COMPUTER SCIENCE AND ENGINEERING

Ms. Bandaru Shanmukha Priya

Dr. Shanmuga Sundari M

Assistant Professor
sundari.m@bvrithyderabad.edu.in

AICTE ID: 1-9431856930
JNTUH ID: 1271-161224-100146
Ratified Status: Ratified

Ph.D.: A Study of Neurological Disorders and Heart Diseases through Pattern Mining Analysis for Improved Healthcare Strategies, Koneru Lakshmaih Education Foundation Vaddeswaram, A.P, India.  Year- 2024
M.Tech.: VNRVJIET, JNTUH, 2009
B.Tech.: Madurai Kamaraj University, 2002

Teaching Experience: 15 Years
Research Experience: 05 Years
Industry Experience: 05 Months

Scopus ID: 57443320100
WoS ID: AAZ-1771-2021
Google Scholar ID: https://scholar.google.com/citations?user=ABiTas4AAAAJ&hl=en
Vidwan ID: 206991
ORCID ID: 0000-0001-5755-474X

Health Care-Deep Learning, Image Processing, Computer Vision

  1. Best Paper Award for Students paper in Conference
  2. Received Gold Medal in M.Tech Academics
  3. Best outgoing student in M.Tech Software Engineering
  4. Best Project in M.Tech
  5. NPTEL Discipline star 2019
  6. Bronze Partner faculty under Inspire- The campus connect Faculty Partnership Model
  7. School First academics medal in 10th, 11th and 12th class
  1. Sundari, M. S.,(2025). Navigating Innovations and Challenges in Travel Medicine and Digital Health. In Navigating Innovations and Challenges in Travel Medicine and Digital Health(pp 1-32).
  2. Sundari, M. S., & Gangalapudi, K. P. (2025). Balancing Digital Efficiency With Human Connection in the Workplace. In Humanizing the Hyperconnected Workplace (pp. 31-68). IGI Global Scientific Publishing.
  3. Shanmuga Sundari, M., Rishitha, K. (2024). The Industrial Use Cases of Embodied AI Systems. In: Raj, P., Rocha, A., Singh, S.P., Dutta, P.K., Sundaravadivazhagan, B. (eds) Building Embodied AI Systems: The Agents, the Architecture Principles, Challenges, and Application Domains. Information Systems Engineering and Management, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-031-68256-8_16
  4. Shanmuga Sundari, M., Penthala, H. R., Mogullapalli, A., & Ammangatambu, M. M. (2024). AI‐Based Personalized Drug Treatment. Artificial Intelligence and Machine Learning in Drug Design and Development, 369-406.
  5. Shanmuga Sundari, M., Thotakura, S. A., Dharmana, M., Gadela, P., & Ammangatambu, M. M. (2024). Process and Applications of Structure‐Based Drug Design. Artificial Intelligence and Machine Learning in Drug Design and Development, 321-368.
  6. Sundari, M. S., Penthala, H. R., & Nayyar, A. Transforming Education through AI-Enhanced Content Creation and Personalized Learning Experiences. In Impact of Artificial Intelligence on Society (pp. 98-118). Chapman and Hall/CRC.
  7. Sundari, S., Penthala, H. R., Mogullapalli, A., Sukhavasi, V., & Nayyar, A. (2024). Women and Millets: Historical Perspective. In The Role of Women in Cultivating Sustainable Societies Through Millets (pp. 196-229). IGI Global.
  8. Shanmuga, S. M., & Bhambri, P. (2024). Bone Marrow Cancer Detection From Leukocytes using Neural Networks. In Computational Intelligence and Blockchain in Biomedical and Health Informatics (pp. 307-319). CRC Press.
  9. Shanmuga, S. M., & Bhambri, P. (2024). Pulmonary and Lungs Nodule Classification using Deep Learning. In Computational Intelligence and Blockchain in Biomedical and Health Informatics (pp. 320-331). CRC Press.

