معرفی
Denghui Zhang is an Assistant Professor in the School of Business at Stevens Institute of Technology. His research focuses on data science, large language models (LLMs), and business analytics, with particular emphasis on applications in financial systems, knowledge graphs, and spatio-temporal prediction. He is a member of the Stevens Institute for Artificial Intelligence and has held academic roles including reviewer positions for prestigious journals like Nature Communications and conferences such as AAAI and SIGKDD.
Dr. Zhang holds a PhD in Information Systems from Rutgers University (2023) and an MS in Computer Science from the University of Chinese Academy of Sciences (2018). His educational background bridges computer science and business analytics, enabling his cross-disciplinary research.
His research explores cutting-edge topics like federated learning optimization for LLMs, theory-of-mind reasoning mechanisms, and ethical AI governance. Notable contributions include turbulence forecasting models, traffic prediction frameworks, and venture capital investment strategies leveraging reinforcement learning.
Dr. Zhang has received prestigious recognitions including the ICIS 2023 Best Student Paper Award and AAAI-23 Student Scholar distinction. His work frequently addresses practical challenges in AI ethics, financial decision-making systems, and scalable machine learning architectures.
He actively contributes to academic communities through program committee roles for top conferences and has pioneered novel methodologies in multi-agent financial systems and graph neural network design.
