Assistant Professor |
Ph.D.: Computer Science Engineering, CUTM, 2024.
M. Tech.: Computer Science Engineering, JNTU Kakinada, 2013.
Teaching Experience: 14 Years
Contact Number: +91 9849776869
Orcid Profile : 0000-0003-3411-0358
Scopus Profile : 57211574487
Google Scholar Profile : aDqm00MAAAAJ
- Data Mining
- Web Mining
- Big Data Analytics
- Data Science
- Artificial Intelligence
- Machine Learning
- Life Member of CSI, ISTE and IE
- Member in CII – IWN
- Project 01:
File No : SR/WOS-A/ET-82/2011
PI : N Silpa
Co-PI : Dr. V V R Maheswara Rao
Area : Text Mining
Project Title : Implementation of Improved KNN Classification and
Clustering algorithms as Tool using Mining
Status : Completed (2012 – 2015)
- Project 02:
File No : DST/NSTMIS/05/159/2017-18
PI : Dr. V V R Maheswara Rao
Co-PI : N Silpa
Area : Big Data Analytics
Project Title : A Comprehensive approach to Analyze and stimulate
Outcomes of Research and Development Activities in Universities
Status : Sanctioned
- AN IOT GARBAGE SEGREGATOR & BIN LEVEL INDICATOR DEVICE in the name of
1. Shri Vishnu Engineering College For Women(A)
2. Dr. V V R Maheswara Rao
3. Dr. G Durga Prasad
4. N Silpa
5. Dr. S M Padmaja
6. N Praveen Kumar.
- N. Silpa and V. M. Rao, “Classify and predict web user behaviour using butterfly optimization and recurrent neural network,” Multimedia Tools and Applications, vol. 1, pp. 1-23, 2024.
- N. Silpa and V. M. Rao, “A Complete Research on Techniques & Technologies of Big Web Data Preparation to Web User Usage Behavior,” International Journal of Recent Technology and Engineering (IJRTE), vol. 8, no. 2S11, 2019.
- N. Silpa and V. M. Rao, “Enriched big data pre-processing model with machine learning approach to investigate web user usage behaviour,” Indian Journal of Computer Science and Engineering, vol. 12, no. 5, pp. 1248-1256, 2021.
- N. Silpa and V. M. Rao, “Machine learning-based optimal segmentation system for web data using Genetic approach,” Journal of Theoretical and Applied Information Technology, vol. 100, no. 11, pp. 3552-3561, 2022.
- V. M. Rao, N. Silpa, M. Gadiraju, R. S. Shankar, V. Kumar, and D. K. B. Rao, “An optimal machine learning model based on selective reinforced Markov decision to predict web browsing patterns,” Journal of Theoretical and Applied Information Technology, vol. 101, no. 2, pp. 859-873, 2023.
- S. S. Reddy, V. V. M. Rao, V. Priyadarshini, and S. Nrusimhadri, ” You only look once model-based object identification in computer vision” IAES International Journal of Artificial Intelligence, vol. 13, no. 1, pp. 827-838, 2024.
- S. S. Reddy, V. V. M. Rao, K. Sravani, and S. Nrusimhadri, “Image quality evaluation: evaluation of the image quality of actual images by using machine learning models,” Bulletin of Electrical Engineering and Informatics, vol. 13, no. 2, pp. 1172-1182, 2024.
- Karrar S. Mohsin, Jhansilakshmi Mettu, Chinnam Madhuri, Gude Usharani, Silpa N and Pachipala Yellamma, “Enhancing Urban Traffic Management Through Hybrid Convolutional and Graph Neural Network Integration”, pp. 360-370, April 2024. doi: 10.53759/7669/jmc202404034.
- V. V. R. Maheswara Rao, N. Silpa, G. Mahesh, and S. S. Reddy, “An enhanced machine learning classification system to investigate the status of micronutrients in rural women,” in Proceedings of International Conference on Recent Trends in Computing: ICRTC 2021, pp. 51-60, Springer Singapore, 2022.
- G. Mahesh, S. Shankar Reddy, V. V. R. Maheswara Rao, and N. Silpa, “Preeminent Sign Language System by Employing Mining Techniques,” in International Conference on IoT Based Control Networks and Intelligent Systems, pp. 571-588, Singapore, Springer Nature Singapore, June 2023.
