Education
2011–2015: Ph.D. in Economics, Guanghua School of Management, Peking University
2007–2011: B.A. in Economics, School of Statistics, Renmin University of China
Work Experience
2023–present: Professor, School of Statistics, Renmin University of China
2018–2023: Associate Professor, School of Statistics, Renmin University of China
2015–2018: Assistant Professor, School of Statistics, Renmin University of China
Professional Service
2023–present: Executive Council Member, Education Statistics and Management Branch, Chinese Association for Applied Statistics
2022–present: Industrial Commissioner, First Batch of Expert Service Group, “One Thousand Experts Serving One Thousand Enterprises” Action Plan, Beijing
2019–present: Deputy Secretary-General and Executive Council Member, Beijing Big Data Association
2018–present: Council Member, Association of Young Statisticians
Research Grants
Complex Network Models and Algorithms in the Digitalization of SMEs, National Natural Science Foundation of China (General Program), 2025–2028, PI, ongoing
Statistical Modeling for Digital Transformation of Private Enterprises with Large-Scale Data, Beijing Social Science Foundation (Key Project), 2024–2026, PI, ongoing
Key Technologies for Financial Data Synthesis and Intelligent Risk Monitoring Models, National Key R&D Program of China (“Social Governance and Smart Society”), 2024–2026, Co-PI, ongoing
Statistical Methods for the Digital Development of SMEs, National Statistical Science Research Program (Key Project), 2024–2025, PI, ongoing
Modeling, Computation, and Applications of Sparse Network Data, National Natural Science Foundation of China (General Program), 2021–2024, PI, ongoing.
Strategic Research on China’s Cross-Border Payment Monitoring System, Consulting Project of the Chinese Academy of Engineering, 2020–2021, participant, completed.
Credit Evaluation Models for Small and Micro Merchants under Multidimensional Data Streams, Renmin University Scientific Research Fund (General Program), 2019–2021, PI, ongoing.
Spatial Autoregressive Models in Social Networks: Theory and Applications, National Natural Science Foundation of China (Young Scholar Program), 2018–2020, PI, completed.
Big Data–Driven Internet Credit Rating Models, Beijing Social Science Foundation (Young Scholar Program), 2018–2020, PI, completed.
Integration of Unstructured Data in Internet Credit Evaluation, National Bureau of Statistics Research Project, 2017–2019, PI, completed.
Statistical Models for Large-Scale Social Networks, Renmin University Scientific Research Fund (Young Scholar Program), 2016–2017, PI, completed.
Credit Scoring Models in Internet Finance, Industry Project, 2016–2017, PI, completed.
Honors and Awards
Second Prize, Science Category, 13th Teaching Competition for Young Faculty, Beijing Universities, 2023
Most Popular Teacher Award, Science Category, 13th Teaching Competition for Young Faculty, Beijing Universities, 2023
Teaching Excellence Award, Renmin University of China, 2023
First Prize for Outstanding Research Achievement, Renmin University of China, 2023
First Prize, Science Category, 12th Teaching Competition for Young Faculty (1st place), Renmin University of China, 2023
Young Talent Support Program, Beijing Association for Science and Technology, 2023–2025
Outstanding Instructor Award, National Undergraduate Market Survey and Analysis Competition, 2021 & 2023
“Outstanding Young Scholar,” Renmin University of China, 2020–present
Research Excellence Award, Renmin University of China, 2020
Beijing Excellent Talent Training Program, 2017
Courses Taught
Business Analytics Practice, 2020–present
Mathematical Statistics, 2018–present
Time Series Analysis, 2018–present
Statistics, 2017–present
Business Big Data Case Analysis, 2016–present
Selected Topics in Stochastic Analysis, 2015
Research Interests
Dimension Reduction in Ultra-High-Dimensional Data
Complex Network Modeling
Distributed Computing
Digitalization of Small and Micro Enterprises
Publications
Journals & Conference
Yin, H., Wang, L.*, Zhu, Y., Zhu, L., & Huang, D.*(2025), Vertical Federated Feature Screening, Advances in Neural Information Processing Systems (NeurIPS), Accepted.
Hu, W., Huang, D., & Zhang, B. (2025). Pseudo-Likelihood Ratio Screening based on Network Data with Applications. Annals of Applied Statistics, 19(3), 2517–2538.
Li, X., Huang, D., & Wang, H. (2025). Pairwise Maximum Likelihood For Multi-Class Logistic Regression Model With Multiple Rare Classes. In Proceedings of the 42nd International Conference on Machine Learning, Vol. 267, 34725-34741.
Lin, Z., Huang, D.*, Xiong, Z., Wang, H.(2025) Statistical Inference for Regression with Imputed Binary Covariates with Application to Emotion Recognition. Annals of Applied Statistics. Accepted.
Zhu, Y., Huang, D.*, Zhang, B.(2025) A Wasserstein distance-based spectral clustering method for transaction data analysis. Expert Systems with Applications, 260, 125418.
Deng, J., Yang, X., Yu, J., Liu, J., Shen, Z., Huang, D., Cheng, H.*(2024) Network Tight Community Detection. 41st International Conference on Machine Learning, PMLR 235, 10574-10596.
Deng, J., Huang D.*, Zhang, B.(2024) Distributed Pseudo-Likelihood Method for Community Detection in Large-Scale Networks. ACM Transactions on Knowledge Discovery from Data, 18(7), 1-25.
Wu, S., Huang, D.*, Wang, H.*(2023) Quasi-Newton Updating for Large-Scale Distributed Learning. Journal of the Royal Statistical Society：Series B (Statistical Methodology), 85(4), 1326-1354.
