participated in international conferences, faculty development programmes (FDPs), workshops, and training programmes.

Publications

Conference Proceedings

Year : 2025

Ensemble-Based Multi-Class Classification for Surge Pricing in Ride-Hailing Services

Cite this Research Publication : Anitha Jaikumar, Alona Santh Salil, Sreenivasa Chakravarthi Sangapu, Ensemble-Based Multi-Class Classification for Surge Pricing in Ride-Hailing Services, 2025 2nd Asia Pacific Conference on Innovation in Technology (APCIT), IEEE, 2025, https://doi.org/10.1109/apcit65661.2025.11411067

Publisher : IEEE

Journal Article

Year : 2025

Early-Stage Diabetic Retinopathy Diagnosis with Feature Pyramid Networks and Spatial Pyramid Pooling Utilizing Full-Field Optical Coherence Tomography (FF-OCT)

Cite this Research Publication : Anitha Jaikumar, Sreenivasa Chakravarthi Sangapu, Early-Stage Diabetic Retinopathy Diagnosis with Feature Pyramid Networks and Spatial Pyramid Pooling Utilizing Full-Field Optical Coherence Tomography (FF-OCT), Journal of Computational and Cognitive Engineering, BON VIEW PUBLISHING PTE, 2025, https://doi.org/10.47852/bonviewjcce52024763

Publisher : BON VIEW PUBLISHING PTE

Year : 2025

Unified intelligence in ophthalmology: a comprehensive review of a single framework for predicting multiple eye diseases

Cite this Research Publication : Anitha J, Sreenivasa Chakravarthi Sangapu, Unified intelligence in ophthalmology: a comprehensive review of a single framework for predicting multiple eye diseases, Cybernetics and Physics, Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences - IPME RAS, 2025, https://doi.org/10.35470/2226-4116-2025-14-2-127-136

Publisher : Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences - IPME RAS

Year : 2025

RetinoNet: an EfficientNet and feature pyramid network-based framework for accurate diabetic retinopathy classification

Cite this Research Publication : Anitha Jaikumar, Sreenivasa Chakravarthi Sangapu, RetinoNet: an EfficientNet and feature pyramid network-based framework for accurate diabetic retinopathy classification, PeerJ Computer Science, PeerJ, 2025, https://doi.org/10.7717/peerj-cs.3361

Publisher : PeerJ

Year : 2020

A Novel Intelligent Diagnosis and Disease Prediction Algorithm in Green Cloud Using Machine Learning Approach

Cite this Research Publication : Priya L. Sai, Sathya A., Poornimathi K., Anitha J. “A Novel Intelligent Diagnosis and Disease Prediction Algorithm in Green Cloud Using Machine Learning Approach,” Journal of Green Engineering, Volume 10, Issue 7, pp. 3421–3433, July 2020

Year : 2019

A Study on Machine Learning Algorithms in Medical Imaging

Cite this Research Publication : Poornimathi K., Anitha J., Sudarsaan A., Priya L. Sai. “A Study on Machine Learning Algorithms in Medical Imaging,” Journal of Advanced Research in Dynamical and Control Systems, Volume 11, Special Issue-05, pp. 2162–2170, 2019..

Qualifications
2023 – 2026 Ph.D.
Amrita Vishwa Vidyapeetham, ChennaiDissertation Title: Clinical Data-Driven Intelligent Framework for Prognosis and Stage-Wise Diagnosis of Diabetic Retinopathy.
2004 – 2006 M.Tech. (Information Technology)
Bharath Institute of Science and Technology, Chennai
2002 – 2004 M.Sc. (Information Technology)
Madras University, Chennai
1996 – 1999 B.Sc. (Computer Science)
Madras University, Chennai
Professional
July 2026 – Present Assistant Professor (Selection Grade)
Amrita School of Computing,
Amrita Vishwa Vidyapeetham, Chennai Campus
June 2023 – June 2026 Research Scholar (Full-Time)
Amrita School of Computing,
Amrita Vishwa Vidyapeetham, Chennai Campus
Sep 2008 – July 2022 Assistant Professor (Selection Grade)
Rajalakshmi Engineering College,
Chennai
August 2007 – June 2008 Assistant Professor
Hindustan College of Engineering,
Chennai
June 2006 – May 2007 Assistant Professor
St. Peter’s Engineering College,
Chennai
Awards
  • Received the Best Teacher Award for outstanding teaching in C# Programming in 2011.
  • Received the Best Paper Award for the paper “Efficacy Detection of Type-II Diabetes Mellitus with Support Vector Machine and Artificial Neural Network” at the International Conference on Advanced Theoretical Computer Applications (ICATCA 2016), Kuala Lumpur, Malaysia.
Skills
  • Programming Languages: Python, Java, C, C++
  • Artificial Intelligence & Machine Learning: TensorFlow, Keras, Scikit-learn
  • Computer Vision & Image Processing: OpenCV
  • Deep Learning Frameworks: TensorFlow, Keras
  • Development & Research Tools: Jupyter Notebook, Google Colab
Courses

Courses Handled: 

  • Artificial Intelligence, Machine Learning, Deep Learning & Computer Vision
  • Programming Languages: C, C++, Java & Python
  • Software Engineering & Object-Oriented Analysis and Design (OOAD)
  • Computer Architecture, Mobile Communication
Workshops

Faculty Development Programme (FDP)

  • Completed One-week ATAL FDP on “Artificial Intelligence for Next Generation Industrial Cyber-Physical Systems” during December 18–23, 2023.
  • Participated in the Two-day National Seminar on “The Impact of Artificial Intelligence on Cybersecurity and Sustainable Development” during September 13–14, 2023.
  • Participated in the One-week Workshop on “Introduction to Angular JS” during May 24–28, 2021.
  • Attended the Presentation on “A Novel Role-Based Privacy Preservation Technique for Cloud-Assisted Healthcare System” during May 10, 2021.
  • Attended the Session on “Deep Learning” during May 15, 2020.
  • Participated in the One-day Workshop on “Deep Learning and Its Applications Using TensorFlow and Keras” during August 5, 2020.
  • Attended the One-day Workshop on “Writing and Publishing High Impact Research Publications and Scientific Documents” during October 5, 2020.
  • Attended the Five-day Event on “Digital Transformation” during May 8–12, 2020.
  • Attended the Sessions on “Paradigm Shift in Education during Crisis” during May 5, 6, and 11, 2020.
  • Participated in the Four-week Program on “Innovation, IPR, Entrepreneurship, and Start-ups” during April 28–May 22, 2020.

Guest lecture Delivered: 

  • Delivered a Lecture on “Overview of Image Processing Techniques in Digital Image Processing” during a Workshop on July 26, 2021.
  • Served as a Resource Person for the Workshop on “Programming Logic Using Python” during June 13, 2020.
  • Delivered a Lecture on “Real-Time Applications of IoT” during a Workshop on June 14, 2019.

Certification Courses Completed:

  • Elite Certification in NPTEL Course – Programming Data Structures and Algorithms using Python.
  •  Course Certificate – Introduction to Machine Learning, Duke University, offered through Coursera, May 2021.
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