Publications
Chu, T., Liu, J., Zhu, J. and Wang, H. (2022). Spatio-Temporal Expanding Distance Asymptotic Framework for Locally Stationary Processes. Sankhya A, 84, 689-713.
Liu, J., Chu, T., Zhu, J. and Wang, H. (2022). Large Spatial Data Modeling and Analysis: A Krylov Subspace Approach. Scandinavian Journal of Statistics, 49, 1115-1143
Liu, J., Chu, T., Zhu, J. and Wang, H. (2022). Long term behavior of incomplete and time varying product ratings. Statistics and Probability Letters, 184, 109387.
Zhang, L., Zhou, W. and Wang, H. (2022). Non-Asymptotic Properties of Spectral Decomposition of Large Gram-Type Matrices and Applications. Bernoulli, 28, 1224-1249.
Vaca, F.E., Li, K., Gao, X., Zagnoli, K., Wang, H., Haynie, D., Fell, J.C., Simons-Morton, B., Romano, E. (2021). Time to Licensure for Driving Among U.S. Teens: Survival Analysis of Interval-Censored Survey Data. Traffic Injury Prevention, 22, 431-436.
Zhang, L., Zhou, W. and Wang, H. (2021). A Semiparametric Latent Factor Model for Large Scale Temporal Data with Heteroscedasticity. Journal of Multivariate Analysis, 186, 104786.
Liu, J., Chu, T., Zhu, J. and Wang, H. (2021). Semiparametric Method and Theory for Continuously Indexed Spatio-Temporal Processes. Journal of Multivariate Analysis, 183, 104735.
Kokoszka, P., Nguyen, H., Wang, H. and Yang, L. (2020). Statistical and probabilistic analysis of interarrival and waiting times of Internet2 anomalies. Statistical Methods & Applications, 29, 724-744.
Zheng, X., Duan D., Yang, L., Wang, H. (2020). Decomposed Iterative Optimal Power Flow with Automatic Regionalization. Energies, 13, 4987.
Fang, L., Wang, H., Cheng, X., Yang, L. and Cui, S. (2020). Mobile Privacy: Scalable Ensemble Matching for User Identification Attacks. IEEE Access, 8, 97243-97257.
Tu, C.Y., Park, J. and Wang, H. (2020). Estimation of Functional Sparsity in Nonparametric Varying Coefficient Models for Longitudinal Data Analysis. Statistica Sinica, 29, 439-465.
Chu, T., Zhu, J. and Wang, H. (2019). Semiparametric Modeling with Nonseparable and Nonstationary Spatio-Temporal Covariance Functions and Its Inference. Statistica Sinica, 29, 1233-1252.
Fang, L., Cheng, X., Wang, H. and Yang, L. (2019). Idle Time Window Prediction in Cellular Networks with Deep Spatiotemporal Modeling. IEEE Journal on Selected Areas in Communications, 37, 1441-1454.
Fang, L., Cheng, X., Yang, L. and Wang, H. (2018). Location Privacy in Mobile Big Data: User Identifiability via Habitat Region Representation. Journal of Communications and Information Networks, 3, 31-38.
Wang, F. and Wang, H. (2018). Modeling Non-stationary Multivariate Time Series of Counts via Common Factors. Journal of the Royal Statistical Society, Series B, 80, 769-791.
Sienkiewicz, E. and Wang, H. (2018). Pareto Quantiles of Unlabeled Tree Objects. The Annals of Statistics, 46, 1513-1540.
Fang, L., Cheng, X., Wang, H. and Yang, L. (2018). Mobile Demand Forecasting via Deep Graph-Sequence Spatiotemporal Modeling in Cellular Networks. IEEE Internet of Things Journal, 5, 3091-3101.
Meyer, M.C., Kim, S. and Wang, H. (2018). Convergence rates for constrained regression splines. Journal of Statistical Planning and Inference, 193, 179-188.
