Ureshii recommends activities to improve one's mental wellbeing. Ureshii does this by making use of a clinical psychology inspired questionnaire and a machine learning algorithm, programmed by me. The machine learning algorithm uses user profiles and data to categorize them in clusters. This process is known as clustering. The recommender system algorithm uses the clusters to recommend similar activities to users in the same cluster. This maximizes the accuracy of the activities being recommended to the users and ensures that they will enjoy and profit off of the activities they are being recommended. These algorithms allow us to use BAT or behavioral activation therapy over an online software to help improve user’s mental wellbeing.

At 221B-Analytics I worked on creating dashboards, implementing machine learning in the form of prediction and regression, and working on social media by creating advertisements.

Worked on multiple research projects with various students and professors in India, specifically physics and engineering projects, some of which I co-authored

Developing the Karya AI Whatsapp Bot to help move 100 million people out of extreme poverty by 2030.