Ph.D.: KL University, Pursuing
PG: M. Tech (CSE), Vardhaman College of Engineering, Feb-2012
UG: B. Tech (CSE), KITS, Huzurabad, 2008
Teaching Experience: 15 years
Research Experience: 4 years
JNTUH Registration ID: 87150331-221138
AICTE Registration ID: 1-3578008056
- Artificial Intelligence and Machine Learning
- Deep Learning
- CSI Membership-2010000454
- FET Qualified-2011
- Kondra, Pranitha, and Naresh Vurukonda. “Feature extraction and classification of gray-scale images of brain tumor using deep learning.” Scalable Computing: Practice and Experience25, no. 2 (2024): 1005-1017.
- Pranitha, Kondra, and Naresh Vurukonda. “Hybrid deep learning algorithm for multi-grade brain tumor classification.” African Journal of Biomedical Research27, no. 3 (2024): 805-822.
- Raju, Ch Suresh Kumar, Kondra Pranitha, Pusarla Samyuktha, and Jessu Madhumathi. “Prediction of COVID 19-chest image classification and detection using RELM classifier in machine learning.” In 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS), vol. 1, pp. 1184-1188. IEEE, 2022.
- Pranitha, Kondra, Naresh Vurukonda, and Rudra Kalyan Nayak. “A comprehensive survey on MRI images classification for brain tumor identification using deep learning techniques.” In 2022 3rd International Conference on Smart Electronics and Communication (ICOSEC), pp. 1206-1212. IEEE, 2022.
- Narendra Kumar Rao, B., Kondra Pranitha, Ranjana, C. V. Krishnaveni, and Midhun Chakkaravarthy. “Text recognition from Images using deep learning techniques.” In Intelligent Computing and Applications: Proceedings of ICDIC 2020, pp. 265-279. Singapore: Springer Nature Singapore, 2022.
- Pranitha, Kondra, K. Reddy Madhavi, Rudraraju Pranathi, Abdul Bari Shaik, and Pantham Vishnu. “Automatic Brain Tumor Classification Using Transfer Learning.” In International Conference on Intelligent Healthcare and Computational Neural Modeling, pp. 179-185. Singapore: Springer Nature Singapore, 2022.
- Anumandla, Sannith Reddy, Shivani Cherupally, Alluri Supriya Reddy, A. Vamshi Krishna, and K. Pranitha. “A Classification based approach for early stage Prediction and Multi-dimensional analysis of Alzheimer’s Disease.” In 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT), vol. 1, pp. 408-413. IEEE, 2024.
- Madhu, R., G. Deepika, K. Manasa, P. Chinnasamy, Revathi Durgam, and Kondra Pranitha. “Machine Learning-Based Analysis of MRI Data for Brain Disorder Diagnosis.” Available at SSRN 5109744 (2024).
- Raju, K. Srujan, K. Suneetha, K. Reddy Madhavi, Kondra Pranitha, J. Avanija, and B. Narendra Kumar Rao. “Enhancing Smart Agriculture Applications Utilizing Deep Learning Models and Computer Vision Techniques.” In Agriculture and Aquaculture Applications of Biosensors and Bioelectronics, pp. 241-255. IGI Global Scientific Publishing, 2024.
- Reddy Madhavi, K., K. Pranitha, M. Tech, Nagendar Yamsani, Mohmad Ahmed Ali, K. Srujan Raju, Balijapalli Prathyusha, and B. Tech. “Image Steganography Using Deep Neural Networks.” (2024).
- Problem solving through Programming In C, 12 Weeks and April-2019
- Deep Learning – IIT Ropar, 12 Weeks, Oct 2024
- Attended FDP on “Introduction to Python Programming” from 17-4-2019 to 22-4-2019 Conducted by Microsoft at BVRIT Narsapur.
- Attended five-day International FDP on “Advancements in Medical Imaging through Machine Learning and Deep Learning: Techniques, Applications, and Challenges from 11th to 15th March 2024, conducted by KL University.
- Attended FDP on “Deep Learning” through NPTEL 12-Weeks Course.
- Attended ATAL FDP on “The future of Quantum computing and High-performance computing (HPC)”.
