Tanvin Sharma

Founded Hearfront.ai, an AI-powered feedback app that transforms how businesses gather and act on customer and employee feedback. Currently finalizing the technical aspects of the app and client scouting, supported by the startup initiative at the Technical University of Munich.

Restructured software requirements using the EARS format and implemented parsing techniques with GPT-4, achieving a 93% increase in parsing accuracy. Developed a tool using FastAPI for requirement engineers, reducing manual restructuring time by 60%.

Created REST APIs for Toptal’s internal employee system using Ruby on Rails and integrated GraphQL for efficient querying, enhancing data accessibility for internal users.

Designed and implemented REST APIs for NID Smart Manhole and MPWiK Pipelines projects, enhancing reporting features for real-time analytics and improving operational decision-making by 50%.

Developed a Q&A system for complex legal documents, achieving 87% accuracy through fine-tuning BERT and implementing Semantic Search techniques for document retrieval.

Developed educational material in Python, automating the solution-checking process for teachers, saving them 7-10 hours per week through an automated checking method.

Grade: 2.1/1

Pursuing a Masters of Science (M.S.) in Computer Science with a specialization in Natural Language Processing (NLP). Key coursework includes Machine Learning, Deep Learning, Efficient Data Structures and Algorithms, and Advanced NLP.

Grade: 4.56/5

Completed a Bachelor of Science (B.S.) in Computer Science. Key coursework included Algorithms, Object Oriented Programming, and Artificial Intelligence.