Sivakamasundari | Computer Science | Best Researcher Award

Ms. Sivakamasundari | Computer Science | Best Researcher Award

SRM Institute of Science and Technology | India

Ms. P. Sivakamasundari is a dedicated academic and researcher in Computer Science and Engineering, recognized for her contributions to deep learning-based medical image analysis. With qualifications spanning Diploma, Bachelor’s, and Master’s degrees in Computer Science and Engineering, she is currently pursuing her Ph.D. at SRM Institute of Science and Technology. She has extensive teaching experience as an Assistant Professor for more than a decade, during which she has guided students in core computing subjects including algorithms, computation theory, compiler design, and image classification. Her research focuses on advanced deep learning frameworks for healthcare applications, particularly diabetic retinopathy and diabetic foot ulcer detection, resulting in book chapters, conference publications, and journal manuscripts under review. She has published and filed patents related to medical imaging and automated disease detection systems, demonstrating her innovation-driven approach. Her scholarly presence includes 1 citation, 1 h-index, and 0 i10-index, indicating emerging research visibility. She has completed multiple professional certifications and participated in workshops, FDPs, and internships in machine learning, biometrics, accelerated computing, and high-performance healthcare analytics. Her work reflects strong commitment toward applying AI for societal benefit, and she continues to advance her expertise through active research and academic contributions.

Profile: Google Scholar

Featured Publications

Sivakamasundari, P., Anandhi, S., Kumaran, A. A., Vijayakumar, K., Birnica, Y. J., & others. (2024). Early detection of glaucoma utilizing retinal nerve fiber layer (RNFL) investigation. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2025). An automatic detection and classification of diabetic foot ulcers using Chebyshev chaotic ladybug beetle optimized extended Swin Transformer–InceptionV3 model. Biomedical Signal Processing and Control, 110, 108268.

Gomathi, G., Sumathy, V., Sivakamasundari, P., & Deepa, R. (2024). A various approaches of machine learning algorithms for kidney disease prediction. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2024). Diabetic foot ulcer classification using deep learning approach. International Conference on Computer, Communication and Signal Processing (ICCCSP).

Sivakamasundari, P., & Niranjana, G. (2023). A critique on deep learning methodologies employed for the identification of diabetic retinopathy using fundus images. Intelligent Computing and Control for Engineering and Business Systems (ICCEBS).

Sri Vasavi Chandu | Computer Science | Best Researcher Award

Ms. Sri Vasavi Chandu | Computer Science | Best Researcher Award

SRM University AP, India

Author Profile

SCOPUS

🎓 EARLY ACADEMIC PURSUITS

Sri Vasavi Chandu began her academic journey in the field of Computer Science and Engineering with a consistent track record of academic excellence. During her undergraduate studies at SRM University, AP, she demonstrated a strong aptitude for core computing principles, programming, and data science. Her curiosity-driven approach during her formative years laid the foundation for her engagement in cutting-edge research, innovation projects, and interdisciplinary collaboration.

🏢 PROFESSIONAL ENDEAVORS

Chandu is currently an Associate Software Engineer at Accenture, where she works in the domain of SAP ABAP and SAP HANA. Her responsibilities include development, testing, and debugging of enterprise-level ABAP applications, working across modules such as Smart Forms, ALE, IDOC, ALV, Function Modules, CDS Views, and Object-Oriented Programming in SAP environments.

She has also interned with:

  • Oasis Infobyte Pvt. Ltd – where she developed responsive web pages using HTML, CSS, and JavaScript, aligning with modern frontend design practices.

  • SRM University Research Internship – contributing to advanced research in relation extraction using knowledge graphs.

  • Twowaits Technologies Pvt. Ltd – where she implemented a cryptography-based encryption-decryption tool and built structured assessment platforms using Python.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN COMPUTER SCIENCE

Chandu’s research interests span multiple domains in computer science, including:

  • Federated Learning

  • Natural Language Processing

  • Cybersecurity and Intrusion Detection

  • Machine Learning Algorithms

  • Knowledge Graphs and Information Retrieval

Her major projects include:

  • Fake News Detection using Federated Learning: Implemented advanced models like LSTM, BERT, and SVM, and deployed a verification website.

  • Music Genre Prediction using Machine Learning: Built multi-model classifiers and used PCA for effective dimensionality reduction.

  • ArtVista Art Gallery Website: Designed a dynamic, feedback-driven art portfolio website using frontend technologies.

  • Event Management System: Developed a backend-intensive platform using MySQL with optimized data storage.

  • Advanced Calculator: Built an intelligent calculator in Python supporting complex operations and robust error handling.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

Chandu has contributed to high-quality publications in reputable international journals and conferences:

  • 📄 “Federated Learning in the Detection of Fake News: A Survey”Elsevier

  • 📄 “Evaluating the Effectiveness of Machine Learning Algorithms for Network Intrusion Detection”Springer Nature

  • 📄 “A Survey on Extraction of Relations using Knowledge Graphs in Various Applications”IEEE

She has also completed professional programs and certifications including:

  • J.P. Morgan Software Engineering Virtual Experience on Forage

  • 21st Century Core Employability Skills Certificate by Skill AP (APSSDC)

  • Participant in Microsoft’s AI Skills Fest, which contributed to a Guinness World Record

🌍 IMPACT AND INFLUENCE

Chandu’s work aligns with global needs for responsible AI, misinformation control, and decentralized data protection. By tackling contemporary issues like fake news detection and network security, she aims to develop transparent, ethical, and explainable AI models. Her participation in international platforms, including Microsoft’s AI Skills Fest, underscores her commitment to leveraging technology for societal good.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Sri Vasavi Chandu is driven by a vision to bridge academic research and real-world application. She is actively shaping her future contributions toward building secure, decentralized, and trustworthy AI systems. With an expanding portfolio of AI-driven solutions and a strong foundation in enterprise technologies, she is poised to contribute to:

  • Federated and Edge AI Systems

  • AI for Social Impact

  • Intelligent Information Extraction

  • Responsible Machine Learning Practices

 ✅CONCLUSION

A driven technologist, research contributor, and solution architect in the making, Sri Vasavi Chandu represents a new generation of engineers who combine technical depth with social consciousness. Her trajectory showcases a commitment to learning, interdisciplinary problem-solving, and real-world innovation. Her future promises impactful contributions across both academia and industry.

🔬NOTABLE PUBLICATION:

Federated Learning in the Detection of Fake News: A Survey
Author: Sri Vasavi Chandu
Journal: Elsevier
Year: 2025

Evaluating the Effectiveness of Machine Learning Algorithms for Network Intrusion Detection
Author: Sri Vasavi Chandu
Journal: Springer Nature Switzerland
Year: 2024

A Survey on Extraction of Relations using Knowledge Graphs in Various Applications
Author: Sri Vasavi Chandu
Journal: IEEE
Year: 2023