Dr. Priyadharshini Vadivel Muthurathinam | Information Technology | Best Researcher Award

Dr. Priyadharshini Vadivel Muthurathinam | Information Technology | Best Researcher Award

Dr. Priyadharshini Vadivel Muthurathinam , BIT Campus, India

Dr. V.M. Priyadharshini is a seasoned academician with over 20 years of experience in Information Technology πŸŽ“πŸ’». Currently serving as an Assistant Professor (Selection Grade) at AUBIT, she holds a Ph.D. in Information Technology and specializes in Social Network Analysis 🌐. Her contributions span across intelligent systems, geospatial applications, and privacy-preserving frameworks, reflecting her commitment to impactful, interdisciplinary research πŸ”πŸ“Š. With numerous publications in reputed international journals and conferences, she continuously explores innovative solutions for modern-day digital challenges πŸš€πŸ“‘. Dr. Priyadharshini also mentors budding researchers while actively contributing to technological advancement in academia πŸ§‘β€πŸ”¬πŸ“š.

Professional Profile:

Orcid

Suitability Of Best Researcher Award

Dr. V.M. Priyadharshini is an exemplary candidate for the Best Researcher Award based on her outstanding academic contributions, interdisciplinary research, and commitment to addressing pressing digital challenges. With over two decades of experience in Information Technology, Dr. Priyadharshini has developed a strong academic and professional profile, which includes notable achievements in Social Network Analysis (SNA), geospatial data analysis, and privacy-preserving frameworks.

πŸŽ“ Education and ExperienceΒ 

  • πŸŽ“ B.Tech in Information Technology

  • πŸŽ“ M.Tech in Information Technology

  • πŸŽ“ Ph.D. in Information Technology

  • πŸ§‘β€πŸ« Assistant Professor (Selection Grade) – Department of IT, AUBIT

  • πŸ—“οΈ 20 Years of Professional Experience in academia and research

πŸ“ˆ Professional Development

Dr. Priyadharshini has consistently enhanced her academic and research profile through active participation in scholarly publications and technology forums πŸ“˜πŸ§ . Her recent works in geospatial data analysis, machine learning, and spam detection in online networks exemplify her engagement with real-world challenges through a research lens πŸŒπŸ€–. She collaborates with peers across disciplines and contributes to conferences and workshops on privacy, cyber safety, and AI applications πŸ›‘οΈπŸ§‘β€πŸ’Ό. By integrating teaching and research, she ensures students stay updated with emerging trends while fostering innovation in the field of information technology πŸŽ―πŸ“‘.

πŸ”¬ Research Focus Category

Dr. Priyadharshini’s primary research lies in Social Network Analysis (SNA) and its applications in cyber-security and intelligent systems πŸŒπŸ”. Her work involves analyzing complex user behaviors, detecting malicious profiles, and safeguarding digital communication through adaptive frameworks πŸ’¬πŸ§ . She also delves into machine learning, spam detection, and geospatial risk assessment, bringing a multi-disciplinary approach to digital and environmental data analytics πŸŒŽπŸ“Š. Through applied computational models, she seeks to solve pressing issues in privacy protection, digital pollution monitoring, and smart data processing, pushing the envelope in IT-enabled societal resilience πŸ“‘πŸ§¬.

πŸ† Awards and HonorsΒ 

  • πŸ… Published in high-impact international journals such as ScienceDirect, Springer, and IOS Press

  • πŸ“– Recognized contributor to IEEE Conferences and Proceedings

  • 🌟 Reputed faculty at AUBIT with 20 years of teaching and research excellence

  • πŸ§ͺ Lead researcher in government-funded academic projects

Publication Top Notes:

Title: Adaptive Framework for Privacy Preserving in Online Social Networks
Journal: Wireless Personal Communications
Publication Date: December 20, 2021
DOI: 10.1007/s11277-021-08822-4
Authors: V. M. Priyadharshini, A. Valarmathi

πŸ” Summary in Simple Terms:

This research addresses the growing concern of privacy in online social networks (OSNs) like Facebook, Twitter, and Instagram. The authors propose an adaptive privacy-preserving framework that helps users control how much and what kind of personal information is shared with others.