Dr. Sowmya V
Invited Speaker - GCSRAI 2026

Dr. Sowmya V

Associate Professor
School of Artificial Intelligence
Amrita Vishwa Vidyapeetham, Coimbatore

Artificial Intelligence • Healthcare Analytics • Deep Learning • Computer Vision

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Session Information

Research Area

Artificial Intelligence for Healthcare Data Analytics

Talk Title

AI-Driven Healthcare Innovations: Challenges, Ethics and Opportunities

Date

11 June 2026

Mode

Offline

Email

v_sowmya@cb.amrita.edu

Biography

Dr. Sowmya V is currently an Associate Professor at the School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Coimbatore. She previously served as Assistant Professor at the Center for Computational Engineering and Networking (CEN), Amrita Coimbatore.

She completed her M.Tech in Remote Sensing and Wireless Sensor Networks from Amrita School of Engineering, Coimbatore and earned her Ph.D. in Artificial Intelligence for Natural Scene Analysis from Amrita Vishwa Vidyapeetham.

Her doctoral research focused on Artificial Intelligence for Computer Vision, Healthcare Data Analysis and Remote Sensing Data Analysis, which aligns closely with her current research interests.

Research Interests

  • Artificial Intelligence for Healthcare Data Analytics
  • Machine Learning Algorithms
  • Deep Learning Algorithms
  • Computer Vision
  • Signal and Image Analysis
  • Remote Sensing Data Analytics

Awards & Recognition

  • Women in AI Leadership Award 2019 – RISING 2019, Bangalore
  • Co-Mentor for IEEE Industrial Electronics Society Hackathon
  • Contributor to AI-driven solutions for industrial and civil applications

Selected Publications

  • Unsupervised Deep Learning-Based Disease Diagnosis Using Medical Images (2022)
  • CT Image Enhancement Using Variational Mode Decomposition for AI-Enabled COVID Classification (2023)
  • Tuberculosis Classification Using Pre-trained Deep Learning Models (2021)
  • Multi-task Data Driven Modelling in Deep Learning for Biomedical Application (2021)

Research Highlights

Her work focuses heavily on applying Artificial Intelligence and Machine Learning techniques to healthcare diagnostics, medical imaging, COVID-19 detection, tuberculosis classification and disease diagnosis using deep learning.

She actively contributes to the development of intelligent healthcare systems that support accurate diagnosis and clinical decision-making.

10+

Years Academic Experience

4+

Major Publications

3+

Research Domains

AI

Healthcare Focus