Henry Chiang

Henry Chiang is a Quantitative Researcher at the Quantitative Research & Solutions (QRS) team at S&P Global Market Intelligence, specializing in systematic equity research and alpha extraction using large language models (LLM).

Prior to his current position, Henry served as an NLP research assistant at Academia Sinica, Taiwan’s national research institution. In this role, he investigated the early-stage financial and legal applications of NLP and LLM technologies.

Leveraging his expertise in NLP and LLM, Henry led the technical development of several impactful AI research projects, including ‘Questioning the Answers’, ‘Earning Seasons Report’ and ‘Three tools for Trump Tariffs 2.0’. His work has been well-received at conferences and cited by major media outlets, including Financial Times, Forbes, etc.

Henry joined S&P Global in August 2023 as a Quantitative Research Associate. He is currently pursuing an Executive Masters in Finance at London School of Economics (LSE) and holds a Bachelor degree in Physics from Imperial College London.