Santamaria, I., Schard, L.L., Via, J., Wang, H. and Wang, Y. (2017). Passive Detection of Correlated Subspace Signals in Two MIMO Channels. IEEE Transactions on Signal Processing, 65, 5266-5280.
Sienkiewicz, E., Song, D., Breidt, F.J. and Wang, H. (2017). Sparse Functional Dynamical Models --- a Big Data Approach. Journal of Computational and Graphical Statistics, 26, 319-329. (Web)
Lin, Z., Cao, J., Wang, L. and Wang, H. (2017). Locally Sparse Estimator for Functional Linear Regression Models. Journal of Computational and Graphical Statistics, 26, 306-318
Koehler, K., Zhu, J., Wang, H. and Peters, T. (2017). Sampling Strategies for Accurate Hazard Mapping of Noise and Other Hazards Using Short-Duration Measurements. Annals of Work Exposures and Health, 61, 183-194.
Ludwig, G., Chu, T., Zhu, J., Wang, H. and Koehler, K. (2017). Static and Roving Sensor Data Fusion for Spatio-Temporal Hazard Mapping with Application to Occupational Exposure Assessment. The Annals of Applied Statistics, 11, 139-160.
Wang, H. and Kai, B. (2015). Functional Sparsity: Global versus Local. Statistica Sinica, 25, 1337-1354.
Hayne, S., Wang, H. and Wang, L. (2015). Modeling Reputation as a Time-Series: Evaluating the Risk of Purchase Decisions on eBay. Decision Sciences, 46, 1077-1107.
Lake, K., Zhu, J., Wang, H., Volckens, J. and Koehler, K. (2015). Effects of Data Sparsity and Spatiotemporal Variability on Hazard Maps of Workplace Noise. Journal of Occupational and Environmental Hygiene, 12, 256-265.
Wang, J., Opsomer, J.D. and Wang, H. (2014). Bagging nondifferentiable estimators in complex surveys. Survey Methodology, 40, 189-209.
Sienkiewicz, E. and Wang, H. (2014). Discussion: OODA of Graph and Tree Structured Data. Biometrical Journal, 56, 778-780.
Chu, T., Wang, H. and Zhu, J. (2014). On Semiparametric Inference of Geostatistical Models via Local Karhunen-Loève Expansion. Journal of the Royal Statistical Society, 76, 817-832.
Wang, Y., Wang, H. and Scharf, L.L. (2014). The Geometry of Fusion Inspired Channel Design. Signal Processing, 99, 136-146.
Wang, Y., Wang, H. and Scharf, L.L. (2014). Optimum Compression of a Noisy Measurement for Transmission over a Noisy Channel. IEEE Transactions on Signal Processing, 62, 1279-1289.
Song, D., Wang, H., Tu, C.Y., Marmarelis, V.Z., Hampsone, R.E., Deadwyler, S.A., and Berger, T.W. (2013). Identification of Sparse Neural Functional Connectivity using Penalized Likelihood Estimation and Basis Functions. Journal of Computational Neuroscience, 35, 335-357.
Chang, H.-W., Iyer, H., Bullitt, E. and Wang, H. (2013). Generalized Linear Mixed Models for Branching Probabilities of Brain Artery Systems. Model Assisted Statistics and Applications, 8, 121-133.(Web)
Wang, Y., Marron, J.S., Aydin, Ladha, A., Bullitt, E. and Wang, H. (2012). A Nonparametric Regression Model With Tree-Structured Response. Journal of the American Statistical Association, 107, 1272-1285. (Web)
Tu, C.Y., Song, D., Breidt, J.F., Berger, T.W. and Wang, H. (2012). Functional Model Selection for Sparse Binary Time Series with Multiple Inputs. Economic Time Series: Modeling and Seasonality, 477-497.
