Research Projects

Ground Water Quality Assessment using ML and Clustering

Research on assessment of ground water quality parameters using clustering algorithms and machine learning approaches. Presented at International Conference on Application of Civil Engineering in Agriculture (ACEA 2025) at IIEST Shivpur.

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Brain Tissue Segmentation using AI/ML Techniques

Research on brain tissue segmentation and classification in infant MRI images using advanced techniques including Seeded Region Growing, Foster Corner Detection Theory, and Sparse Autoencoder. Published in Alexandria Engineering Journal (Impact Factor: 6.8).

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IoT Based Image Processing System for Medical Applications

Development of an IoT-based image processing system for medical applications, combining embedded systems with advanced image processing algorithms for healthcare automation.

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Microarray Gene Expression Analysis using Machine Learning

Ph.D. research focusing on cancer gene recognition from microarray data using advanced machine learning techniques including Manta Ray optimization, ANFIS, and fuzzy clustering methods. This research has resulted in multiple publications in high-impact SCI journals including Elsevier and Springer.

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Electronic Nose Monitoring and Evaluation System

Research on monitoring and evaluating the operation of electronic noses for various sensing applications.

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Signal Processing Applications in Biomedical Engineering

Ongoing research exploring advanced signal processing techniques for biomedical applications including EMG signal analysis, ECG heart rate detection, PPG signal processing, and biosignal denoising using wavelet-based methods.

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