Debjyoti Paul - The mathematics behind transformer and attention mechanism

​The session will cover the following:
1. The positional encoding, ROPE
2. How that becomes attention and then how approximation is done at inference time
3. A short corollary for multi-head attention and mixture of experts

Speaker Bio:
Debjyoti is a Data Scientist at Amazon with over 9 years of industrial experience in Natural Language Processing (NLP), Large Language Models (LLMs), and Agentic AI and Responsible AI, Currently Debjyoti is Leading Agentic development and actively working on Agent learning primarily focusing on Agentic System improvement from Context Engineering to RL based Learning framework. Prior to this Debjyoti has led AI-driven solutions in enterprise applications focusing on Anomaly Detection, Recommendation system, NLP, Information extraction and Computer Vision. Their research expertise spans AI ethical AI governance, bias mitigation, and scalable LLM deployment, model interpretability ensuring responsible AI adoption across industries. With hands-on experience in developing production-grade AI systems, they actively research fairness, robustness, and transparency in AI, contributing to frameworks that enhance trust and accountability in AI-driven decision-making.