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Academic Experts
Jyoti Singh

Biography

Jyoti Singh is currently working as an Assistant Professor (Grade II) in the Department of Computer Science Engineering & Information Technology at Jaypee Institute of Information Technology (JIIT), Noida. She holds a B.Tech. degree in Computer Science from University of Delhi (DU), and M.Tech. degree in Computer Science and Engineering (CSE) from University School of Information, Communication & Technology (USIC&T), Guru Gobind Singh Indraprastha University (GGSIPU), New Delhi. She is currently pursuing Ph.D. degree (CSE) from USIC&T, GGSIPU, New Delhi, and is a recipient of prestigious AICTE Doctoral fellowship (ADF) scheme during PhD.

With over four years of academic experience, she has taught a wide range ofcourses at the undergraduate and postgraduate levels, including Theory of Computation, Operating Systems, Programming in Python, and Advanced Database Management Systems, Advance Business Analytics & Predictive Learning, Compiler Design.

Research Highlights

Her research is centered around handling incomplete data and improving data quality, particularly in medical and healthcare datasets. Her work focuses on developing intelligent, machine learning-based approaches that enhance the reliability and accuracy of incomplete data by leveraging concepts from fuzzy clustering, soft computing, and machine learning. She has authored two book chapters and presented her papers at various international conferences. Her research has been recognized internationally, including receiving the Best Paper Award at an international conference on data analytics and management. She has reviewed 20+ SCI/ SCIE indexedjournals in various fields related to computer science .

Beyond her core work in data imputation, her broader research interests include Artificial Intelligence, Machine Learning, Data Analytics, Cyber Security, and Theoretical Computer Science. Her research bridges the gap between data science theory and real-world challenges, especially in domains where data incompleteness and uncertainty pose significant obstacles.

She remains committed to integrating emerging technologies into education and research to foster innovation,interdisciplinary thinking, and ethical AI adoption. Her ongoing work aims to develop robust, interpretable,and application-oriented solutions that support effective decision-making in complex, data-driven environments.

Areas of Interest
  • Applications ofMachine Learning
  • Data Analytics and Data mining
  • Fuzzy clustering
  • AI & ML
  • Deep learning
Publications
  • Jyoti Singh, Jaspreeti Singh, Anjana Gosain. Enhancing Medical Data Imputation using an Iterative K-Nearest Neighbor-based Kernelized Fuzzy c-means Hybrid Imputation Method, Discover Computing, vol 29, No 9 (SCIE Index, Scopus Index) https://doi.org/10.1007/s10791-025-09889-4
  • Jyoti Singh, Jaspreeti Singh, Anjana Gosain. (2025) Revolutionizing Medical Data Quality with DKFCM-𝜎: Density-Oriented Kernelized Fuzzy C-means Sigma Imputation Approach, Engineering Research Express, vol 7, No 4 (ESCI Index, Scopus Index) https://doi.org/10.1088/2631-8695/ae1945
  • Jyoti, J. Singh, and A. Gosain, “Revolutionizing Missing Data Handling with RFKFCM: Random Forest-Based Kernelized Fuzzy C-Means”, Procedia Computer Science 233 (2024): 66-76 https://doi.org/10.1016/j.procs.2024.03.196 (Scopus)
  • Jyoti, J. Singh, and Anjana Gosain, “Handling Missing Values Using Fuzzy Clustering: A Review,” Advances in intelligent systems and computing, pp. 341–353, June. 2023, doi: https://doi.org/10.1007/978-981-99-0550-8_28
  • Jyoti, J. Singh, and Anjana Gosain, “LIPFCM: Linear Interpolation-Based Possibilistic Fuzzy C-Means Clustering Imputation Method for Handling Incomplete Data,” Lecture notes in networks and systems, pp. 87–99, Dec. 2023, doi: https://doi.org/10.1007/978-981-99-6553-3_7.
  • Jyoti, J. Singh, and A. Gosain, “Revolutionizing Missing Data Handling with RFKFCM: Random Forest-Based Kernelized Fuzzy C-Means”, 5th International Conference on Innovative Data Communication Technologies and Application (ICIDCA 2024)