Journal of Climate Change and Pollution

Zhaoen Qu is currently pursuing a dual bachelor’s degree in Management Information Systems at Beijing Jiaotong University (China) and Rochester Institute of Technology (USA). As a Research Assistant at Beijing Jiaotong University, Zhaoen has contributed to the National Natural Science Foundation of China project “Research on Blockchain Consensus Mechanisms Based on Multilateral Negotiation. He has authored and co-authored several accepted SCIE-indexed publications, focusing on stochastic analysis, deep learning frameworks, and carbon emission forecasting. His works demonstrate strong interdisciplinary expertise bridging financial mathematics, machine learning, and environmental modeling. Zhaoen has also led award-winning teams in national innovation competitions, developing AI-based systems for logistics and sustainability applications. His academic background, research rigor, and innovation in intelligent systems make him a promising young researcher in data science and sustainability analytics.

• Stochastic Differential Equations
• Carbon Emission Prediction
• Sustainable Innovation and Environmental Data Analysis
• Financial Time Series Forecasting
• Blockchain Consensus Mechanisms
• Machine Learning and Deep Learning

1. Research Assistant, National Natural Science Foundation of China project
2. Anonymous Reviewer for FinTech and Sustainable Innovation Journal
3. Team Leader, AI-based Logistics Customer Service System (Software Copyright Filed)
4. Participant and Prize Winner,
5. China International College Students’ Innovation Competition (Beijing Division) – Third Prize
6. 15th National College Students’ E-Commerce Innovation Challenge – First Prize

1. Qu, Z. (2025). Malliavin Differentiability and Density Smoothness for Non-Lipschitz Stochastic Differential Equations. Axioms (Accepted).
2. Qu, Z., et al. (2025). Adaptive Ensemble Learning for Financial Time Series Forecasting: A Hypernetwork-Enhanced Reservoir Computing Framework with Multi-Scale Temporal Modeling. Axioms (Accepted).
3. Qu, Z., et al. (2025). Hierarchical Multi-Scale Decomposition and Deep Learning Ensemble Framework for Enhanced Carbon Emission Prediction. Mathematics (Accepted).