Assistant Professor
Department of Artificial Intelligence and Data Science
CMR Institute of Technology, Bengaluru
Email: shiksha.s@cmrit.ac.in
Phone: 9844411847
Dr. Shiksha is always ready to learn new things and to reskill herself, she likes learning new things hence she moved from Electrical & Electronics to Nano electronics to Software and then to Data Science and to Artificial Intelligence. And when she got the opportunity to enroll for PhD in Artificial Intelligence after completing MSc in Data Science under Dr. Elon Correa in Liverpool University, she didn't have to think regarding it, as already MSc had instilled in her the interest for the Data Science field which she wanted to explore more and this research zeal is still continuing that's why now also after her PhD in the field of Artificial Intelligence, she wants to continue her studies in academic field helping others to gain knowledge in this field. Many of her research contributions have been published in Scopus-indexed journals and books, and many more are in pipelines showing her enthusiasm in the academic field.
Ph.D in Artificial Intelligence - Liverpool John Moores University, UK. Graduated on 1st Dec 2025
MSc in Data Science - Liverpool John Moores University, UK. Graduated in 2020
PG Diploma in Data Science - IIIT B, Graduated in 2019
MSc in Nanoelectronics and Nanotechnology - University of Southampton, UK, Graduated in 2013
B.E in Electrical and Electronics - Manipal Institute of Technology, Graduated in 2009
Assistant Professor - CMRIT (present)
Thesis Supervisor - upGrad from 12/2020 to 12/2021
Consultant - Capgemini from 05/2015 to 10/2017
Software Developer - TCS from 12/2009 to 06/2012
Artificial Intelligence
Deep Learning
Machine Learning
Data analysis
Shiksha, & Correa, E. (2023). A Review on Performance Evaluation using Machine Learning Algorithms to Predict Cardiac Event for Diabetes. 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023, 2023-June, 2684-2690.
Shiksha, & Correa, E. (2024). A Review on Performance Evaluation using Convolutional Neural Network to Predict Cardiac Event. 15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024, 1, 290-296.
Shiksha, & Correa, E. (2023). Poster presentation. Developing Artificial Intelligence Models to Detect Cardiac Events. LJMU Postgraduate Researcher Conference, Liverpool, UK.2023
Shiksha, & Correa, E. (2025). Multimodal data analysis of ECG and clinical data to identify cardiovascular diseases using a large dataset. LJMU Postgraduate Researcher Conference, Liverpool, UK.2024, British Library.
Shiksha & Jayabalan, M. (2024). Use of machine learning in credit card fraud detection. Digital Innovation Adoption: Architectural Recommendations and Security Solutions, pp. 79 – 95. DOI: 10.2174/9789815079661124010010
Shiksha. (2022). Application of machine learning algorithms with balancing techniques for credit card fraud detection: A comparative analysis. Fundamentals and Methods of Machine and Deep Learning: Algorithms, Tools, and Applications, pp. 277 – 309. DOI: 10.1002/9781119821908.ch12
Google Scholar - https://scholar.google.co.in/citations?hl=en&user=hbG7A3EAAAAJ&hl
Scopus: https://www.scopus.com/pages/publications/85208789747
Researchgate: https://www.researchgate.net/profile/Shiksha-Shiksha
Orcid id- 0009-0007-3967-7536