I'm good at presenting my idea and in Machine learning. Challenges and to learn something new everyday drives me. My final year project on analysising EEG data and applying ML algorithm on it to make relationship between stress levels and music genre that can soothe was one of my co Plex projects. The project was an end to end project where even the data collection was done by us, we had to build a standardized data collection pipeline and then perform our data collection experiment on 10 subjects both male and female. Data collection was still okay, most complex part was the data cleaning process since EEG is such a sensitive signal. In fact being an engineer I had no idea about EEG signals, so initial months went in just learning about EEG signals. Definitely this project made me learn so many things like it is worth it spending long hours on data pre processing and dimensionality reduction task before jumping into applying any machine learning model that can produce good results. Also because it was a team project, the whole team had to decide on the standard data cleaning up process and distribute the task such that each step is in line with the other. This project also taught me the value of working in a team and how to deal with conflicting ideas.
I'm a staunch supporter of women in technology and I myself am a part of Women in data science Mumbai team and have been running the chapter for 2 years now. On the other hand I love participating in hackathons, and it's been quite a few months that I haven't participated in one, since I got busy with my job. With this hackathon I hope to resume my Hackathon spree.
I got selected as a technology graduate in the credit risk IT department in UBS Business Solutions centre. My work involves dealing with firms dealing credit Risk data and perform the task similar to data ETL process that meets the business requirements in compliance with BCBS 239 regulations. Technology stack I use everyday is java, PL/SQL, Unix, git.