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

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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 🎓💻. 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 🔍📊. With numerous publications in reputed international journals and conferences, she continuously explores innovative solutions for modern-day digital challenges 🚀📡. Dr. Priyadharshini also mentors budding researchers while actively contributing to technological advancement in academia 🧑‍🔬📚.

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.

🎓 Education and Experience 

  • 🎓 B.Tech in Information Technology

  • 🎓 M.Tech in Information Technology

  • 🎓 Ph.D. in Information Technology

  • 🧑‍🏫 Assistant Professor (Selection Grade) – Department of IT, AUBIT

  • 🗓️ 20 Years of Professional Experience in academia and research

📈 Professional Development

Dr. Priyadharshini has consistently enhanced her academic and research profile through active participation in scholarly publications and technology forums 📘🧠. 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 🌍🤖. She collaborates with peers across disciplines and contributes to conferences and workshops on privacy, cyber safety, and AI applications 🛡️🧑‍💼. By integrating teaching and research, she ensures students stay updated with emerging trends while fostering innovation in the field of information technology 🎯📡.

🔬 Research Focus Category

Dr. Priyadharshini’s primary research lies in Social Network Analysis (SNA) and its applications in cyber-security and intelligent systems 🌐🔐. Her work involves analyzing complex user behaviors, detecting malicious profiles, and safeguarding digital communication through adaptive frameworks 💬🧠. She also delves into machine learning, spam detection, and geospatial risk assessment, bringing a multi-disciplinary approach to digital and environmental data analytics 🌎📊. 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 📡🧬.

🏆 Awards and Honors 

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

  • 📖 Recognized contributor to IEEE Conferences and Proceedings

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

  • 🧪 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

🔍 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.

Touraj BaniRostam | Big Data | Best Researcher Award

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Assist. Prof. Dr. Touraj BaniRostam | Big Data | Best Researcher Award

Assistant Professor at University of Niagara Falls Canada, Canada📖

Dr. Touraj BaniRostam is a seasoned Computer Science and Artificial Intelligence (AI) expert with extensive academic and industry experience. Holding a Ph.D. in Computer Science, he is currently a Full-Time Faculty Member and Assistant Professor at the University of Niagara Falls, Canada. With a strong focus on AI, machine learning (ML), data analytics, and intelligent autonomous agents, Dr. BaniRostam is committed to advancing the fields of AI, cognitive science, and philosophy of AI. He has significantly contributed to the academic community, having supervised over 85 master’s and 5 Ph.D. students and published various impactful research works in AI, machine learning, cognitive science, and multi-agent systems.

Profile

Scopus Profile

Google Scholar Profile

Education Background🎓

  • Ph.D. in Computer Science – Science and Research Branch, Islamic Azad University, Tehran, Iran (Sep. 2006 – Sep. 2011)
  • M.Sc. in Philosophy of Science – Science and Research Branch, Islamic Azad University, Tehran, Iran (Sep. 2016 – Sep. 2019)
  • M.A. in Psychology – Islamic Azad University, Tehran, Iran (Feb. 2014 – Sep. 2016)
  • M.Sc. in Artificial Intelligence – Science and Research Branch, Islamic Azad University, Tehran, Iran (Sep. 2001 – Sep. 2004)
  • B.Sc. in Computer Hardware – Islamic Azad University, Central Tehran Branch, Tehran, Iran (Sep. 1996 – Jul. 2000)

Professional Experience🌱

1. University of Niagara Falls, Canada

  • Full-Time Faculty Member & Assistant Professor (May 2024 – Present)
    • Data Analytics, Medical Computing, and Data Visualization
    • Teaching various courses related to data analytics, business intelligence, and medical & scientific computing.

2. International Business University (IBU), Toronto, Canada

  • Lecturer (Adjunct Professor) (Jan 2024 – Present)
    • Courses: Business Analytics, Technology Literacy, and Digital Transformation, including cloud computing, AI & machine learning, and cybersecurity compliance.

3. Georgian College, Barrie Campus, Canada

  • Lecturer (Part-Time) (May 2023 – Present)
    • Courses: Reinforcement Learning, System Vision, and Conversational AI.

4. Humber College, Toronto, Canada

  • Lecturer (Part-Time) (Jan 2024 – Aug 2024)
    • Emerging Technologies in AI, Generative AI, and Quantum Computing.

5. Durham College, Oshawa, Canada

  • Lecturer (Part-Time) (Jan 2024 – May 2024)
    • AI Algorithms and teaching various machine learning techniques such as supervised, unsupervised learning, and ensemble methods.

6. DAPCCO, Toronto, Canada

  • Research Manager (Part-Time) (Apr 2023 – Apr 2024)
    • Research on AI for intelligent waterproofing estimation, including machine learning, data mining, and deep neural networks.

