Faculty Directory Dr. Jayati Mukherjee
Dr. Jayati Mukherjee

Dr. Jayati Mukherjee

Associate Professor

Academic Information

Ph. D., Visva- Bharati, 2023

Research Interests

My research interests focus on Machine Learning, Pattern Recognition, and Image Processing, with an emphasis on designing intelligent models for data-driven analysis and decision-making. I work on developing and optimizing supervised and unsupervised learning algorithms to extract meaningful patterns from complex datasets. My interests include feature extraction, classification, and predictive modeling, as well as image enhancement, segmentation, and visual analysis. I am particularly interested in integrating machine learning and deep learning techniques for image-based applications such as object recognition and medical image analysis, aiming to develop robust, efficient, and scalable intelligent systems.

Courses Taught

Artificial Intelligence and Machine Learning, Data Science, Data Analytics

Positions Held

Associate Professor, University of Engineering and Management
Assistant Professor, Noida International University
Research Associate, Indian Statistical Institute

Publications

1 J. Mukherjee, S. Mishra, A. Tomar, and V. Kumar, “A low-cost hybrid handwritten devanagari character classifier(esci,scopus),” Innovations in Systems and Software Engineering, vol. 21, no. 1, pp. 237–245, 2025.

2 S. Mukhopadhyay, J. Mukherjee, D. Das, et al., “Learning fuzzy decision trees for predicting outcomes of legal cases relating to intellectual property rights(scie,scopus),” Applied Soft Computing, p. 113 179, 2025.

3 J. Mukherjee, “A deep neural network based holistic approach for optical character recognition of handwritten documents(scopus),” SN Computer Science, vol. 5, no. 4, p. 347, 2024.

4 J. Mukherjee and U. Roy, “A low resource multi lingual simultaneous script identification and text recognition model(scopus),” SN Computer Science, vol. 5, no. 6, p. 740, 2024.

 5 N. Sharma, Shanmuganathan, U. Garg, J. Mukherjee, and S. Mishra, “Analysis of student’s academic performance based on their time spent on extra-curricular activities using machine learning techniques” International Journal of modern education and computer science (Scopus), vol. 15, no. 1, pp. 46–57, 2023.

 6 P. Kumar, S. Mishra, M. Kumar, A. Tomar, and J. Mukherjee, “Security of internet of things of application, challenges and related future technologies,” Gradiva Review Journal(UGC), vol. 8, no. 06, pp. 392–408, 2022.

7 J.Mukherjee, S. K. Parui, and U. Roy, “An unsupervised and robust line and word segmentation method for handwritten and degraded printed document,” ACM Trans. Asian Low-Resour. Lang. Inf. Process.(SCIE, Scopus), vol. 21, no. 2, Oct. 2021, issn: 2375-4699. doi: 10.1145/3474118.

 8 J. Mukherjee, S. K. Parui, and U. Roy, “NN-based analytic approach to symbol level recognition for degraded Bengali printed documents,” S¯adhan¯a (SCIE, Scopus), Springer, vol. 45, no. 1, pp. 1–22, 2020.

 9 J. Mukherjee, S. Parui, and U. Roy, “Degraded Bangla character recognition by k-NN classifier,” International Journal of Computer Sciences and Engineering (UGC approved journal no- 63193), vol. 7, no. 01, pp. 42–47, 2019.

10 J. Mukherjee and U. Roy, “Recognition of degraded Bangla documents using hybrid deep neural network model,” in 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), IEEE, 2021, pp. 254–259.