The applications of machine learning are numerous, and it has the potential to improve many aspects of our lives, such as making transportation safer, increasing crop yields, and improving the efficiency of healthcare systems. All these reasons make machine learning application research exciting, as it helps to drive progress and innovation in a wide range of fields, and has the potential to improve many aspects of our lives, while also making sure that the models developed are robust, fair, and explainable.



Research Projects


  1. Bengali Document Clustering: A Comprehensive Study of K-means, K-means++, Spectral K means [Accepted at ICACIE 2022, Springer]

  • Collaborated with Prof. Kamal Sarkar and Dr. Chintan Mandal, Jadavpur University, India.

  • Implemented state-of-the-art clustering algorithms for Bengali document clustering

  1. Ensemble Of CNN Models For Detecting COVID-19 From Chest X-ray Images (Ongoing)

  • Collaborating with Prof. Kamal Sarkar, Jadavpur University, India

  • Focused on developing an ensemble method which would be more effective than standard ensemble methods such as majority voting, product rule and sum rule

  1. Improving K-means with the Help of Geometric Tool

  • Worked with Prof. Kamal Sarkar and Dr. Chintan Mandal, Jadavpur University, India.

  • Utilized the Voronoi Diagram and ‘max of min’ concept to efficiently find the centroids of k-means.

  1. Source Localization Problem [Final Year Thesis]

  • Undertaken in association with Dr. Chintan Mandal, and Dr. Chandreyee Chowdhury, Jadavpur University, India.

  • The problems of locating a radiating source from range measurements or from range-difference measurements collected using a network (or array) of passive sensors have received