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Academics > Departments

Computer Science & Engineering (CSE)

Dr. V V R Maheswara Rao

Professor & Dean Statutory Bodies |

deansb@svecw.edu.in

Dr. V. V. R. Maheswara Rao is a distinguished Professor in the Department of Computer Science and Engineering. He earned his M.Tech. in Computer Science and Engineering from JNTUK and later obtained his Ph.D. from Acharya Nagarjuna University, specializing in Web Mining with Soft Computing Techniques.

With a strong research background, he has published over 168 research articles in various international journals and conferences. Additionally, Dr. Maheswara Rao has filed and published four patents in the fields of Data Science and Machine Learning.

Driven by a deep passion for Data Science and Machine Learning, he is more than just a professor—he is a mentor, inspiring and shaping young minds through his extensive experience and profound expertise.

Dr. Rao’s illustrious career spans 21 years of dedicated teaching, 15 years of pioneering research, and 5 years of industry experience.

His scholarly work speaks volumes, with 168 research papers, 68 of which are indexed by Scopus and 33 by Web of Science. His research interests span Data Mining, Web Mining, Cloud Computing, Big Data Analytics, Data Science, Artificial Intelligence, and Machine Learning, reflecting his insatiable curiosity and commitment to advancing technology.

  • Senior Member, IEEE
  • Member, IEEE Computational Intelligence Society
  • Associate Member, IE
  • Life Member, CSI
  • Life Member, ISTE

Ph.D. Degree Awardees(02)

  1. Dr. N Silpa – Awarded from Centurion University of Technology and Management, Odisha, India in the year 2024.
      • Thesis Title: A COMPREHENSIVE BIG DATA ANALYTICS FRAMEWORK TO INVESTIGATE WEB USER BEHAVIOUR WITH MACHINE LEARNING APPROACH
  2. Dr. A. Kranthi – Awarded from James Cook University, Australia in the year 2024.
      • Thesis Title:   ENHANCING MANAGEMENT SYSTEMS TO SUPPORT ONLINE LEARNING USING ACADEMAGOGY

 

Ph.D. Pursuing Students (02)

  1. Mr. M Venkata Durga Rao from JNTUK Kakinada, 2023 
  2. Ms. B Revathi from  JNTUK Kakinada, 2024

His impact extends far beyond the classroom. He has led and executed three pivotal projects funded by DST, showcasing his ability to turn ideas into reality. 

  • A Comprehensive Approach to Analyze and Stimulate outcomes of Research and Development activities in Universities, Funded by DST, worth of 32 Lakhs, Period 2018 – 2021.
  • Nutritional Security And Economic Empowerment Of Rural Women Throuh Food Based Interventions And Ass Media (RADI Vishnu 90.4) Approach, , Funded by DST, worth of 27 Lakhs, Period 2015 – 2018.
  • Implementation of improved KNN classification and clustering algorithm as a tools using mining, Funded by DST, worth of 17 Lakhs, Period 2012 – 2015.
Dr. Maheswara Rao has also secured three patents in the interdisciplinary realm of Deep Learning, showcasing his ability to innovate in diverse fields. He’s not just a researcher but also an active member of various journals and conferences, lending his expertise as an Editorial Member and Reviewer.
  1. AN IOT Garbage Segregator & Bin Level Indicator Device 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.
  2. Sun Tracking Solar Panel Device, 1. Shri Vishnu Engineering College For Women(A) 2. Dr. V V R Maheswara Rao
  3. A Combined Approach of DWT-DCT for Blind Medical Image Watermarking 1. Shri Vishnu Engineering College For Women(A) 2. S M Padmaja 3. Dr. V V R Maheswara Rao 4. N. Silpa 5. Lakshman Kumar Dangeti 6. R. Pradeep Sudha 7. B. Mahendra ChandBade 8. P. Sricharani 9. K. Janaki Siva Rama Raju
  4. Autonomous Hybrid CNN-Bi GRU Deep Learning System For Real-Time Wild Animal Surveillance and Instant Alerts 1. Shri Vishnu Engineering College For Women(A) 2. Dr. N.Silpa 3. Dr. V V R Maheswara Rao 4. Dr. Ramachandra Rao Kurada 5. G. S.L.N.V.S.Sindhuja 6. Dr. S M Padmaja 7. Dr. G. Durga Prasad

Journal Publications: 24 (12 SCI + 12 Scopus)

