Osmania University | India
Author Profile
Scopus
Early Academic Pursuits
Dr. Swathi Priyadarshini Tigulla laid the foundation of her academic journey with a degree in Information Technology, followed by a master’s program in Information Technology with a specialization in network security. Her pursuit of advanced knowledge culminated in a doctoral degree in Computer Science and Engineering from Osmania University. From the beginning, she demonstrated a strong inclination toward solving computational problems and a keen interest in the emerging domains of artificial intelligence, machine learning, and network security.
Professional Endeavors
Her professional career reflects an extensive teaching and mentoring journey across reputed institutions. She began her career as an Assistant Professor in engineering colleges where she taught computer science, network security, and software engineering, and guided student projects. Over the years, she progressed to significant academic roles, including serving as Head of the Department, coordinating extracurricular activities, and contributing to student training and placement. Presently, she continues her academic engagement as an Assistant Professor specializing in artificial intelligence and machine learning, while also actively mentoring projects and participating in innovative academic initiatives such as GEN-AI teams and project schools.
Contributions and Research Focus
Dr. Tigulla’s research is strongly anchored in artificial intelligence, machine learning, and soft computing, with a particular focus on healthcare applications such as heart stroke prediction models. Her publications have proposed innovative approaches that integrate clustering, classification, and deep learning techniques to enhance medical predictions, combining accuracy with practical applicability. Beyond healthcare, her work also explores security strategies in cloud computing and data-driven approaches to protect systems from vulnerabilities. This blend of healthcare informatics and cyber security positions her research at the intersection of technology and community impact.
Accolades and Recognition
Her expertise has been recognized through publications in reputed international journals such as Measurement: Sensors and Journal of Positive School Psychology, along with contributions to international conferences under IEEE. She has served as a reviewer for scholarly journals and academic book chapters, demonstrating her standing as a trusted evaluator in her field. Her involvement as an organizer of technical workshops, hackathons, and project expos reflects her commitment to academic innovation and student skill development, further reinforcing her recognition as a versatile academic leader.
Impact and Influence
The impact of Dr. Tigulla’s work is evident in both her research outcomes and her teaching contributions. Her models for heart stroke prediction contribute significantly to community health by combining artificial intelligence with real-world medical applications. As an educator, she has influenced generations of students by equipping them with knowledge in machine learning, artificial intelligence, and advanced computational concepts. Her leadership in academic events has fostered a culture of innovation, creativity, and hands-on learning among students, thereby extending her influence beyond traditional teaching.
Legacy and Future Contributions
Dr. Tigulla’s legacy is one of blending research excellence with community benefit. By focusing on both healthcare prediction models and system security, she has addressed two domains of immense social importance—public health and digital trust. Looking forward, her future contributions are expected to further deepen the integration of artificial intelligence into real-world applications, enhance her role as a reviewer and academic guide, and continue her efforts to shape students into innovative researchers and industry-ready professionals.
Publications
Article: Developing Heart Stroke Prediction Model using Deep Learning with Combination of Fixed Row Initial Centroid Method with Naïve Bayes, Decision Tree, and Artificial Neural Network
Authors: T. Swathi Priyadarshini, Vuppala Sukanya, Mohd Abdul Hameed
Journal: Measurement: Sensors
Year: 2024
Article: Collaboration of Clustering and Classification Techniques for Better Prediction of Severity of Heart Stroke using Deep Learning
Authors: T. Swathi Priyadarshini, Vuppala Sukanya, Mohd Abdul Hameed
Journal: Measurement: Sensors
Year: 2025
Article: Deep Learning Prediction Model for Predicting Heart Stroke using the Combination Sequential Row Method Integrated with Artificial Neural Network
Authors: T. Swathi Priyadarshini, Mohd Abdul Hameed, Balagadde Ssali Robert
Journal: Journal of Positive School Psychology
Year: 2022
Article: Methods of Hidden Pattern Usage in Cloud Computing Security Strategies with K-means Clustering
Authors: T. Swathi Priyadarshini, Dr. S. Ramachandram
Journal: AIJREAS
Year: 2021
Article: A Review on Security Issue Solving Methods in Public and Private Cloud Computing
Authors: T. Swathi Priyadarshini, S. Ramachandram
Journal: IJMTST
Year: 2020
Conclusion
Dr. Swathi Priyadarshini Tigulla embodies the qualities of an academician and researcher who successfully bridges the gap between theoretical advancements and community impact. Her journey, marked by academic rigor, extensive teaching experience, and impactful research, showcases her dedication to advancing artificial intelligence and machine learning for practical applications. Recognized as both a researcher and a mentor, she continues to inspire through her contributions in education, healthcare, and cyber security. In conclusion, her career highlights a sustained commitment to knowledge, innovation, and community-oriented research, establishing her as a distinguished academic voice in the field of computer science and engineering.