Book:

  1. A SIGNIFICANT APPROACHON MACHINE LEARNING AND

IT’S APPLICATIONS- ISBN: 978-93-90651-92-4- Mahi Publication

  1. Sundari, S., Divya, Y., Durga, K. B. K. S., Sukhavasi, V., Sugnana Rao, M. D., & Rani, M. S. (2024). A Stable Method for Brain Tumor Prediction in Magnetic Resonance Images using Finetuned XceptionNet. International Journal of Computing and Digital Systems, 15(1), 67-79.
  2. Sundari M, S., Sukhavasi, V., Kbks, D., Shaylesh Lunawat, P., & Mandya Ammangatambu, M. (2024). Optimized AlexNet For Enhanced Tuberculosis Classification Using Deep Learning. International Journal of Computing and Digital Systems, 16(1), 1509-1522.
  3. Jadala, V. C. (2024). Real-Time Neurological Disease Prediction with 3D Single Pose Estimation using MediaPipe. International Journal of Intelligent Systems and Applications in Engineering, 12(4s), 595-607.
  4. Shanmuga Sundari, M., & Jadala, V. C. (2023). Neurological disease prediction using impaired gait analysis for foot position in cerebellar ataxia by ensemble approach. Automatika, 64(3), 541-550.
  5. Performance Analysis and Activity Deviation Discovery in Event Log Using Process Mining Tool for Hospital System, Journal of Information Systems and Telecommunication (JIST), 11(42), 110-122.
  6. Shanmuga Sundari, M., & Jadala, V. C. (2022). Improved Performance Analysis for Cerebellar Ataxia disease Classification using AdaBoost. NeuroQuantology, 9488-9497.
  7. Sundari, M. S., & Nayak, R. K. (2020). Process mining in healthcare systems: a critical review and its future. International Journal of Emerging Trends in Engineering Research, 8(9).
  8. Sundari, M. S., & Nayak, R. K. (2020). Master card anomaly detection using random forest and support vector machine algorithms. J. Critic. Rev, 7(9).
  1. Swapna, D., Sundari, M. S., Sreeja, G. K., Varma, S. S., & Rajeshwari, M. (2024, September). Robust Statistical Models for Identifying Inauthentic Online Reviews. In 2024 4th International Conference on Soft Computing for Security Applications (ICSCSA) (pp. 466-470). IEEE.
  2. Sundari, M. S., Ammangatambu, M. M., Mythili, R., & Anisha, M. Chestnet-TB: A Novel Approach to Tuberculosis Classification from Chest Radiology Using Modified AlexNet. Amit Kumar Gheorghita Ghinea, 437.
  3. Sukhavasi, V., Shanmuga Sundari, M., Nithya, K. Y., & Bairu, P. (2024, September). Spatial Temporal Signatures: A Hybrid CNN-LSTM Architecture for Improved Sign Language Recognition. In International Conference on Electronic Governance with Emerging Technologies (pp. 21-32). Cham: Springer Nature Switzerland.
  4. Divya, Y., Shanmuga Sundari, M., Seekruthi, K., Jyothsna, B., & Chaitanya, T. (2024, March). EfficientNetB1 Empowered Deep Learning for Accurate Leukemia Detection in Blood Smear Image. In International Conference on Computing and Machine Learning (pp. 345-355). Singapore: Springer Nature Singapore.
  5. Durga, K. B. K. S., Shanmuga Sundari, M., Akshaya, K., Shresta, M., & Tejaswini, U. (2024, March). Unveiling Insights: AlexNet-Driven MRI Analysis for Precision Diagnosis of Knee Disorders. In International Conference on Computing and Machine Learning (pp. 319-329). Singapore: Springer Nature Singapore.
  6. Bindu, V., Sundari, M. S., Pasupuleti, P., Shaik, R., & Pochareddy, J. (2024, November). Revolutionizing Skin Disease Diagnosis: Advanced Image Analysis and Precision Healthcare using EfficientNet. In 2024 8th International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 604-608). IEEE.
  7. Durga, K., Sundari, M.S., Shaik, A., Mukthala, S., Gudapati, H. (2025). Improving PCOS Diagnosis Accuracy with CNN-Based Image Analysis. In: Bairwa, A.K., Tiwari, V., Vishwakarma, S.K., Tuba, M., Ganokratanaa, T. (eds) Computation of Artificial Intelligence and Machine Learning. ICCAIML 2024. Communications in Computer and Information Science, vol 2185. Springer, Cham. https://doi.org/10.1007/978-3-031-71484-9_4.