- V. V. R. Maheswara Rao, N. Silpa, S. S. Reddy, S. M. Hussain, S. Bonthu, and P. J. Uppalapati, “An Optimized Ensemble Machine Learning Framework for Multi-class Classification of Date Fruits by Integrating Feature Selection Techniques,” in International Conference on Cognitive Computing and Cyber Physical Systems, pp. 12-27, Cham, Springer Nature Switzerland, December 2023.
- M. R. V V R, S. N, M. Gadiraju, S. S. Reddy, S. Bonthu and R. R. Kurada, “A Plausible RNN-LSTM based Profession Recommendation System by Predicting Human Personality Types on Social Media Forums,” 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2023, pp. 850-855, doi: 10.1109/ICCMC56507.2023.10083557.
- N. Silpa, V. V. R. Maheswara Rao, M. V. Subbarao, R. R. Kurada, S. S. Reddy and P. J. Uppalapati, “An Enriched Employee Retention Analysis System with a Combination Strategy of Feature Selection and Machine Learning Techniques,” 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2023, pp. 142-149, doi: 10.1109/ICICCS56967.2023.10142473.
- S. S. Ahmed, P. J. Uppalapati, S. Ayesha, S. M. Hussain, K. Narasimharao and N. Silpa, “Assessing Public Sentiment towards Digital India through Twitter Sentiment Analysis: A Comparative Study,” 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2023, pp. 955-959, doi: 10.1109/ICICCS56967.2023.10142882.
- R. R. Kurada, S. Pattem, R. Y, M. R. VVR, S. N and S. Bonthu, “Raitu Vrudhi – An Android based Mobile Application for Agro-Marketing,” 2023 4th International Conference for Emerging Technology (INCET), Belgaum, India, 2023, pp. 1-7, doi: 10.1109/INCET57972.2023.10170078.
- M. V. Subbarao, U. L. S. Rani, J. T. S. Sindhu, G. P. Kumar, V. Ravuri and S. N, “A Comprehensive Study of Machine Learning Algorithms for Date Fruit Genotype Classification,” 2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC), Dharwad, India, 2023, pp. 1-7, doi: 10.1109/ICAISC58445.2023.10199785.
- M. Rao V V R, M. K, S. N, V. S. S. P. R. Gottumukkala, N. R. M and N. Pamarthi, “An Innovative Machine Learning based Heart Disease Assessment System by Sequential Feature Selection Approach,” 2023 3rd International Conference on Intelligent Technologies (CONIT), Hubli, India, 2023, pp. 1-7, doi: 10.1109/CONIT59222.2023.10205817.
- S. N, M. R. V. V. R, M. V. Subbarao, M. Pradeep, C. R. Grandhi and A. Karunasri, “A Robust Team Building Recommendation System by Leveraging Personality Traits Through MBTI and Deep Learning Frameworks,” 2023 International Conference on IoT, Communication and Automation Technology (ICICAT), Gorakhpur, India, 2023, pp. 1-6, doi: 10.1109/ICICAT57735.2023.10263718
- R. R. Kurada, K. Pavan Kanadam, Y. Ramu, N. Silpa, V. V. R. M. Rao and S. Pattem, “Story Telling with Basic and Advanced Data Visualizations of Blockchain Technologies,” 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 1254-1259, doi: 10.1109/ICAISS58487.2023.10250661.
- N. Silpa, V. Vaishalini, S. V. S. S. Lakshmi, M. R. V V R, R. R. Kurada and S. Bonthu, “Empowering Diabetic Prediction through MRMR-Driven Feature Selection and Robustness of Ensemble Machine Learning,” 2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS), Kalaburagi, India, 2023, pp. 1-7, doi: 10.1109/ICIICS59993.2023.10421410. –
- M. R. V. V. R, S. N, S. Shankar Reddy, R. Rao Kurada, S. Mahaboob Hussain and E. L Sameera, “A Robust XG-Boost Machine Learning Model for Water Quality Estimation System by Leveraging with Chi-Square Forward Sequential Feature Selection Technique,” 2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE), Ballari, India, 2023, pp. 1-7, doi: 10.1109/AIKIIE60097.2023.10390370.
- M. R. V V R, S. N, S. S. Reddy, S. Bonthu, R. Rao Kurada and V. Vaishalini, “An Optimized Ensemble Machine Learning Framework for Water Quality Assessment System by Leveraging Forward Sequential Minimum Redundancy Maximum Relevance Feature Selection Method,” 2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), Chennai, India, 2023, pp. 1-8, doi: 10.1109/ICSES60034.2023.10465554.
