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Faculty Directory Debanjana Ghosh
Debanjana Ghosh

Debanjana Ghosh

Assistant Professor

[email protected]
Vidwan Profile Google Scholar

Academic Information

M.E, JU, 2018

Research Areas

Machine Learning Deep Learning Computer Vision

Research Interests

My research interests focus on the application of artificial intelligence and data-driven techniques to different fields like agritech, health etc. I am interested in machine vision, data acquisition from sensors and deep learning models for pattern recognition and classification on those data. I explore to develop practical, industry-relevant solutions that leading to publishable research with real-world impact in different sectors like agricultural quality assessment, sustainability, and intelligent decision-support systems.

Courses Taught

DBMS, Data Analytics, Digital Electronics, Software Engineering

Positions Held

Assistant Professor at Dept. of ECE, IEM Newtown, UEM Kolkata (2018-till date)
Associate system Engineer at IBM India (2015-16)

Publications

Ghosh, D., Das, D., Nag, S., & Roy, R. B. (2025). Online Monitoring of Phytochemical Dynamics in Black Tea Processing Using MIP-Driven Classifier Models. Chemometrics and Intelligent Laboratory Systems, 105611. Ghosh, D., Nag, S., Das, D., & Roy, R. B. (2024, June). Discrimination of Catechin and EGCG Through Various Tea Processing Stages Using Clustering Techniques. In International Conference on Advanced Computing and Systems (pp. 63-70). Singapore: Springer Nature Singapore. Ghosh, D., & Mukherjee, S. (2024). Machine learning in medical imaging: A comprehensive study. In Advances in Technological Innovations in Higher Education (pp. 42-50). CRC Press. Ghosh, S., Sur, S., & Ghosh, D. (2024). Lung Cancer Prediction Using Supervised Machine Learning. AJEC. Ghosh, D., Chatterjee, S., Kothari, V., Kumar, A., Nair, M., & Lokesh, E. (2019, March). An application of Li-Fi based wireless communication system using visible light communication. In 2019 International Conference on Opto-Electronics and Applied Optics (Optronix) (pp. 1-3). IEEE. Mullick, S., Singh, A. K., Shaw, A. K., Viswakarma, V., Kishan, M., & Ghosh, D. (2022). IoT based smart system to detect mental health emergencies: A proposed model. American Journal of Science & Engineering, 2(4), 18-21.