Hayne, S., Wang, H. and Mendonca, S. (2012). eBay as the "Terminator": Determining User Suspension from Feedback Ratings. Journal of Organizational Computing and Electronic Commerce, 22, 160-183.
Aue, A., Lee, T.C.M. and Wang, H. (2012). Local Bandwidth Selection via Second Derivative Segmentation. Electronic Journal of Statistics, 6, 478-500.
Aydin, B., Pataki, G., Wang, H., Ladha, A., Bullitt, E. and Marron, J.S. (2012). New Approaches to Principal Component Analysis. Statistics in Biosciences, 4, 132-156.
Chu, T., Zhu, J. and Wang, H. (2011). Penalized Maximum Likelihood Estimation and Variable Selection in Geostatistics. The Annals of Statistics, 39, 2607-2625. (Technical Report)
Aydin, B., Pataki, G., Wang, H., Ladha, A., Bullitt, E. and Marron, J.S. (2011). Visualizing the Structure of Large Trees. Electronic Journal of Statistics, 5, 405-420. (Web)
Al-Qawasmeh, A.M., Maciejewski, A.A., Wang, H., Smith, J., Siegel, H.J., and Potter, J. (2011). Statistical Measures for Quantifying Task and Machine Heterogeneities. The Journal of Supercomputing, special Issue on Advances in Parallel and Distributed Computing, 57, 34-50.
Hayne, S., Bugbee, B. and Wang, H. (2010). Bidder Behaviours on eBay: Collectibles and Commodities. Electronic Markets, 20, 95-104.
Aydin, B., Pataki, G., Wang, H., Bullitt, E. and Marron, J.S. (2009). A Principal Component Analysis for Trees. The Annals of Applied Statistics, 3, 1597-1615. (Web)
Wang, H., Cao, X. and Iyer, H. (2009). Estimation of the Proportion of Differentially Expressed Genes using Hellinger Distance. Statistics in Biosciences, 1, 246-267.
Wang, H. and Zhu, J. (2009). Variable Selection in Spatial Regression via Penalized Least Squares. The Canadian Journal of Statistics, 37, 607-624.
Sonderegger, D., Wang, H., Huang, Y. and William, C. (2009). Effects Of Measurement Error On The Strength Of Concentration-Response Relationships In Aquatic Toxicology. Ecotoxicology, 18, 824-828.
Wang, H. (2009). Measures of Agreement for Vectorcardiography Data. Statistics in Medicine, 28, 1093-1107.
Sonderegger, D., Wang, H., William, C. and Noon, B. (2009). Using SiZer to detect thresholds in ecological data. Frontiers in Ecology and the Environment, 7, 190-195.
Wang, H. and Lee, T. C. M. (2008). Extraction of Curvilinear Features from Noisy Point Patterns using Principal Curves. Pattern Recognition Letters, 29, 2078-2084.
Wang, H. and Marron, J. S. (2007). Object Oriented Data Analysis: Sets of Trees. The Annals of Statistics, 35, 1849-1873. (Web)
Wang, H. and Iyer, H. (2007). Application of Local Linear Embedding to Nonlinear Exploratory Latent Structure Analysis. Psychometrika, 72, 199-225.
Wang, H. and Ranalli, M. G. (2007). Low-rank Smoothing Splines on Complex Domains. Biometrics, 63, 209-217.
Wang, H. and Lee, T. C. M. (2006). Automatic Parameter Selection for a k-Segments Algorithm for Computing Principal Curves. Pattern Recognition Letters, 27, 1142-1150.
Refereed Proceedings/Transactions
Shirazi, H., Pickard, W., Ray, I. and Wang, H. (2022). Towards Resiliency of Heavy Vehicles through Compromised Sensor Data Reconstruction. Proceedings of the Twelveth ACM Conference on Data and Application Security and Privacy, 276-287.
Kattadige, C., Muramudalige, S.R., Choi, K.N., Jourjon, J., Wang, H., Jayasumana, A., and Thilakarathna, K. (2021). VideoTrain: A Generative Adversarial Framework for Synthetic Video Traffic Generation. 2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM).
