Applied AI for Financial Decision-Making: From Risk-Aware Predictions to Adaptive Portfolio Intelligence

ABSTRACT

Artificial intelligence is transforming financial decision-making by enhancing prediction accuracy, risk management, and portfolio optimization. In this talk, I will present our recent works in applied AI for finance, showcasing how advanced machine learning, large language models, and reinforcement learning can be harnessed to address complex market challenges. These include RAGIC, a risk-aware generative framework for forecasting stock price intervals; DySTAGE, a dynamic spatio-temporal graph learning model for asset pricing; an LLM-based adaptive and explainable margin trading system for portfolio management; and MARS, a meta-adaptive reinforcement learning framework for multi-agent trading. Together, these approaches illustrate how AI can enable more intelligent, adaptive, and interpretable financial systems.

BIOGRAPHY

Prof. Guiling “Grace” Wang, Ph.D., CFA, is a Distinguished Professor of Computer Science and the Associate Dean for Research and External Relations at the Ying Wu College of Computing at the New Jersey Institute of Technology (NJIT). She established the AI Center for Research at NJIT and serves as its Founding Director. Prof. Wang led the development of NJIT’s M.S. in Artificial Intelligence program and the AI Certificate Program, both of which officially launched in 2023 as among the first AI programs in New Jersey.

Prof. Wang has been elected a Fellow of the IEEE, becoming the first female IEEE Fellow at NJIT, and is also a Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA). Her expertise in AI has been applied to solving complex challenges in fields such as finance and transportation. Her research on deep reinforcement learning for traffic signal cycle optimization received the IEEE Vehicular Technology Society’s 2023 Best Paper Award—four years after publication—in recognition of its lasting impact. In 2020, her project was selected as one of four awardees from 122 submissions nationwide under the U.S. Department of Transportation’s prestigious Exploratory Advanced Research (EAR) Program.

Prof. Wang served as Program Co-Chair of the ACM Conference on AI in Finance in 2023 and as General Co-Chair in 2024. She founded KDD Finance Day and has organized it annually since 2023. She also served as Sponsor Chair or Co-Chair for AAAI 2023, AAAI 2024, and ICDM 2025. In addition, she serves as an Associate Editor for several top-tier journals, including ACM Computing Surveys, IEEE Transactions on Knowledge and Data Engineering, and ACM Transactions on Internet Technology.

Beyond her academic achievements, Prof. Wang holds multiple governmental advisory roles. Since 2023, she has served as the sole academic representative on the New Jersey Supreme Court Committee on Artificial Intelligence and the Courts. The committee has issued multiple guidelines to the New Jersey legal community, including “Legal Practice: Preliminary Guidelines on the Use of Artificial Intelligence by New Jersey Lawyers”, followed by “Guidance for Courts on the Importance of Artificial Intelligence.” She also contributed to the New Jersey Governor’s AI Task Force Innovation Group in 2024–2025, again as the only university representative. Since 2024, she has served on the New Jersey Supreme Court Advisory Committee on Access and Fairness. In addition, she is a Subject Matter Expert in AI for the U.S. Department of Homeland Security’s SAGE program.