Faculty & Staff
Contact
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Email
parinita.cs.et@msruas.ac.in
- Websites
Ms. Parinita Bora
Assistant Professor
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School/College
Faculty of Engineering and Technology
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Department
Department of Computer Science and Engineering
I have diverse experience spanning the IT industry, government corporate, as well as short-term engagements in academia. I am currently pursuing Ph.D. in the application of machine learning in the area of medical informatics. I qualified for UGC-NET under the Ph.D. category (2024/2025), I had an old GATE score of 92.63 pc (2008). Over the past three years, I have been involved in teaching at Ramaiah University while pursuing my research under research fellowship.
Qualifications
- PhD (Pursuing)
Ramaiah University Of Applied Sciences
- M. Tech. in Machine Learning & Intelligent Systems
Ramaiah University Of Applied Sciences 2020
- B. E in Computer Science & Engg.
Jorhat Engineering College 1994
Academic Experience
- Lectureship (DCB college, a govt. aided college under UGC : 2 yrs )
- Lecturership (NIT Silchar : <1 yr )
- Trainee / R & D Support (SERC, IISc : <2 yrs)
- Consulting in IT (CapGemini Technology Services Pvt. Ltd.: 14 Yrs )
- Dept. of Telecom Services/BSNL: 7 yrs.)
International Conference Papers - Book chapters
- Bora, P. and Chatterjee, S. (2021) ‘A review on deep learning framework for Alzheimer’s disease detection from MRI’, in Proceedings of the International Conference on Computational Intelligence (ICCI 2020), 2 October.
- Nannapaneni, R., Chakravarti, A., Sangappa, S., Bora, P. and Kulkarni, R.V. (2022) ‘Augmentation of handwritten Devanagari character dataset using DCGAN’, in Machine Intelligence and Smart Systems: Proceedings of MISS 2021, pp. 31–44.
- Sharika, S., Bora, P., Kumari, S.D.A. and Chatterjee, S. (2025) ‘SPT based liquefaction prediction of soils employing AI techniques’, in Advances in Materials Science and Technology, pp. 145–153
- Exploring machine learning methodologies and data-driven framework approaches for artificial intelligence in medical informatics.
- interdisciplinary research to bridge computer science/AI and other domains.
ADDRESS
