ADITYA SHUKLA

I am a B.Tech student in Computer and Communication Engineering with hands-on research experience in multimodal large language models and applied machine learning. I have explored fine-tuning techniques, Direct Preference Optimization, and replication studies related to RLHF-V while contributing to a government-funded multilingual tribal languages project.

My project work includes implementing state-of-the-art domain adaptation and segmentation models — notably a Multi-Representation Adaptation Network that achieved 95.6% cross-domain image classification accuracy and a UNET-based retinal vessel segmentation model. I regularly use Python, TensorFlow, Hugging Face, and common data-science libraries to produce reproducible results.

I actively engage in campus technical communities and events, serving in the Google Developer Student Club and volunteering at conferences and AI-ML workshops, and I seek roles where I can apply research experience to real-world ML and NLP challenges with impact.