Dual degree (B.S + M.S)

Automated Hindi transcript cleaning Performed CTC segmentation using Nvidia’s Nemo model for audio files • Performed thorough research implemented three state-of-the-art RAG[1] architectures(simple, hyde, and fusion) • Obtained F1 score of 0.8-0.9 for RAG models on custom methods developed using prompt engineering techniques • Automated the evaluation process by constructing an end-to-end MLflow pipeline for benchmarking

LLM Ops Engineer

• Developed VR games from scratch using Unity & implemented the game logic in c# using advanced OOPS concepts • Enhanced user engagement by implementing multiplayer functionality with lobby management using Photon PUN • Designed and developed a VR game for Apple Vison Pro using Swift, optimized for advanced hardware capabilities

Junior Developer

– Researched various Methods to implement tactile feedback, as part of the hardware team. – Implemented a pipeline for communication between microcontroller and unity using a WebSocket, As lead of the software team. – Created a 3D game in Unity to ensure the proper functioning of the pipeline. – Created a basic VR game in Unity to test the functionality of the glove.

Project Member

Data Scientist

– Cuerated, analyzed, and cleaned cancer patient details using pandas and mapped them with microarray/RNAseq data. – Implemented a generalised cleaning function and merged it with a python library being developed from scratch. – Read research papers on GSVA, and signscore algorithms and implement them in r programing language. – Visuvalised batch effect for above-mentioned algorithms using UMAP in r programing language.

Research Associate Intern

Software Engineer

Building AI @ QApilot

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