Ms. Gargi N
Ms. Gargi N
Assistant Professor, Department of Artificial Intelligence & Data Science
Academic Qualifications
  • Ph.D.: Pursuing, Deep Learning, VTU
  • Masters in Computer Science and Engineering, VTU
  • B.E. in Information Science & Engineering, VTU
Professional Summary
Ms. Gargi N is an Assistant Professor in the Department of Artificial Intelligence & Data Science at Global Academy of Technology, Bengaluru. She has over 10 years of teaching experience and is passionate about advancing knowledge in AI. Her subject specialization includes Data Visualization using Tableau and Power BI. She contributes to curriculum design, student mentoring, and engagement, effectively blending theoretical concepts with practical applications to build strong academic foundations and professional skills in students.
Research Interests & Expertise
  • Deep Learning
  • Artificial Intelligence & Data Science
  • Natural Language Processing
Selected Publications
  • Artificial Intelligence-Based Multi-Disease Prediction: An Ensemble Learning Perspective, Journal of Dalian University of Technology, Vol. 32, Issue 9, 2025 (Scopus – Q4). link
  • Evaluating E-Service Quality in Banking by Fuzzy AHP and Fuzzy TOPSIS Approach, Springer Book Chapter, 2025. link
  • City Power Generation and Optimization Using Fuzzy AHP and Fuzzy TOPSIS, Taylor & Francis, CRC Press, Book Chapter, 2024. link
  • A Comparison Between Fuzzy TOPSIS and AHP Methods for Intrusion Detection Selection, AIP Conf. Proc. 3278, 2025. link
  • Analysis of Factors Affecting Mental Illness and Social Stress in Young Adults Using Fuzzy TOPSIS and AHP Methods, AIP Conf. Proc. 3278, 2025. link
  • Smart Thyroid Diagnosis: A Machine Learning Based Interactive System, ICETCS 2024, IEEE, Scopus. link
  • Enhancing Password Security: Fuzzy AHP and TOPSIS-based Vulnerability Assessment, I2CT 2024, IEEE, Scopus. link
  • Enhancing Brain Tumour Detection and Classification: Comparative Analysis of Deep Learning ANN Models, ICIICS 2024, IEEE, Scopus. link
  • Blood Test Report-Based Prediction and Classification of Diseases Using Artificial Neural Networks, InCoWoCo 2024, IEEE, Scopus. link
  • Comparison of Various Computational Models for Accurate Stroke Prediction and Interpretation Using LIME and SHAP Kernels, InCoWoCo 2024, IEEE, Scopus. link
Patents
  • Artificial Intelligence Based Prediction of Kidney Injury Due to Drug Reaction, Patent Application No. 202141010368 A
Grants & Projects
  • Project: “Design and Development of Framework for Detecting Parkinson’s Disease Using Machine Learning” – Sponsored by KSCST (2020–2021), Grant: ₹3,000
  • Project: “IoT Based Smart Vehicle and Accident Prevention System” – Sponsored by KSCST (2017–2018), selected for State Level Project Exhibition, Grant: ₹5,000
Awards & Honors
  • Teacher of Excellence Award
Professional Memberships
  • IAENG
Contact Information