Abhishek Kumar

Developed “Personalized Lyrics Generation” project using generative AI (Google gemini-pro) and prompt engineering. Leveraged Streamlit for building an interactive user interface, enabling users to generate tailored lyrics. Applied innovative prompt engineering techniques to customize AI-generated lyrics based on individual preferences.

Meticulously assembled the Neo4j Graph database from the ground up and skillfully moved the RDBMS to the Graph structure, orchestrating a seamless transition aimed at augmenting overall database performance. Designed and devised an advanced deep learning and NLP-driven model tailored for email and SMS analysis, which proved instrumental in monitoring and comprehending clients’ intricate financial outlays. Created a voice recognition model capable of accurately identifying and understanding the speech patterns of customers. Designed a face-matching CNN-based model for Aadhar card and current face matching, ensuring high security and identification accuracy.

Collaborated closely with Product Engineering teams to meticulously devise and engineer an NLP-based query engine. Managed data preprocessing, data visualization, and researched low latency loading of datasets. Proficient in Object-Relational Mapping (ORM) techniques, utilizing them to bridge the gap between the relational database and application layers.