Dr. Shwetha C H

Dr. Shwetha C H

Position: Assistant Professor

Education Qualification

BE- Computer Science and Engineering

MTech – Computer Science and Engineering

PhD – NLP and Deep Learning

Total Experience

11.6 yrs

Area of Interest

  • Deep Learning
  • Image Processing
  • Natural Language Processing
  • Database Management System

Subject handled

  • Design and Analysis of Algorithms
  • Database Management System
  • Web Technology and its Applications
  • Object Oriented Concepts
  • Big Data Analytics
  • Storage Area Network
  • Cloud Computing
  • Data Structure
  • OOP with Java
  • Artificial Intelligence and Machine learning
  • Computer Graphics and Visualization and React

Workshops FDPs/SDPs Attended/Conducted: 08

Conferences / Journal Publications

  1. A Hybrid Deep Learning Framework for Multilingual Depression Detection and Symptom Classification from Social Media Text, International Journal of Information Technology, Page No: 1-24, 2026. https://doi.org/10.1007/s41870-025-03055-1
  2. Exploring Sentiment Analysis: Applications and Challenges —A Comprehensive Survey” International Journal of Scientific Research in Engineering and Management, Vol.7, Issue7, 2023
  3. Different Approach to Software Testing Techniques International Journal for Scientific Research & Development| Vol. 8, Issue 9, 2020
  4. Efficient Query Processing and Data Integrity in Cloud using Column Oriented Database- International Journal of Engineering Research & Technology, Vol. 3 Issue 4, 2014
  5. Creation and annotation of a code-mixed Kannada English dataset with accurate labels for detecting depression and major depressive disorder categories in Engineering Research Express, 2025
  6. Exploring Sentiment Analysis: Applications, and Challenges —A Comprehensive Survey, 2023
  7. Corpus Creation and Annotating Multilingual Code-Mixed Kannada English Data with Precise Labels for Depression Detection, 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
  8. Depression Detection from a Social Media Dataset Using Deep Learning and NLP Techniques: A Review, 2024 ICT for Intelligent Systems”