Shengyu (Henry) Huang is a PhD Candidate in Financial Engineering at Stevens Institute of Technology and will join the College of Business and Technology at Winthrop University in Fall 2026. His research focuses on empirical asset pricing and interpretable machine learning, with a particular emphasis on how model complexity affects financial predictions and market outcomes. His dissertation examines the role of nonlinear models in asset pricing and financial stability, with applications spanning stock return predictability and bank complexity measurement. Beyond his dissertation, his work extends to fintech, financial risk management, and corporate disclosure, integrating modern machine learning techniques with traditional financial theories to address core questions in asset pricing, risk management, and market efficiency. Recently, he published Watching the FedWatch in the Journal of Futures Markets, which demonstrates that market-implied monetary policy trackers deliver high predictive accuracy and economic value while reducing uncertainty around FOMC decisions.

In addition to his research, Shengyu is dedicated to teaching and mentoring. Drawing on his interdisciplinary background in finance and technology, he strives to engage students with contemporary financial topics while developing their practical, market-relevant skills. His teaching philosophy emphasizes empathy, the integration of new technologies, real-world applications of theory, and clear, structured content. He has served as a Teaching Assistant at NYU and Stevens Institute of Technology, and has independently taught coding lab courses in R, SQL, and Python, helping students build both critical thinking and technical proficiency in a supportive learning environment.

Outside academia, Shengyu enjoys traveling, photography, and following soccer. He is a lifelong supporter of his hometown team, Shanghai Shenhua, and values these interests as a way to stay balanced and connected beyond his academic work.