  8. Mariyappan, S. S., Divya, Y., Sukhavasi, V., Durga, K. B. K. S., & Samyuktha, P. (2024, July). Improved prediction accuracy for stocks using long short-term memory algorithm. In AIP Conference Proceedings (Vol. 3028, No. 1). AIP Publishing.
  9. Mariyappan, S. S., Penthala, H. R., Nagaram, A., & Arisham, D. (2024, July). Retina fundus disease gray scale image perception using semantic segmentation model. In AIP Conference Proceedings (Vol. 3028, No. 1). AIP Publishing.
  10. Mariyappan, S. S., Ammangatambu, M. M., & Sai, B. C. (2024, July). Dynamic gender recognition using Yolov7 with minimal frame per second. In AIP Conference Proceedings (Vol. 3028, No. 1). AIP Publishing.
  11. Durga Devi, T., Shanmuga Sundari, M., Swarnalatha, P., Aishwarya, K., & Nikhitha, S. (2023, April). IoT-Based Automated Dustbin Using Arduino and Global System for Mobile Communication. In International Conference on Recent Trends in Machine Learning, IOT, Smart Cities & Applications (pp. 699-705). Singapore: Springer Nature Singapore.
  12. S. M, S. Das and H. Mazumdar, “Predictive Accuracy Analysis for Corona Virus Using Residual U-Net in Radiological Data,” 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), Gwalior, India, 2024, pp. 1-6, doi: 10.1109/IATMSI60426.2024.10503374. keywords: {Covid-19;Prediction;Radiological data;Residual U-Net;X-Ray},
  13. M, Sai, B. C., Tinnaluri, Y., & Tella, T. (2024, January). Accurate Prediction of Classifcation Score using DenseNet for Acute Pneumonia. In 2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) (pp. 1293-1299). IEEE.
  14. M, Sukhavasi, V., Gangisetty, N., & Maharaj, N. S. (2023, December). Accuracy Prediction for Detecting Brain Tumour from MRI Images using ResNet50. In 2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA) (pp. 420-426). IEEE.
  15. M, Srividya, K., Jadala, V. C., Chandrasekhar, U., Durga, K., & Ammangatambu, M. M. (2023, December). Improved Classification for Corona Virus Disease using XceptionNet in X-Ray Images. In 2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA) (pp. 396-400). IEEE.
  16. S. M, M. D. S. Rao, M. S. Rani, K. Durga and A. Kranthi, “Covid-19 X-Ray Image Detection using ResNet50 and VGG16 in Convolution Neural Network,” 2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), Gwalior, India, 2022, pp. 1-5, doi: 10.1109/IATMSI56455.2022.10119261.
  17. Shanmuga Sundari, M., Priya, K. S. S., Haripriya, N., & Sree, V. N. (2023). Music Genre Classification Using Librosa Implementation in Convolutional Neural Network. In Proceedings of Fourth International Conference on Computer and Communication Technologies (pp. 583-591). Springer, Singapore.
  18. Shanmuga Sundari, M., Dyva Sugnana Rao, M., & Kumar, C. A. (2023). Effective Prediction Analysis for Cardiovascular Using Various Machine Learning Algorithms. In Proceedings of Fourth International Conference on Computer and Communication Technologies (pp. 641-650). Springer, Singapore.
  19. Uddagiri, C., & Shanmuga Sundari, M. (2023). Authorship Identification Through Stylometry Analysis Using Text Processing and Machine Learning Algorithms. In Proceedings of Fourth International Conference on Computer and Communication Technologies (pp. 573-581). Springer, Singapore.
  20. Shanmuga Sundari, M., Sudha Rani, M., & Kranthi, A. (2023). Detect Traffic Lane Image Using Geospatial LiDAR Data Point Clouds with Machine Learning Analysis. In Intelligent System Design (pp. 217-225). Springer, Singapore.
  21. Shanmuga Sundari, M., Sudha Rani, M., & Ram, K. B. (2023). Acute Leukemia Classification and Prediction in Blood Cells Using Convolution Neural Network. In International Conference on Innovative Computing and Communications (pp. 129-137). Springer, Singapore.
