Chengshuo Dai

I’m a self-taught AI/LLM engineer in progress, currently transitioning into the field by studying GenAI and building real-world LLM apps.

My academic background spans Information Mgt, Finance, and Biostat, but growing fascination with LLM led me to pivot toward AI engineering. I began this journey in 2025, and since then I’ve been focused on studying how modern large language model systems work.

Through self-study and hands-on projects, I’ve been exploring the end-to-end LLM stack (including the engineer intuition of math/stat behind) — from model fundamentals (architectures, pretraining, fine-tuning, RLHF) to inference optimization and downstream applications such as RAG pipelines, agentic workflows, and AI-powered search systems.

I believe in the AI era, the most valuable asset is not a single background, but the curiosity, discipline, and ability to fast-learn and adapt. As a self-driven builder, I’m deeply curious about how new AI technologies work, enjoy exploring them from first principles and turn them into working systems and practical products.

Here’s a quote that deeply inspires me:
Background defines the past, but problems define the future.