Paper 'TextFlow' accepted for main conference at NAACL 2025; 'CreativeMath' accepted for oral presentation at AAAI 2025; 'Margin Trader LLM' and 'DySTAGE' accepted for oral presentation at ICAIF 2024; 'DataFrame QA' accepted for oral presentation at ACML 2024.
Research Experience
Conducting research at NJIT Fintech Lab and Center for AI Research.
Education
Ph.D. candidate in Computer Science at New Jersey Institute of Technology (NJIT), under the mentorship of Distinguished Professor Guiling (Grace) Wang. Holds a master’s degree in Computer Science from NJIT and a master’s degree in Optics from Shanghai University, where he studied under the guidance of Professor Ye Dai.
Background
His research interests lie at the intersection of large language models, graph neural networks, time series analysis, and computer vision. His work focuses on developing innovative AI frameworks for solving real-world challenges, including privacy-preserving information retrieval, financial modeling, and explainable decision-making AI systems. He is particularly interested in exploring the creative and interpretive capabilities of AI in applications spanning finance, healthcare, and decision making.