  22. Raju, C. S. K., Pranitha, K., Sundari.M, Samyuktha, P., & Madhumathi, J. (2022, March). 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.
  23. Shanmuga Sundari, M., Samyuktha, P., Kranthi, A., & Das, S. (2022). Evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector Machine. In Smart Intelligent Computing and Applications, Volume 1 (pp. 151-159). Springer, Singapore.
  24. Shanmuga Sundari, M., Deekshitha, C., Rani, V. E., & SriChandana, D. (2022, June). Automatic Detection of Diabetic Eye Disease Using Convolutional Neural Network. In International Conference on Frontiers of Intelligent Computing: Theory and Applications (pp. 621-628). Singapore: Springer Nature Singapore.
  25. Khatoon Mohammed, T., Shanmuga Sundari, M., & Sivani, U. L. (2022). Brain Tumor Image Classification with CNN Perception Model. In Soft Computing and Signal Processing (pp. 351-361). Springer, Singapore.
  26. S. M, V. C. Jadala, S. K. Pasupuleti and P. Yellamma, “Deep Learning analysis using ResNet for Early Detection of Cerebellar Ataxia Disease,” 2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC), Bhubaneswar, India, 2022, pp. 1-6, doi: 10.1109/ASSIC55218.2022.10088379.
  27. Shanmuga Sundari, M., & Nayak, R. K. (2023). Comparative Analysis of Process Mining Algorithms in Industrial Applications. In Proceedings of the International Conference on Cognitive and Intelligent Computing (pp. 463-468). Springer, Singapore.
  28. Shanmuga Sundari, M., & Nayak, R. K. (2023). Deviation and Cluster Analysis Using Inductive Alpha Miner in Process Mining. In Communication, Software and Networks (pp. 451-458). Springer, Singapore.
  29. Shanmuga Sundari, M., & Jadala, V. C. (2022). Improved Performance Analysis for Cerebellar Ataxia disease Classification using AdaBoost. NeuroQuantology, 9488-9497.
  30. Sundari, M. S., Jadala, V. C., & Pasupuleti, S. K. (2022, June). Prediction of Activity pattern mining for Neurological disease using Convolution Neural Network. In 2022 7th International Conference on Communication and Electronics Systems (ICCES) (pp. 1319-1324). IEEE.
  31. Chandra, J. V., & Pasupuleti, S. K. (2022, March). Machine Learning Methodologies for predicting Neurological disease using Behavioral Activity Mining in Health Care. In 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS) (Vol. 1, pp. 1035-1039). IEEE.
  32. Sundari, M. S., & Nayak, R. K. (2021, November). Efficient Tracing and Detection of Activity Deviation in Event Log Using ProM in Health Care Industry. In 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) (pp. 1238-1245). IEEE.
  1. Integrated System for Neuro Disease Diagnosis and Management Using Large Language Models and Advanced Image Processing- 202541010761-7/2/2025
  2. Enhanced Human Pose Estimation with Predictive Modeling Using U-Net and BlazePose Frameworks- 202541007992-30/1/2025
  3. Smart Diaper System with Load Monitoring and Insect Detection for Healthcare Assistance-202441101562-10/1/2025
  4. Posture Screening System for Joint Injury Detection in Athletes Using Biomechanical Analysis- 202441083588- 8/11/2024
  5. Automated Gas Cylinder Management System with Integrated Smart Dashboard Control-202441079729-25/10/2025
  6. A SYSTEM AND METHOD FOR OPTIMIZED TIMEFRAME BRAIN TUMOR DETECTION UTILIZING SQUEEZENET TECHNOLOGY- 202441008405
  7. Advanced Enhanced Neural Style Transfer (NST) Method Leveraging ResNet Architecture for High-Fidelity Image Synthesis- 202341066332
  8. METHOD AND SYSTEM FOR IMPLEMENTING POWER GRID CONTROL OPERATIONS USING BIG DATA BASED ARTIFICIAL INTELLIGENCE (AI) TECHNIQUES- 202141054474 A
  9. SECURED IoT FRAMEWORK FOR MALWARE DETECTION ON CLOUD NETWORKS USING MACHINE LEARNING- 202341002324
  10. Method and System for Neurological Disease Prediction and Pattern Mining: Identifying Disease Patterns and Predictive Models for Enhanced Diagnosis and Treatment- 202341054290

