◦ Email Classification Pipeline: Sourced and vetted email datasets, executed EDA (bigram analysis, word clouds) to validate suitability for NLP tasks. ◦ Data Engineering & Preprocessing: Cleaned, transformed, and staged raw email data—ensuring high-quality inputs for model training. ◦ Model Development & Evaluation: Built, fine-tuned, and benchmarked machine-learning classifiers (sentiment& intent) to achieve optimal accuracy and robustness. ◦ Cross-Functional Collaboration: Partnered with analysts and engineers to integrate NLP insights into broader analytics workflows and reporting.

◦ AI-Generated Code Assessment: Reviewed and analyzed AI-generated Python code, ensuring clarity, correctness, and adherence to best practices. ◦ Code Refinement and Optimization: Enhanced AI-generated code by improving efficiency, readability, and maintainability through refactoring and optimization. ◦ Test Case Design: Developed and executed test cases to validate the accuracy and robustness of AI-generated solutions. ◦ Code Documentation and Review: Provided detailed feedback, documentation, and structured explanations to improve code comprehension and usability. ◦ Diverse AI Labelling Tasks: Contributed to various AI-driven projects, including evaluating code snippets, annotating programming logic, and improving AI coding assistance models.

◦ AI-Generated Code Evaluation: Evaluated the quality of AI-generated code, providing human-readable summaries and insights to ensure clarity and efficiency. ◦ Solving Coding Challenges: Solved diverse coding challenges by writing functional and efficient code, ensuring optimal performance and scalability. ◦ Test Case Development: Developed robust test cases to verify the efficiency and accuracy of code, enhancing reliability across projects. ◦ Instruction Creation and Code Review: Created detailed instructions to assist others in understanding coding logic and conducted thorough code reviews before integration into AI models. ◦ Variety of AI Projects: Worked on a wide range of projects, from evaluating Python code quality to developing full mobile applications with chatbots and optimizing their responses for better performance.

◦ Innovative WhatsApp Bot Development: Designed and implemented a WhatsApp bot to enhance customer engagement and streamline promotional outreach. The bot facilitated follow-ups with customers to address challenges in transitioning to the new application, significantly improving the efficiency of the Sales Department.

◦ VectorDB: Created a Vector Database (VectorDB) for storing history and retrieving it to implement Retrieval-Augmented Generation (RAG). ◦ Speech-to-Speech: Integrated Text-to-Speech (TTS) and Speech-to-Text (STT) systems for seamless speech interactions. ◦ Prompt Engineering: Performed prompt engineering using Gemini Pro to optimize interactions with large language models (LLMs).

Currently at 6th semester