Education

• Ph.D. in Computer Science, New Jersey Institute of Technology (NJIT), 2025 (advisor: Distinguished Professor Guiling (Grace) Wang; NJIT Fintech Lab and Center for AI Research)
• M.S. in Computer Science, New Jersey Institute of Technology (NJIT) (advisor: Distinguished Professor Guiling (Grace) Wang)
• M.S. in Optics, Shanghai University (advisor: Prof. Ye Dai)

Employment

• Assistant Professor, School of Computing, College of Science and Mathematics, Montclair State University

Publications

Can You Delete a Year of Market Data? Machine Unlearning Against Exact Retraining Oracles

Ye, J. (2026). "Can You Delete a Year of Market Data? Machine Unlearning Against Exact Retraining Oracles." Proceedings of the 7th ACM International Conference on AI in Finance (ICAIF '26).

Damage Predicts Recovery: When Calibration Data Matters in Compressing Financial LLMs

Ye, J., Yu, M., Hazra, D., & Wang, G. (2026). "Damage Predicts Recovery: When Calibration Data Matters in Compressing Financial LLMs." Proceedings of the 7th ACM International Conference on AI in Finance (ICAIF '26).

Regime-Gated Residual Mixture-of-Experts for Cross-Sectional Volatility Forecasting

Ye, J., & Borde, G. V. (2026). "Regime-Gated Residual Mixture-of-Experts for Cross-Sectional Volatility Forecasting." Proceedings of the 7th ACM International Conference on AI in Finance (ICAIF '26).

Calibration Bets on the Past: Post-Training Quantization for Financial Time-Series Forecasting

Ye, J., & Wanjiku, I. G. (2026). "Calibration Bets on the Past: Post-Training Quantization for Financial Time-Series Forecasting." Proceedings of the 7th ACM International Conference on AI in Finance (ICAIF '26).

Illusions in Humans and AI: How Visual Perception Aligns and Diverges

Yang*, J., Ye*, J., Dash, A., & Wang, G. (2025). "Illusions in Humans and AI: How Visual Perception Aligns and Diverges." arXiv preprint arXiv:2508.12422.

From Standalone LLMs to Integrated Intelligence: A Survey of Compound AI Systems

Chen, J., Ye, J., & Wang, G. (2025). "From Standalone LLMs to Integrated Intelligence: A Survey of Compound AI Systems." arXiv preprint arXiv:2506.04565.

Beyond End-to-End VLMs: Leveraging Intermediate Text Representations for Superior Flowchart Understanding

Ye, J., Dash, A., Yin, W., & Wang, G. (2025). "Beyond End-to-End VLMs: Leveraging Intermediate Text Representations for Superior Flowchart Understanding." Proceedings of NAACL 2025.

Assessing the Creativity of LLMs in Proposing Novel Solutions to Mathematical Problems

Ye, J., Gu, J., Zhao, X., Yin, W., & Wang, G. (2025). "Assessing the Creativity of LLMs in Proposing Novel Solutions to Mathematical Problems." Proceedings of the AAAI Conference on Artificial Intelligence.

Adaptive and Explainable Margin Trading via Large Language Models on Portfolio Management

Gu*, J., Ye*, J., Wang, G., & Yin, W. (2024). "Adaptive and Explainable Margin Trading via Large Language Models on Portfolio Management." Proceedings of the 5th ACM International Conference on AI in Finance (ICAIF '24), 248–256.

DySTAGE: Dynamic Graph Representation Learning for Asset Pricing via Spatio-Temporal Attention and Graph Encodings

Gu*, J., Ye*, J., Uddin, A., & Wang, G. (2024). "DySTAGE: Dynamic Graph Representation Learning for Asset Pricing via Spatio-Temporal Attention and Graph Encodings." Proceedings of the 5th ACM International Conference on AI in Finance (ICAIF '24), 388–396.

From Blind Solvers to Logical Thinkers: Benchmarking LLMs’ Logical Integrity on Faulty Mathematical Problems

Rahman*, M., Ye*, J., Yao, W., Yin, W., & Wang, G. (2024). "From Blind Solvers to Logical Thinkers: Benchmarking LLMs' Logical Integrity on Faulty Mathematical Problems." arXiv preprint arXiv:2410.18921.

DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure

Ye, J., Du, M., & Wang, G. (2024). "DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure." The 16th Asian Conference on Machine Learning.

From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing

Ye*, J., Goswami*, B., Gu*, J., Uddin, A., & Wang, G. (2024). "From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing." arXiv preprint arXiv:2403.06779.

High Resolution Solar Image Generation Using Generative Adversarial Networks

Dash, A., Ye, J., Wang, G., & Jin, H. (2024). "High Resolution Solar Image Generation Using Generative Adversarial Networks." Annals of Data Science, 11(5), 1545–1561.

A Review of Generative Adversarial Networks (GANs) and Its Applications in a Wide Variety of Disciplines: From Medical to Remote Sensing

Dash, A., Ye, J., & Wang, G. (2024). "A Review of Generative Adversarial Networks (GANs) and Its Applications in a Wide Variety of Disciplines: From Medical to Remote Sensing." IEEE Access, 12, 18330–18357.

Establishing a Baseline for Evaluating Blockchain-Based Self-Sovereign Identity Systems: A Systematic Approach to Assess Capability, Compatibility and Interoperability

Yao, W., Du, W., Gu, J., Ye, J., Deek, F. P., & Wang, G. (2024). "Establishing a Baseline for Evaluating Blockchain-Based Self-Sovereign Identity Systems." Proceedings of the 2024 6th Blockchain and Internet of Things Conference, 108–119.

SafeLight: A Reinforcement Learning Method toward Collision-Free Traffic Signal Control

Du, W., Ye, J., Gu, J., Li, J., Wei, H., & Wang, G. (2023). "SafeLight: A Reinforcement Learning Method toward Collision-Free Traffic Signal Control." Proceedings of the AAAI Conference on Artificial Intelligence, 37(12), 14801–14810.

Prediction with Time-Series Mixer for the S&P500 Index

Ye, J., Gu, J., Dash, A., Deek, F. P., & Wang, G. (2023). "Prediction with Time-Series Mixer for the S&P500 Index." 2023 IEEE 39th International Conference on Data Engineering Workshops (ICDEW), 20–27.