Ayushi Gaur
About Ayushi Gaur
Ayushi Gaur is a Data Science Intern with extensive experience in various roles, including a Health Benefits Data Analyst Intern at Segal and an LLM Engineering Assistant at the University of Illinois Chicago. She holds a PhD in Computer Science and has developed tools for suicide-ideation detection and machine learning model enhancements.
Work at CCC Intelligent Solutions
Currently, Ayushi Gaur serves as a Data Science Intern at CCC Intelligent Solutions, a company valued at $7 billion. She has been in this role since 2024, working remotely for a duration of 8 months. In her position, she is involved in creating an LLM-based Online Analytical Processing (OLAP) system aimed at enhancing the querying capabilities of machine learning models.
Current Role at University of Illinois Chicago
Ayushi Gaur is also employed as an LLM Engineering Assistant at the University of Illinois Chicago. She has held this position since 2023, working on-site for a year. Her responsibilities include supporting projects that leverage large language models in various applications.
Previous Experience in Data Science and Machine Learning
Prior to her current roles, Ayushi Gaur gained experience as a Data Science Intern at Schneider Electric for one month in 2023. She also worked as a Data Science Assistant at the University of Illinois Chicago for three months in 2022. Additionally, she served as a Research Collaborator at the Computer Vision Research Society from 2021 to 2022.
Educational Background
Ayushi Gaur holds a Doctor of Philosophy (PhD) in Computer Science from the Birla Institute of Technology and Science, Pilani, which she completed from 2019 to 2021. She also earned a Master of Science in Business Analytics from the University of Illinois Chicago in 2023. Her undergraduate studies were completed at Banasthali Vidyapith, where she received a Bachelor's degree in Computer Science from 2014 to 2018.
Projects and Innovations
During her tenure at UI Health, Ayushi Gaur developed MindWatch, a web tool utilizing BERT and OpenAI technologies for suicide ideation detection. This project showcases her ability to apply machine learning techniques to real-world problems. She specializes in designing end-to-end machine learning pipelines and extracting insights from complex datasets.