SCI Journal Papers: 12

  1. Umesh Kumar Lilhore, V. V. R. Maheswara Rao, et al., “Hybrid DRL-Enhanced ACO-WWO for Efficient Resource Allocation and Load-Balancing in Cloud Computing,” International Journal of Computational Intelligence Systems, vol. 18, p. 148, 2025, https://doi.org/10.1007/s44196-025-00882-9.
  2. Rao, V.V.R.M., Reddy, S.S., Nrusimhadri, S. et al. A Flawless QoS Aware Task Offloading in IoT Driven Edge Computing System using Chebyshev Based Sand Cat Swarm Optimization. J Grid Computing 23, 7 (2025). https://doi.org/10.1007/s10723-024-09791-1
  3. Pachipala, Y., Dasari, D.B., Rao, V.V.R.M. et al.Workload prioritization and optimal task scheduling in cloud: introduction to hybrid optimization algorithm. Wireless Netw 31, 945–964 (2025). https://doi.org/10.1007/s11276-024-03793-3
  4. Punuri, S. B., Kuanar, S. K., Mishra, T. K., Rao, V. V. R. M., & Reddy, S. S. (2024). Decoding Human Facial Emotions: A Ranking Approach using Explainable AI. IEEE Access, 12, 186229-186245. https://doi.org/10.1109/ACCESS.2024.3474012
  5. Lilhore, U. K., Simaiya, S., Dalal, S., Faujdar, N., Sharma, Y. K., Rao, K. B. V. B., Rao, V. V. R. M., Tomar, S., Ghith, E., & Tlija, M. (2024). ProtienCNN‐BLSTM: An efficient deep neural network with amino acid embedding‐based model of protein sequence classification and biological analysis. Computational Intelligence, 40(4). https://doi.org/10.1111/coin.12696
  6. P, D., Durairaj, M., Subudhi, S. et al.AI-driven drowned-detection system for rapid coastal rescue operations.  Inf. Res. 32, 143–150 (2024). https://doi.org/10.1007/s41324-023-00549-7
  7. Lilhore, U. K., Dalal, S., Varshney, N., Sharma, Y. K., Rao, K. B. V. B., Rao, V. V. R. M., Alroobaea, R., Simaiya, S., Margala, M., & Chakrabarti, P. (2024). Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-54927-8
  8. Kumar Lilhore, U., Simaiya, S., Sharma, Y.K. et al.A precise model for skin cancer diagnosis using hybrid U-Net and improved MobileNet-V3 with hyperparameters optimization. Sci Rep 14, 4299 (2024). https://doi.org/10.1038/s41598-024-54212-8
  9. Silpa, N., Rao, V.V.R.M. Classify and predict web user behaviour using butterfly optimization and recurrent neural network. Multimed Tools Appl83, 66319–66341 (2024). https://doi.org/10.1007/s11042-024-18201-3
  10. Simaiya, S., Lilhore, U.K., Sharma, Y.K. et al. A hybrid cloud load balancing and host utilization prediction method using deep learning and optimization techniques. Sci Rep 14, 1337 (2024). https://doi.org/10.1038/s41598-024-51466-0
  11. Reddy, N. S. S., Gadiraju, M., Preethi, N. M., & Rao, V. (2023). A Novel Approach for Prediction of Gestational Diabetes based on Clinical Signs and Risk Factors. ICST Transactions on Scalable Information Systems, e8. https://doi.org/10.4108/eetsis.v10i3.2697
  12. Vijayan, V.P., Juvanna, I., Rao, V.V.M. et al. Intelligent exploration strategy for a mobile robot to reduce the repeated searches in an unknown environment. Int J Syst Assur Eng Manag (2022). https://doi.org/10.1007/s13198-022-01776-1

