Department of ECE

Dr.Patike Kiran Rao

M.Tech, PhD,AMIE,MISTE
(HPC Master Trainer)
Associate Professor
Department of CSE

P Kiran Rao is an Associate Professor, Department of CSE, Ravindra College of Engineering for Women. His research focuses on the intersection of computer science and healthcare, specifically in the areas of medical informatics and deep learning. He received his undergraduate degree in Computer Science and Engineering from a reputable university in India. After that, he gained practical experience working in the industry for a few years before pursuing a Master’s Degree in Computer Science. It was during this Master’s program that he developed a keen interest in the field of medical informatics, which led him to pursue a Ph.D. in the same area. His current research involves developing advanced machine learning and deep learning techniques to improve the accuracy and efficiency of medical diagnosis and treatment.

    • RAVINDRA ENGINEERING COLLEGE FOR WOMEN: KURNOOL, ANDRA PRADESH, IN

      2022-02-07 to present | Associate Professor

    • K L University: Hyderabad, Telangana, IN

      2021-12-02 to 2022-02-05 | Assistant Professor (CSE)

    • G PULLAIHA COLLEGE OF ENGINEERING & TECHNOLOGY: KURNOOL, AP, IN

      2008-02-08 to 2021-12-01 | Assistant Professor and Placement Trainer (cse)

    • MS Ramaiah University of Applied Sciences: Bangalore, Karnataka, IN

      May 2024 | PhD (CSE)

    • Jawaharlal Nehru Technological University Anantapur: Anantapur, IN

      March 2012 | M.Tech (CSE)

    • Sri Kottam Tulasi Reddy Memorial College of Engineering: Itikyal, Andhra Pradesh, IN

      March 2007 | MCA (MCA)

    • St Joseph Degree College: Kurnool, AP, IN

      March 2004 | B.Sc(CSE) (CSE)

    • Indian Scoiety for Technical Education: Kurnool, Andhra Pradesh, IN

      | MISTE (CSE)

    • Institution of Engineers India: Kolkata, West Bengal, IN

      2013-05-17 to present | Associate Member – AM151476-0 (CSE)

1.Rao, P.K (2024) Adaptive Cyber Defence: Leveraging GANs for Simulating and Mitigating Advanced Network Attacks in IoT Environments in the 11th ACSS International Doctoral Symposium, July 19-20, 2024

2.Rao, P. K. (2024). Enhancing diagnosis of kidney ailments from CT scan with explainable AI. In *Computational Intelligence Methods and Applications* (pp. TBD). Springer Singapore.

3. Rao, P. K. (2024). SMS2DC: Synchronous mobile sinks scheduling for data collection in internet of things-enabled wireless sensor networks. *International Journal of Network Management*. https://doi.org/10.1002/nem.2267

4. Rao, P. K. (2024). Decoupled SculptorGAN framework for 3D reconstruction and enhanced segmentation of kidney tumors in CT images. *IEEE Access*. https://doi.org/10.1109/ACCESS.2024.3389504

5. Rao, P. K. (2023). Optimizing inference distribution for efficient kidney tumor segmentation using a UNet-PWP deep-learning model with XAI on CT scan images. *Diagnostics, 13*(2), 3244. https://doi.org/10.3390/diagnostics13203244

6. Rao, P. K. (2023). Fusion of graph and tabular deep learning models for predicting chronic kidney disease. *Diagnostics, 13*(12), 1981. https://doi.org/10.3390/diagnostics13121981

7. Rao, P. K. (2022). Sentiment analysis and classification using convolutional neural network architecture. In *Proceedings of the 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)* (pp. TBD). IEEE. https://doi.org/10.1109/ictacs56270.2022.9988084

8. Rao, P. K. (2022). TabNet to identify risks in chronic kidney disease using GAN’s synthetic data. In *Proceedings of the 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)* (pp. TBD). IEEE. https://doi.org/10.1109/ictacs56270.2022.9988284

9. Rao, P. K. (2022). Multilevel ensemble method to identify risks in chronic kidney disease using hybrid synthetic data. In *Proceedings of the 13th International Conference on Computing Communication and Networking Technologies (ICCCNT)* (pp. TBD). IEEE. https://doi.org/10.1109/icccnt54827.2022.9984346

10. Rao, P. K. (2022). Weight pruning-UNet: Weight pruning UNet with depth-wise separable convolutions for semantic segmentation of kidney tumors. *Journal of Medical Signals & Sensors*. https://doi.org/10.4103/jmss.jmss_108_21

11. Rao, P. K. (2021). Recommender system based on deep neural network and long short term memory. In *International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA)* (pp. TBD). IEEE. https://doi.org/10.1109/contesa52813.2021.9657131

12. Rao, P. K. (2021). A comparative review on object detection system for visually impaired. *Turkish Journal of Computer and Mathematics Education, 12*(2). https://doi.org/10.17762/turcomat.v12i2.1442

13. Rao, P. K. (2021). Cassava leaf disease classification using separable convolutions UNet. *Turkish Journal of Computer and Mathematics Education*.

14. Rao, P. K. (2020). Diagnosis of kidney renal cell tumor through clinical data mining and CT scan image processing: A survey. *International Journal of Research in Pharmaceutical Sciences, 11*(1). https://doi.org/10.26452/ijrps.v11i1.1778

Reviewer for Computers in Biology and Medicine

Reviewer for Informatics in Medicine Unlocked

Journal of Bigdata

Digital Health

Journal of Medical Signals and Sensors

Signal, Image and Video Processing

Development of Beaglebone Webcam server for Security Survelliance

The Institution of Engineers (Kolkata)
2013-06 to 2015-02|Grant

GRANT_NUMBER: RDPG2013027)