Bhavi D.

I am a Computer Engineering student graduating in June 2022. I am passionate about working in the Deep Learning & Machine Learning domains and will be pursuing a master's degree in the field in Fall 2022. I believe my interests, experience, and willingness to learn new things make me a deserving candidate. I have detailed my experience below. I would be happy to connect to clarify any concerns! INTERNSHIP EXPERIENCE Company: Avail Finance, Bangalore, India. Dates: September 2021 to Present Title: Data Science Intern Details: Working on creating a features on bureau scrub pulls in order to improve the classification AUC of Risk underwriting models Modelled the customer base and their mutual connections as a directional graph and performed Page Rank analysis to segment users for targeted marketing. The segment posited to be the best performed 5x better than the previous average. University: Indian Institute of Technology (IIT), Gandhinagar, India. Dates: June 2021 to August 2021 Title: Summer Student Research Intern Details: Built a pipeline for predicting properties of Additively Manufactured Aluminium and Titanium alloys using Artificial Neural Network architectures. Curated a dataset of relevant manufacturing process parameters and corresponding alloy properties from domain literature. Company: Minedbytes Technologies, Mumbai, India. Dates: July 2020 to November 2020 Title: Machine Learning Intern Details: Designed a pipeline that scrapes Instagram data from brand accounts and Implemented the PCD algorithm to rank and classify the posts into corresponding business verticals. Created an ensemble model to perform sentiment analysis and predict an engagement score for Instagram brand posts using Vader sentiment analysis, the Emot library, and the Google cloud vision API. Company: Intech, IDBI Bank, Mumbai, India. Dates: June 2020 to July 2020 Title: Student Summer Intern Details: Developed a prototype that detects faces, recognizes known customers, and analyses 7 emotions from video footage to gauge customer satisfaction using a custom Convolutional Neural Network. HACKATHON WINS & PROJECTS 1. ‘Best Data Science Hack’ at MacHacks Hackathon, McMaster University, Canada. Details: Built a web application that auto generates relevant text summaries for video lectures by using Silero Speech-To-Text models and NLP models built on top of BERT. 2. Won Prize at Hackytics hackathon, Georgia Tech, USA. Details: Built a chrome extension that uses NLP models to get the probability score of a news article being fake and gets alternative sources for fake articles.