Scopus indexed Journal Papers: 12

  1. R, M. R. V. V., Praveena, S. L., Silpa, N., Addanki, K., Reddy, S. S., Kurada, R. R., & Yellamma, P. (2025). Optimization of Neural Network Classifiers by Leveraging the Sequential Feature Engineering for Robust Water Quality Prediction System. Proceedings on Engineering Sciences, 7(1), 1741–1750. https://doi.org/10.24874/pes07.01b.008
  2. S. Reddy, K. Amrutha, V. M. N. S. S. V. K. R. Gupta, K. V. S. S. R. Murthy, and V. V. R. M. Rao, “Optimizing hyperparameters for credit card fraud detection with nature-inspired metaheuristic algorithms in machine learning,” J. Inst. Eng. India Ser. B, 2025. https://doi.org/10.1007/s40031-025-01207-2
  3. Reddy, S. S., Rao, V. V. R. M., Sravani, K., & Nrusimhadri, S. (2024). Image quality evaluation: evaluation of the image quality of actual images by using machine learning models. Bulletin of Electrical Engineering and Informatics, 13(2), 1172–1182. https://doi.org/10.11591/eei.v13i2.5947
  4. Reddy, S. S., Rao, V. R. M., Voosala, P., & Nrusimhadri, S. (2023). You only look once model-based object identification in computer vision. IAES International Journal of Artificial Intelligence, 13(1), 827. https://doi.org/10.11591/ijai.v13.i1.pp827-838
  5. Silpa, N., Swain, S. K., & R, M. R. V. V. (2024). Revolutionizing Feature Engineering for Robust Ensemble Machine Learning by Hybridizing MRMR Insight and Chi2 Independence. Proceedings on Engineering Sciences, 6(3), 1337–1348. https://doi.org/10.24874/pes.si.24.03.017
  6. Praneetha, N., Rao, S. S., R, M. R. V. V., Rao, I. S. S., & Brahmanandam, P. S. (2024). Identity-Based Privacy-Preserving Anonymous Authentication Access Control for Secure Cloud Computing. Proceedings on Engineering Sciences, 6(3), 1327–1336. https://doi.org/10.24874/pes.si.24.03.015
  7. Pachipala, Y., Shaik, M. R., Samavedam, J. R., Peddineni, A., & Rao, V. V. R. M. (2024). Secure User Authentication in the Cloud: Leveraging Face Recognition Technology. Proceedings on Engineering Sciences, 6(4), 1849–1856. https://doi.org/10.24874/pes.si.25.03b.017
  8. Gali, N. R., Terlapu, P. V., Mandavakuriti, Y., Somu, S. M., Telugu, V., & R, M. R. V. V. (2024). Smart Hybrid Models for Improved Breast Cancer Detection. Proceedings on Engineering Sciences, 6(4), 1731–1740. https://doi.org/10.24874/pes.si.24.03.006
  9. Rao, V. VR Maheswara, et al. “An Optimal Machine Learning Model Based on Selective Reinforced Markov Decision to Predict Web Browsing Patterns.” Journal of Theoretical and Applied Information Technology 101.2 (2023): 859-873
  10. Silpa, N., and VVR Maheswara Rao. “Machine Learning-Based Optimal Segmentation System for Web Data Using Genetic Approach.” Journal of Theoretical and Applied Information Technology 100.11 (2022).
  11. Silpa, N., and VVR Maheswara Rao. “Enriched Big Data Pre-Processing Model with Machine Learning Approach to Investigate Web User Usage Behaviour.” Vol. 12 No. 5 (2021). DOI: 10.21817/indjcse/2021/v12i5/211205050.
  12. Silpa, N., & Rao, V. M. (2019). A Complete Research on Techniques & Technologies of Big Web Data Preparation to Web User Usage Behaviour. International Journal of Recent Technology and Engineering (IJRTE), 8(2S11), 2356–2367. https://doi.org/10.35940/ijrte.b1269.0982s1119

Books & Book Chapters: 11 (01 +10)

