I have submitted my Ph.D. in the Department of Mechanical Engineering at IIT Kharagpur, under the supervision of Prof. Amiya Ranjan Mohanty. My doctoral research focuses on Vibration Based Data Driven Activity Identification and Tracking of Mining Dumpers, with the broader aim of developing a framework for vibration condition monitoring. My work integrates a custom-developed data acquisition system with machine learning and deep learning techniques to identify and track the activities of the dumpers and later implements these activities to monitor health. 

I have published research papers in reputed international journals, like Automation in Construction, and co-authored publications. I have also presented my work at prestigious international conferences, including the ASME International Mechanical Engineering Congress & Exposition and the World Congress on Engineering Asset Management. I have also filed a patent in India for my doctoral research. I have also been awarded the Government of India ANRF International Travel Support to attend the ASME-IMECE 2025, where I have served as a Session Chair for Track 15: Safety Engineering, Risk and Reliability Analysis, Session: Reliability and Safety in Transportation Systems.

I have developed expertise and hands-on experience in industrial practices, field data collection, data handling, data-driven modeling, and practical, deployable solutions. Through these learnings, I have contributed significantly to various industry-oriented projects. Along with that, my team's academic project, “Innovative Product Design for Real-time Fault Diagnosis and Prognosis of Electric Motor and Gearbox in Electric Vehicle,” has been selected as the Second Winner for the Aruna & Ram Gopal Khandelia Innovation Award at IIT Kharagpur. 

I have served as a Teaching Assistant for the NPTEL course “Machinery Fault Diagnosis and Signal Processing”, and actively supported departmental teaching in courses such as Machine Design, Machine Drawing, Material Testing Lab, and Mechatronics Lab. 

With expertise in industry-oriented product development, a foundation in data collection, signal processing, machine learning, and condition monitoring, and demonstrated teaching potential, I am committed to contributing innovative research and practical solutions in mechanical systems, IoT, and intelligent monitoring.