Nil

  1. ISTE (Indian Society for Technical Education) – Life time membership LM-62894
  2. ACM Membership- 9444660

Nil

Nil

Nil

Five day Faculty Development Program on Mastering Cloud Computing Essentials with AWS in collaboration with the National Institute of Technical Teachers Training & Research (NITTTR) March 3, 2025 to March 7,2025

  1. AI and Digital Technologiesfor Sustainable Healthcare and Medical Technologies at Institute of Technology, Nirma University from 25/11/2024 to 30/11/2024 (ATAL)
  2. Five day Faculty Development Program on Mastering Cloud Computing Essentials with AWS in collaboration with the National Institute of Technical Teachers Training & Research (NITTTR) March 3, 2025 to March 7,2025
  3. Generative AI: Transforming Education and Research at BVRIT HYDERABAD COLLEGE OF ENGINEERING FOR WOMEN from 08/01/2024 to 13/01/2024. (ATAL)
  4. Artificial Intelligence for Agriculture Innovation (AI4AI) at BVRIT HYDERABAD COLLEGE OF ENGINEERING FOR WOMEN from 11/12/2023 to 16/12/2023. (ATAL)
  5. One week OFDP on “IOT and Machine Learning” conducted by G Pulla Reddy Engineering College, Kurnool
  6. One week FDP on “Cloud computing & Devops” organized by VNRVJIET, Hyderabad
  7. Five days OFDP on “Emerging Technologies in Computer Science” organized by Dr.M.G.R. Educational & Research Institute – Chennai
  8. Six days National workshop on ” Web Designing” conducted by Hyderabad Institute of Technology And Management
  9. One Week National Level Online Faculty Development Programme on “Design Thinking” conducted by Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh
  10. Five days OFDP on “Machine Learning ” conducted by J.B.Institute of Engineering & Technology
  11. Three days FDP on “Hadoop and Machine Learning” conducted by Malla Reddy Institute of Technology
  12. Five days FDP on “Cyber security” conducted by VNRVJIET, Hyderabad
  13. One Week Online FDP on “Internet of Things and Artificial Intelligence Applications” organized by the Department of Computer Engineering, K L Deemed to be University, Vaddeswaram, Guntur, Andhra Pradesh
  14. Five days FDP on ” Cloud Computing using Amazon Web Services” conducted by Trinity College of Engineering & Research,Pune
  15. One Week Online Faculty Development Programme “PHP and MySQL” conducted by Sridevi Womens
  16. Engineering College, Hyderabad
  17. One Week Online Faculty Development Program on “PYTHON 3.4.3” Organized by Pragati Engineering College (Autonomous), Surampalem, A.P.
  18. One Week FDP on “AIML” organized by VNRVJIET, Hyderabad
  19. Three days Online FDP on “Intoduction to Machine Learning” organized by MITS-Madanapalle
  20. Five days OFDP on “Artificial Intelligence” conducted by GNITS, Hyderabad
  21. Three days OFDP on “Internet of Things” conducted by Anurag University
  22. Two days OFDP on “Machine learning with matlab” conducted by Malla Reddy College of Engineering
  23. Two days FDP on “Blockchain Technology” conducted by MITS, Madanapalle
  24. One week FDP on “IOT Development and Analytics” conducted in GNITS, Hyderabad
  25. Two days workshop on “Outcome Based Education in Engineering, Teaching and Assessment”
  26. Work shop attended on “Pedagogic Techniques and Teaching and Learning Methods” in IIT, Hyderabad
  27. Two days workshop on “BLOCK CHAIN TECHNOLOGY” conducated by KMIT, Hyderabad
  28. Two days workshop on “Free and open source alternative for web conferencing and teaching learning” organized by MGIT, Hyderabad
  29. One week National Level Online Faculty Development Program on “Artificial Intelligence Applications through Machine Learning” organized by Balaji Institute of Technology & Science, Warangal
  30. One week national workshop on AI & ML conducted by Chalapathi institute of engineering & technology, Guntur
  1. WISE In-Charge
  2. WISE Trainer
  3. Hackathon In-Charge
  4. NAAC, NBA Criteria 2