Atharva Nimbalwar Email & Phone Number

Boston, Massachusetts, United States

• Engineered a customer-facing chatbot using React and TypeScript, integrated with OpenAI GPT-4o mini, improving user interaction by 30% and providing efficient, real-time query handling and improving user interaction
• Developed a dynamic employee management dashboard using React, enabling managers to track progress and assignments for 30+ projects across 8 teams, supported by a scalable Node.js backend
• Designed and implemented RESTful APIs with Django to facilitate secure and optimized data retrieval for project and employee management systems
• Structured and optimized database schemas and queries to optimize data handling, reducing query response times and ensuring seamless integration with backend services

Nagpur

• Crafted an intuitive user interface using HTML, CSS, and React to develop a web page facilitating policy initialization, and seamless interaction using Redux and NodeJS
• Engineered Node.js backend code to validate policy initialization forms and PDFs through integration with PDF verification API
• Deployed a queuing mechanism within Redis to handle customer requests, elevating the authorization process and ensuring streamlined management of incoming data
• Employed ReactJS PDF packages and crafted Python scripts to automate default account creation. Utilized advanced socket communication and Redis to facilitate smooth video communication between clients and customer.
• Implemented Docker for cross-platform compatibility, employed Kubernetes for efficient container management and scaling, and seamlessly integrated GitHub with Jenkins to establish a robust CI/CD pipeline
• Configured MongoDB database for storing policy initialization data, ensuring secure and efficient data retrieval. Employed Mongoose for Node.js to interact with the database and enforce schema validations

Maharashtra, India

• Revamped transformer-based models including BART, T5, and PEGASUS on COVID-19 articles and research papers to generate human-like summaries of ~2TB of data
• Optimized data preprocessing using advanced NLP methods such as tokenization and lemmatization, resulting in a refined dataset
• Implemented TF-IDF vectorization to transform raw text into quantitative features, boosting ML model accuracy by 12%
• Enhanced NLP capabilities by fine-tuning PEGASUS model leveraging the NVIDIA DGX workstation
• Outperformed the initial PEGASUS model demonstrating superior accuracy and Rouge scores by 35%
• Employed CI/CD for automated testing and deployment of fine-tuned transformer models, ensuring rapid and reliable model

Master'S Degree, Software Engineering

Computer Science