Deng, J., Huang D.*, Ding, Y., Zhu, Y., Jing, B., Zhang, B*.(2023) Subsamping Spectral Clustering for Stochastic Block Models in Large-Scale Networks. Computational Statistics & Data Analysis, 189, 107835.
Huang, D., Hu, W.*, Jing, B., Zhang, B.* (2023) Grouped spatial autoregressive model. Computational Statistics & Data Analysis, 178, 107601.
Wang, F., Huang, D.*, Gao, T., Wu, S.*, Wang, H. (2022) Sequential One-Step Estimator by Subsampling for Customer Churn Analysis with Massive Datasets. Journal of the Royal Statistical Society：Series C (Applied Statistics), 71(5), 1753-1786.
Wu, S., Huang,D.*, Wang, H. (2022) Network Gradient Descent Algorithm for Decentralized Federated Learning. Journal of Business & Economic Statistics, 41(3), 806-818.
Hu, W., Huang, D.*, Jing, B., Zhang, B.* (2021) Crawling Subsampling for Multivariate Spatial Autoregression Model in Large-Scale Networks. Electronic Journal of Statistics, 15(2), 3678-3707.
Zhu, Y., Deng, Q., Huang, D.*, Jing, B., Zhang, B.* (2021) Clustering based on Kolmogorov-Smirnov statistic with application to bank card transaction data. Journal of the Royal Statistical Society：Series C (Applied Statistics), 70(3), 558-578.
Wang, F., Zhu, Y., Huang, D.*, Qi. H., Wang, H. (2021) Distributed one-step upgraded estimation for non-uniformly and non-randomly distributed data. Computational Statistics & Data Analysis, 162, 107265.
Zhu, Y., Huang, D.*, Gao, Y., Wu, R., Chen, Y., Zhang, B., Wang, H. (2021) Automatic, Dynamic, and Nearly Optimal Learning Rate Specification via Local Quadratic Approximation. Neural Networks, 141,11-29.
Huang, D., Zhu, X.*, Li, R., Wang, H. (2021) Feature Screening for Network Autoregression Model, Statistica Sinica, 31,1239-1259.
Zhu, X., Huang, D.*, Pan, R., Wang, H. (2020) Multivariate Spatial Autoregressive Model for Large Scale Social Networks, Journal of Econometrics, 215(2), 591-606.
Su, L., Lu, W.*, Song, R., and Huang, D. (2020) Testing and Estimation of Social Network Dependence with Time to Event Data. Journal of the American Statistical Association. 115(530), 570-582.
Huang, D., Wang, F*., Zhu, X., Wang, H.(2020) Two-Mode Network Autoregressive Model for Large-Scale Networks. Journal of Econometrics, 216(1), 203-219.
Zhu, Y., Huang, D.*, Xu, W., & Zhang, B. (2020). Link prediction combining network structure and topic distribution in large-scale directed network. Journal of Organizational Computing and Electronic Commerce, 30(2), 169-185.
Chang X., Huang, D.*, Wang, H. (2019) A Popularity Scaled Latent Space Model for Large-Scale Directed Social Network. Statistica Sinica, 29(3), 1277-1299.
Huang, D., Lan, W., Zhang, H. H., & Wang, H. (2019) Least squares estimation of spatial autoregressive models for large-scale social networks. Electronic Journal of Statistics, 13(1), 1135-1165.
Huang, D., Guan, G.*, Zhou, J., Wang, H. (2018) Network-based Naive Bayes Model for Social Network. Science China Mathematics, 61(4), 627-640.
Huang, D., Zhou, J.*, and Wang, H. (2018) RFMS Method for Credit Scoring Based on Bank Card Transaction Data. Statistica Sinica, 28(4), 2903-2919.
Zhou, J., Huang, D.*, and Wang, H. (2017) A dynamic logistic regression for network link prediction. Science China Mathematics, 60, 165-176.
Huang, D., Yin, J., Shi, T., and Wang, H.* (2016) A statistical model for social network labeling. Journal of Business and Economic Statistics, 34(3), 368-374.
Huang, D., Li, R.*, & Wang, H. (2014) Feature Screening for Ultrahigh Dimensional Categorical Data with Applications. Journal of Business & Economic Statistics, 32(2), 237-244.
Chinese Journals
Zhu, Y., Huang, D., Zhang, B. (2024). A distribution-factor clustering method based on Gaussian mixture model. Statistical Research, 41(6), 147-160.
Huang, D., Zhu, Y., Nan, J., Wang, H. (2022). Identification of credit card cash-out transactions and merchants based on transaction flows. Journal of Mathematical Statistics and Management, 42(1), 127-144.
Huang, D., Guo, Y., Jiang, G., Tian, K. (2022). Analyzing offline sales of restaurant merchants by integrating multidimensional online features. Journal of Marketing Science, 1(2), 30-51.
Huang, D., Zhang, L. (2021). Link prediction in bimodal signed networks based on local community structural balance. Statistical Research, 38(12), 131-144.
Huang, D., Bi, B., Zhu, Y. (2021). Risk merchant clustering analysis based on Gaussian spectral clustering. Statistical Research, 38(6), 145-160.
Huang, D., Bi, B., Miao, Y. (2020). Latent space model based on node popularity in bimodal networks. Statistical Research, 37(3), 60-71.
Wang, Z., Fu, G., Huang, D., Wang, J. (2014). Study on the relationship between “political promotion” of state-owned enterprise CEOs and “on-duty consumption”. Management World, 5, 157-171.
Books / Monographs
Huang, D. (2022). Analysis of Large-Scale Network Data and Spatial Autoregressive Models. Science Press.(in Chinese)
Lü, X., Huang, D. (2021). Foundations of Statistics for Data Science. Renmin University of China Press. (in Chinese)