BIMSA > 严兴
副研究员 严兴

团队: 数字经济

办公室: A15-206

邮箱: yanxing@bimsa.cn

研究方向: 人工智能与数字金融

个人主页: https://sites.google.com/view/xingyan

个人简介

I am an Associate Professor at the Beijing Institute of Mathematical Sciences and Applications, since 2025. Prior to this role, I was an Assistant Professor at the Institute of Statistics and Big Data, Renmin University of China, and a postdoctoral researcher at the School of Data Science, City University of Hong Kong. My research lies at the intersection of AI and finance/business, focusing on FinTech and Business Analytics through innovative machine learning and data science methodologies. My interests include tail risk management, empirical asset pricing, portfolio optimization, derivatives, consumer credit, and related areas. Recently, I have also developed an interest in out-of-distribution (OOD) generalization and uncertainty quantification in machine learning. I publish in both finance/business and machine learning academic journals and conferences.

研究兴趣

  • 机器学习、金融科技、商业分析
  • OOD泛化、不确定性量化

教育经历

  • 2015 - 2019      香港中文大学      SEEM（金融工程方向）      Ph.D      (Supervisor: Prof. Qi Wu)
  • 2012 - 2015      中国科学院计算技术研究所      计算机科学      Master
  • 2008 - 2012      南开大学      基础数学（陈省身班）      Bachelor

工作经历

  • 2025 -      北京雁栖湖应用数学研究院      副研究员
  • 2020 - 2025      中国人民大学统计与大数据研究院      助理教授
  • 2019 - 2020      香港城市大学数据科学学院      博士后

出版物

  • [1] Z Xian, X Yan, CH Leung, Q Wu, Risk-Neutral Generative Networks, arXiv, 2405.17770 (2024)
  • [2] Y Liao, Q Wu, X Yan, Invariant Random Forest: Tree-Based Model Solution for OOD Generalization, AAAI Conference on Artificial Intelligence (AAAI), Oral Presentation (2024)
  • [3] N Yang, CH Leung, X Yan, A novel HMM distance measure with state alignment, Pattern Recognition Letters, 186, 314-321 (2024)
  • [4] C Sun, Q Wu, X Yan, Dynamic CVaR Portfolio Construction with Attention-Powered Generative Factor Learning, Journal of Economic Dynamics and Control (JEDC) (2024)
  • [5] X Liu, X Yan, K Zhang, Kernel quantile estimators for nested simulation with application to portfolio value-at-risk measurement, European Journal of Operational Research, 312(3), 1168-1177 (2024)
  • [6] Y Li, CH Leung, X Sun, C Wang, Y Huang, X Yan, Q Wu, D Wang, ..., The Causal Impact of Credit Lines on Spending Distributions, AAAI Conference on Artificial Intelligence (AAAI) (2024)
  • [7] X Yan, Y Su, W Ma, Ensemble Multi-Quantile: Adaptively Flexible Distribution Prediction for Uncertainty Quantification, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (2023)
  • [8] W Ma, X Yan, K Zhang, Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (2023)
  • [9] Y Liao, Q Wu, Z Wu, X Yan, Decorr: Environment partitioning for invariant learning and ood generalization, arXiv, 2211.10054 (2022)
  • [10] Y Huang, CH Leung, Q Wu, X Yan, S Ma, Z Yuan, D Wang, Z Huang, Robust causal learning for the estimation of average treatment effects, 2022 International Joint Conference on Neural Networks (IJCNN), 1-9 (2022)
  • [11] SY Wang, X Yan, BQ Zheng, H Wang, WL Xu, NB Peng, Q Wu, Risk and return prediction for pricing portfolios of non-performing consumer credit, ACM International Conference on AI in Finance (2021)
  • [12] Y Huang, CH Leung, X Yan, Q Wu, N Peng, D Wang, Z Huang, The Causal Learning of Retail Delinquency, AAAI Conference on Artificial Intelligence (AAAI) (2021)
  • [13] X Yan, Q Wu, W Zhang, Cross-sectional Learning of Extremal Dependence among Financial Assets, Neural Information Processing Systems (NeurIPS) (2019)
  • [14] Q Wu, X Yan, Capturing Deep Tail Risk via Sequential Learning of Quantile Dynamics, Journal of Economic Dynamics and Control (JEDC) (2019)
  • [15] X Yan, W Zhang, L Ma, W Liu, Q Wu, Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning, Neural Information Processing Systems (NeurIPS) (2018)
  • [16] X Yan, H Chang, S Shan, X Chen, Modeling video dynamics with deep dynencoder, European Conference on Computer Vision (ECCV) (2014)
  • [17] X Yan, H Chang, X Chen, Temporally multiple dynamic textures synthesis using piecewise linear dynamic systems, IEEE International Conference on Image Processing, 3167-3171 (2013)

 

更新时间: 2025-12-15 17:00:11