About
Dr. Rajnish Kumar Ranjan is a researcher specializing in Artificial Intelligence and currently serves as a Senior Lecturer in the Department of Computer Science and Engineering at the Government Women's Polytechnic College, Bhopal, India. He completed his Ph.D. in Computer Science and Engineering from LNCT University, Bhopal, focusing on the development of ensemble learning models for the early detection of neurodegenerative disorders. He obtained his M.Tech. from the Indian Institute of Information Technology (IIIT) Allahabad and his B.Tech. from the Heritage Institute of Technology, Kolkata.
His research interests encompass Artificial Intelligence, Machine Learning, Deep Learning, Medical Image Analysis, Computer Vision, Explainable AI, and Healthcare Informatics, with a specific emphasis on AI-based diagnosis of conditions such as Alzheimer's and Parkinson's diseases. His doctoral research resulted in the development of two novel ensemble learning frameworks for analyzing neurodegenerative diseases, based on robust, interpretable, and computationally efficient predictive models.
Dr. Ranjan has authored 16 research publications in Scopus-indexed journals, Springer conference proceedings, and IEEE conferences. Beyond academic research, he possesses over a decade of teaching experience and has actively participated in curriculum development, academic mentoring, and faculty development initiatives. His long-term research vision is to develop intelligent, explainable, and clinically implementable AI systems that can facilitate early diagnosis and personalized healthcare.
Employment
-
LNCT University School of Management
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (4)
- Advancing Voice-based Parkinson's Detection with Hybrid XGBoost-LightGBM Models Save
- Dementia and Its Subtypes: A Statistical Review Save
- A Statistical Study of Lewy Body and Other Types of Dementia Save
- IoT and Machine Learning-Based Covid-19 Healthcare Monitoring System Using Face Recognition Save