Research-driven AI and Data Science specialist with expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and advanced data visualization. Experienced in RLHF, LLM fine-tuning, prompt engineering,…
Research-driven AI and Data Science specialist with expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and advanced data visualization. Experienced in RLHF, LLM fine-tuning, prompt engineering, Lang Chain, and building multimodal AI systems for high-impact applications in healthcare, document intelligence, and scientific research. Skilled at vector database integration, distributed model training with Py Spark, and designing explainable AI systems with SHAP and Grad-CAM. Published author with a proven track record of delivering reproducible, interpretable, and production ready AI solutions.
Led research on transformer-based architectures (MedViT, ViT) for medical imaging anomaly detection, achieving significant accuracy gains over CNN baselines.
Fine-tuned LLMs using RLHF for domain-specific text summarization and entity extraction in healthcare datasets.
Integrated vector databases (FAISS, Weaviate) with LangChain pipelines for semantic search and retrieval-augmented generation.
Developed explainable AI frameworks with SHAP, Grad-CAM, and attention heatmaps to improve model transparency for clinical stakeholders.
Led research on transformer-based architectures, fine-tuned LLMs, integrated vector databases, and developed explainable AI frameworks.
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