Faculty

MS Veena S Badiger

Assistant Professor
Department of Computer Applications

MS Veena S Badiger has 20 years of work experience in academics. Currently working as an Assistant Professor at Presidency College, Bengaluru, India. She is Self Directed, Enthusiastic educator with a passionate commitment to student development and the learning process. She is Skilled in the design of challenging, enriching and innovative activities that address the diverse interest and needs of students with a touch of moral values. Enabling Organization objectives & growth.

She has Completed B.E in CSE and MTech in CSE. She is currently pursuing PhD in Presidency University. Her current area of research interest are Machine learning, Deep learning, Cyber security, Game Theory and optimization.

  • Veena S Badiger(2024). Sentiment Analysis for Products Review based on NLP using Lexicon-Based Approach and Roberta. International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), IEEEXplore, ISBN:979-8-3503-0642-2.
  • Veena S Badiger(2024). Ensemble technique to detect intrusion in network based on UNSWB-NB15 dataset. International Conference on Communication and Computational Technologies (ICCCT 2024), Springer. Book chapter in Lecture notes in Networks and Systems(Accepted for Publication)
  • Veena S Badiger (2023). Brain tumour segmentation and classification using the Convolutional neural network (U- net model), International Conference on Advanced Computing &Communication Technologies (ICACCTech), IEEEXplore. ISBN:979-8-3503-8089-7
  • Veena S Badiger (2023). Diabetes Prediction Using Ada Boost Algorithm. International Conference on Advanced Computing &Communication Technologies (ICACCTech), IEEEXplore. ISBN:979-8-3503-8089-7
  • Received Best paper award for the article Brain tumour segmentation and classification using the Convolutional neural network (U- net model), International Conference on Advanced Computing &Communication Technologies (ICACCTech), IEEEXplore

Research Credentials

Scopus ID: 58928234900

ORCID: 0009-0005-9080-7004

Google Scholar: Kvp4dH4AAAAJ