  • Maheswara Rao V V R, et al. published a text Book entitled “Data Science for Engineers” in Scientific International Publishing House (SIPH), ISBN 978-93-5757-914-8, 2024.
  • Maheswara Rao, V.V.R., et al., “An Optimized Ensemble Machine Learning Framework for Multi-class Classification of Date Fruits by Integrating Feature Selection Techniques”, 2024, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 536. Springer, Cham. https://doi.org/10.1007/978-3-031-48888-7_2
  • Maheswara Rao V V R, et al., “TextRank–Based Keyword Extraction for Constructing a Domain-Specific Dictionary.” In International Conference on Cognitive Computing and Cyber Physical Systems, 2023, Springer Nature Switzerland, doi: 10.1007/978-3-031-48888-7_29.
  • Maheswara Rao V V R, “Preeminent Sign Language System by Employing Mining Techniques,” in IoT Based Control Networks and Intelligent Systems, ICICNIS 2023, vol. 789, Lecture Notes in Networks and Systems, Springer, Singapore, 2024, doi: 10.1007/978-981-99-6586-1_39.
  • Maheswara Rao, V.V.R., Silpa, N., Mahesh, G., Reddy, S.S. “An Enhanced Machine Learning Classification System to Investigate the Status of Micronutrients in Rural Women”, Proceedings of International Conference on Recent Trends in Computing, Lecture Notes in Networks and Systems, vol 341. Springer, Singapore, 2022. https://doi.org/10.1007/978-981-16-7118-0_4.
  • Maheswara Rao, V.V.R., Reddy, S.S., Gadiraju, M., “Analyzing Student Reviews on Teacher Performance Using Long Short-Term Memory”, Innovative Data Communication Technologies and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 96. Springer, Singapore, 2022. https://doi.org/10.1007/978-981-16-7167-8_39
  • Maheswara Rao, V.V.R, Reddy, S.S., Mahesh, G., Preethi, N.M., “Developing Preeminent Model Based on Empirical Approach to Prognose Liver Metastasis”, Ubiquitous Intelligent Systems. Smart Innovation, Systems and Technologies, vol 243. Springer, Singapore, 2022. https://doi.org/10.1007/978-981-16-3675-2_51
  • Maheswara Rao V.V.R., Dr. V. Valli Kumari, Dr. KVSVN Raju “An Intelligent System for Web Usage Data Preprocessing” presented in The First International Conference on Computer Science and Information Technology – CCSIT-2011, January 2 – 4, 2011. Bangalore, India and proceedings published by Springer LNCS-CCIS, ISSN: 1865-0929, ISBN: 978-3-642-17856-6, Vol. 131, Part 1, pp. 481-490, 2011.
  • Maheswara Rao V.V.R., Dr. V. Valli Kumari, Dr. KVSVN Raju “An Intelligent System for Web Usage Data Preprocessing” presented in The First International Conference on Computer Science and Information Technology – CCSIT-2011, January 2 – 4, 2011. Bangalore, India and proceedings published by Springer LNCS-CCIS, ISSN: 1865-0929, ISBN: 978-3-642-17856-6, Vol. 131, Part 1, pp. 481-490, 2011.
  • Maheswara Rao V.V.R., Dr. V. Valli Kumari, Dr. KVSVN Raju “Study of Visitor Behavior by Web Usage Mining” presented in International Conference on Recent Trends in Business Administration and Information Processing – BAIP 2010, March 26-27, 2010, Trivandrum, Kerala, India, and proceedings published by Springer LNCS-CCIS, ISSN: 1865-0929, ISBN: 978-3-642-12213-2, Vol. 70, pp. 181-187, 2010.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “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.
  • Maheswara Rao V V R, et al., “Multi-label and Multi-class Classification on a Custom Dataset using Convolution Neural Networks,” 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2023, pp. 576-579, doi: 10.1109/ICICCS56967.2023.10142828.
  • Maheswara Rao V V R and Dr. Mahesh Gadiraju “Primal-Dual Parallel Algorithm for Optimal Content Delivery in Cloud CDNs”, published in IEEE International Conference on Computational Intelligence and Computing Research, December 2017. DOI: 10.1109/ICCIC.2017.8524392. Scopus Indexed
  • Maheswara Rao V V R and Dr. V. Valli Kumari, “An Efficient Hybrid Predictive Model to Analyze the Visiting Characteristics of Web User using Web Usage Mining” presented in an International Conference on Advances in Recent Technologies in Communication and Computing, ARTCom 2010 Oct 16-17, 2010, Kottayam, India and proceedings published in IEEE Xplore, ISBN: 978-0-7695-4201-0 pp. 225-230, 2010.
  • Reviewer for Springer’s “International Journal of Wireless Information Networks”
  • Reviewer for international Journal of Innovative Research in Advanced Engineering (IJIRAE) https://www.ijirae.com/reviewer-board

In addition to his role as a distinguished professor, Dr. V V R Maheswara Rao serves as the Dean of Statutory Bodies within the institution. In this capacity, he oversees pivotal entities such as UGC, NBA, NAAC, AICTE, JNTUK, APSCHE, AISHE, and other statutory bodies, ensuring compliance and adherence to regulatory standards. Moreover, he shoulders the responsibility of IQAC Coordinator, diligently addressing and mitigating quality concerns at the institute level. Dr. Rao’s multifaceted leadership underscores his commitment to holistic excellence in academia, research and institutional governance.

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