7. Islamic Azad University, Tehran, Iran

  • Faculty Member & Assistant Professor (Feb 2007 – Feb 2023)
    • Taught courses on machine learning, business intelligence, intelligent decision support systems, and supervised numerous student theses in AI, data mining, and big data.

8. Islamic Azad University, Central Organization, Tehran, Iran

  • Vice Chancellor of Science and Engineering (Jun 2022 – Feb 2023)
    • Led the development of AI curricula and served as a policy advisor for AI development across the university system.
Research Interests🔬

Her research interests include:

  • Artificial Intelligence & Machine Learning: Development of intelligent systems, deep learning, and autonomous agents.
  • Data Science & Analytics: Applications of data mining, predictive modeling, and business intelligence.
  • Cognitive Science & Philosophy of AI: Exploring human cognition and decision-making through AI and cognitive models.
  • Multi-Agent Systems: Designing and analyzing autonomous agents in distributed systems.
  • Medical AI: Applications of AI in healthcare, including disease prediction and diagnostics.

Author Metrics

  1. Publications:
    • Published in journals such as PLOS One, SN Computer Science, BMC Bioinformatics, and presented at IEEE conferences such as ICASSP and CONECCT.
    • Notable papers on AI for medical diagnostics and autonomous vehicles.
  2. Supervision:
    • Successfully supervised 85 master’s and 5 Ph.D. students, with a focus on AI and machine learning in diverse applications.
Awards and Honors
  1. Full Scholarship for Ph.D. – Awarded based on academic excellence and research contributions.
  2. Rank 1 in Visvesvaraya PhD Fellowship Entrance Test (2024) – Kalinga Institute of Industrial Technology, MeitY (Govt. of India).
  3. Qualified GATE (2022) – Computer Science & Information Technology.
  4. Qualified JEE (2018) – Secured admission in IIIT Gwalior.
Publications Top Notes 📄

1. Classification of Pima Indian Diabetes Dataset using Ensemble of Decision Tree, Logistic Regression, and Neural Network

  • Authors: M. Abedini, A. Bijari, T. Banirostam
  • Journal: International Journal of Advanced Research in Computer and Communication Engineering
  • Year: 2020
  • Citations: 37
  • Summary: This paper presents an ensemble approach combining decision tree, logistic regression, and neural network for classifying the Pima Indian Diabetes Dataset, improving prediction accuracy and robustness in medical data analysis.

2. Resolving Cold Start and Sparse Data Challenge in Recommender Systems using Multi-Level Singular Value Decomposition

  • Authors: K.V. Rodpysh, S.J. Mirabedini, T. Banirostam
  • Journal: Computers & Electrical Engineering
  • Volume: 94
  • Article: 107361
  • Year: 2021
  • Citations: 23
  • Summary: This research addresses the cold start and sparse data challenges in recommender systems, utilizing multi-level singular value decomposition to enhance system performance and recommendation accuracy in real-time applications.

3. Design, Modeling and Experimental Analysis of Wheeled Mobile Robot

  • Authors: M.H. Korayem, T. Banirostam
  • Conference: 3rd IFAC Symposium on Mechatronic Systems
  • Pages: 629-634
  • Year: 2004
  • Citations: 23
  • Summary: The paper presents the design, modeling, and experimental analysis of a wheeled mobile robot, with a focus on the integration of mechatronic systems for autonomous robotic applications.

4. Employing Singular Value Decomposition and Similarity Criteria for Alleviating Cold Start and Sparse Data in Context-Aware Recommender Systems

  • Authors: K.V. Rodpysh, S.J. Mirabedini, T. Banirostam
  • Journal: Electronic Commerce Research
  • Volume: 23, Issue 2
  • Pages: 681-707
  • Year: 2023
  • Citations: 19
  • Summary: This paper further builds upon the cold start issue in context-aware recommender systems, applying singular value decomposition and similarity criteria to address data sparsity and improve recommendation accuracy.

5. Functional Control of Users by Biometric Behavior Features in Cloud Computing

  • Authors: H. Banirostam, E. Shamsinezhad, T. Banirostam
  • Conference: Intelligent Systems Modeling & Simulation (ISMS-IEEE)
  • Year: 2013
  • Citations: 19
  • Summary: This study explores the use of biometric behavior features to provide functional control of users in cloud computing environments, enhancing security and user authentication in distributed systems.

Conclusion

Dr. Touraj BaniRostam is a highly deserving candidate for the Best Researcher Award. His exceptional academic track record, contributions to AI and machine learning, leadership in educational curricula development, and impactful research in fields such as healthcare AI, autonomous systems, and data science make him a leading figure in the field. Expanding his efforts to industry collaborations, increasing his participation in global conferences, and focusing on scalability and commercialization will further solidify his impact on the global research and technology landscape.