I am currently a research scholar in the in the Department of Computer Science and Engineering at the Indian Institute of Technology, Jodhpur. I am proficient in Python programming and have extensive knowledge of data science, machine learning, and artificial intelligence. My research is centered around digital well-being and healthcare applications, aiming to solve real-world problems.
I am developing a chatbot that utilizes artificial intelligence and natural language processing techniques to interact with users. It will collect relevant information and provide preliminary diagnoses for mental disorders. Creating and implementing this chatbot is based on the concept that people have a "Virtual Friend" who assists them in improving their mental well-being.
Utilizied wearable ECG technology to investigate stress levels during a modified Trier Social Stress Task (TSST), specifically a Mental Arithmetic Task (MAT) with varying difficulty levels.
Proposed a non-intrusive method for early detection of Social Anxiety Disorder (SAD) using speech pattern analysis, eliminating the need for clinical visits or video recordings. Leveraging short audio snippets, our approach provides a practical and accessible solution, especially suited for the digital age with widespread smart device use, offering a scalable tool for real-time anxiety prediction.
This research addresses the global mental health crisis by proposing an automated Mental State Examination summarization tool to aid mental health professionals in the early detection of mental illnesses. The tool, developed through fine-tuning large language models with psychological conversation data, generates concise summaries and shows superior performance in summarizing psychologist-participant interactions.