About

Vandita Patidar is a passionate and driven graduate student at Rensselaer Polytechnic Institute (RPI), majoring in Data Science and Analytics with a focus on Information Technology and Web Science. She is set to graduate in May 2022 with a Master's of Science degree. Vandita has a strong interest in analytics and enjoys using it to collect genuine information from data and build models around it. Vandita has gained valuable experience as an AI research extern at IBM, where she worked on improving LIME for business process automation. She has also worked with NASA on course projects to predict the impact of climate change on healthcare facilities using Python and R technologies. Vandita is highly skilled in Python, SQL, MongoDB, Seaborn, NodeJS, and AngularJS. Currently, Vandita works as a Graduate Teaching Assistant at RPI, where she manages and facilitates knowledge building of JS, NodeJS, Angular, MongoDB, SQL, HTML, and CSS in 50+ students during in-class sessions. She also ensures timely delivery of student grade books and provides constructive feedback. In her previous role as an AI Research Intern at IBM, Vandita gained knowledge about the previous work done by the research team and used new datasets to verify their work. She performed analysis and drew conclusions on new datasets using Python (Matplotlib, Seaborn) to gain insights and share findings with team members. She also iteratively evaluated various machine learning methods on new datasets to verify the research. Vandita has also worked as a Summer Intern at Scientech Technologies, where she built an intelligent street light system that leverages sensor data to operate street lights accordingly. She implemented a Zigbee network between street lights to communicate with each other and deployed the system in Indore as a part of the pilot project by Indore Municipal Corporation. This reduced energy consumption by 75%. Vandita is a highly skilled and motivated individual with relevant experience of 0.86 years. She looks forward to working as a full-time data scientist to utilize her skills to process, model, analyze, and draw conclusions from data to answer complex questions.