Molei Qin

Orcid: 0009-0001-0431-7940

According to our database1, Molei Qin authored at least 10 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
History Is Not Enough: An Adaptive Dataflow System for Financial Time-Series Synthesis.
CoRR, January, 2026

Bayesian Robust Financial Trading with Adversarial Synthetic Market Data.
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

FineFT: Efficient and Risk-Aware Ensemble Reinforcement Learning for Futures Trading.
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

ArchetypeTrader: Reinforcement Learning for Selecting and Refining Learnable Strategic Archetypes in Quantitative Trading.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
Cradle: Empowering Foundation Agents towards General Computer Control.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024
MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

EarnHFT: Efficient Hierarchical Reinforcement Learning for High Frequency Trading.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
PRUDEX-Compass: Towards Systematic Evaluation of Reinforcement Learning in Financial Markets.
Trans. Mach. Learn. Res., 2023

TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023


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