McAndrew, R., Hayne, S. and Wang, H. (2020). An Unsupervised Approach to DDoS Attack Detection and Mitigation in Near-Real Time. Proceedings of the 53rd Hawaii International Conference on System Sciences, 6466-6475.
McAndrew, R., Hayne, S. and Wang, H. (2019). The Benefits of a Functional Approach to Detecting and Mitigating a DDoS Attack. Fourteenth International Conference on Internet Monitoring and Protection (ICIMP).
McAndrew, R., Hayne, S. and Wang, H. (2019). Comparison of Supervised and Unsupervised Learning for Detecting Anomalies in Network Traffic. Proceedings of the 52nd Hawaii International Conference on System Sciences, 7136-7145.
McAndrew, R., Gharaibeh, M., Wang, H., Hayne, S. and Papadopoulos, C. (2017). A Functional Ap- proach to Scanner Detection. Proceedings of the Asian Internet Engineering Conference (AINTEC), 38-45.
Wang, Y. , Scharf, L. L., Santamaria, I. and Wang, H. (2016). Canonical Correlations for Target Detection in a Passive Radar Network. Asilomar Conference on Signals, Systems, and Computers, 1159-1163.
Wang, Y., Wang, H. and Scharf, L.L. (2013). Scaled Canonical Coordinates for Compression and Transmission of Noisy Sensor Measurements. Asilomar Conference on Signals, Systems, and Computers, 409-413.
Wang, Y., Wang, H. and Scharf, L.L. (2013). Fusion Inspired Channel Design. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 5392-5396.
Song, D., Wang, H., and Berger, T.W. (2010). Estimating Sparse Volterra Models using Group L1-Regularization. Proceedings of the 32nd Annual International Conference of the IEEE EMBS, 4128-4131.
Wang, H. and Lee, T. C. M. (2007). Curvilinear Feature Extraction for Noisy Point Pattern Images. IEEE International Conference on Multimedia & Expo, 1635-1638.
Lee, T. C. M. and Wang, H. (2006). On a k-Segments Algorithm for Computing Principal Curves. Seventh IEEE Southwest Symposium on Image Analysis and Interpretation, 183-187.
Technical Reports
Chu, T., Zhu, J. and Wang, H. (2011). Penalized Maximum Likelihood Estimation and Variable Selection in Geostatistics. Technical Report, 2011/2, Department of Statistics, Colorado State University.
Wang, H. (2008). Measures of Agreement for Rotation Matrices with Application to Vectorcardiography Data. Technical Report, 2008/10, Department of Statistics, Colorado State University.
Aue, A., Lee, T.C.M. and Wang, H. (2008). Local Bandwidth Selection via Second derivative Segmentation. Technical Report, 2008/7, Department of Statistics, Colorado State University.
Cao, X.,Wang, H., Hess, A., Iyer, H. (2007) Hellinger Distance Estimation of Positive False Discovery Rate – An Application to Microarray Data Analysis. Technical Report, 2007/4, Department of Statistics, Colorado State University
Book Review
Wang, H. (2009). Review of “Nonlinear Dimensionality Reduction”. Biometrics, 65, 665.
B.S., Nankai University, Tianjin, China
Ph.D., University of North Carolina, Chapel Hill
Object Oriented Data Analysis
Spatial Statistics
Information Fusion
Statistical Analysis on Networks
Computational Neuroscience
216 Statistics Building
Department of Statistics
Colorado State University
Fort Collins, CO80523
Email: wanghn@stat.colostate.edu
Voice: 970-491-2449
My research has been supported by NSF grants DMS-0706761, DMS-0854903, DMS-1106975, DMS-1521746, DMS-1737795, DMS-1923142, CNS-1932413 and DMS-2123761 as well as grants with other collaborators.