Aravind Chakrahari

Led an AI project to extract metadata from 30,000 AT&T contract documents using the Llama 3.2 model, significantly enhancing accuracy and processing speed. Collaborated with cross-functional teams to develop and implement a structured workflow for contract data management and built scalable applications with LLMs using frameworks like LangChain and LlamaIndex.

Designed and implemented an interactive visual questionnaire to collect customer preferences, applying cognitive and behavioral theories to inform its design. Identified opportunities for product improvement based on data-driven insights, leading to a 30% boost in customer satisfaction. Built a data pipeline for a forecasting model to predict product demand, successfully reducing dependency on tra

Conducted a study to investigate temporal accuracy and precision across blocks in the Discrimination and Bisection Task, focusing on how temporal sensitivity varies throughout the task. Designed and executed experiments to examine participants' temporal accuracy and precision during the task, analyzing data to identify patterns and insights related to temporal processing mechanisms.

Collaborated with clients, including Walmart and Dr. Lal Path Labs, to gather requirements and understand needs for product configuration. Utilized JavaScript to configure and customize software products, ensuring alignment with client specifications and enhancing functionality. Engaged in effective client communication to clarify requirements and provide updates on project progress.

Pursued advanced studies in Neural and Cognitive Sciences, gaining theoretical knowledge to solve complex problems. Focused on combining technical skills with cognitive theories to understand and address complex challenges.

Completed a B.Tech in Computer Science and Engineering, building a strong foundation in technical skills. Gained comprehensive knowledge in computer science principles and their practical applications.