Haldia Institute of Technology

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Departments Electrical Engineering Dr. Debasis Maji

Dr. Debasis Maji

Assistant Professor

Electrical Engineering

Email LinkedIn Scholar ORCID

Dr. Debasis Maji

Assistant Professor

Electrical Engineering

Email LinkedIn Scholar ORCID

Quick Stats

7 yrsTeaching

—Industry

29Papers

5Journals

1PhD

1M.Tech

Contact & Info

hitdebasis@gmail.com

Phone

7980681378

Qualification

Ph.D.

Specialization

Control System

Patents

Google Scholar ORCID LinkedIn ResearchGate Vidwan

About Debasis Maji

is a young and dynamic individual with a strong academic background in Electrical Engineering . Currently working as an Assistant Professor in the Department of Electrical Engineering, Haldia Institute of Technology, Halide. He is passionate about research, believes in learning, striving for enhancing skills. Currently, he has expertise in developing computer-aided diagnosis system and content-based image retrieval system for clinical assistance. He received Ph.D. from Jadavpur University, India in 2024. He has 7+ years of teaching experience. His research findings have been published in SCIE/Google-indexed international journals. He has attended and presented many research articles at international conferences. He is also a part of funded projects and patent.

Current Research Projects

Prevalence of Diabetic Retinopathy and its Associated Factors in a Rural Area Based on Deep 3 years MSME 15 lakhs IDEAWB005530 Dr.Debasis Maji

Research Scholars Guided

1PhD Current

1M.Tech

Publications & Patents

29Total

5Journals

23Conferences

2Chapters

1Books

Research Interests

My research interests focus on the development and application of advanced techniques in Artificial IntelligenceImage Processingand Deep Learningwith a strong emphasis on Biomedical Image Analysis. I am particularly interested in designing intelligent algorithms for image enhancementsegmentationfeature extractionand pattern recognition using machine learning and deep neural networks. A major part of my research involves applying convolutional neural networks (CNNs)transfer learningand hybrid AI models to analyze biomedical images such as X-raysMRICT scansand histopathological images. The goal is to improve accuracyefficiencyand reliability in disease detectiondiagnosisand prognosis. I am also interested in explainable AI and model interpretability to ensure transparency and trust in medical decision-support systems. Through interdisciplinary researchI aim to bridge the gap between theoretical AI models and real-world healthcare applicationscontributing to intelligentautomatedand clinically relevant diagnostic solutions.

Editorial Boards

Biomedical Signal Processing and Control(reviewer)

Courses Currently Teaching

Basic Electrical and Electronic Engineering

Control Systems

Digital Control Systems

Digital Electronics

Artificial Intelligence

Sensors and Transducers