Selected Peer-Reviewed Publications

Methodological development

1. Wu Y, Huang C, and Srivastava A (2024+). Rejoinder on: Shape-based functional data analysis. Test, accepted.

2. Shan Y, Huang C, Li Y, and Zhu H (2024+). Merging or Ensembling: Integrative Analysis in Multiple Neuroimaging  Studies. Biometrics, accepted.

3. Zhou X, Ding S, Wang J, Liu R, Kong L, and Huang C (2024+). Distribution-on-scalar single index quantile regression model for handling tumor heterogeneity. Technometrics, accepted.

4. Wu Y, Huang C, and Srivastava A (2024+). Shape-based functional data analysis (discussion paper). Test, accepted.

5. Dogra, H, Ding S, Yeon, M, Liu R, and Huang C (2023). Confounder adjustment in shape-on-scalar regression model: corpus callosum shape alterations in Alzheimer’s disease. Stats, 6, 980-989.

6. Huang, C, Ding S, Li S, and Liu R (2022). LMFE: Learning based Multi-scale Feature Engineering in Partial Discharge Detection. IEEE Transactions on Neural Networks and Learning Systems, 1-9, 36449579.

7. Tu W, Fu F, Kong L, Jiang B, Cobzas D and Huang C (2022). Low-Rank Plus Sparse Decomposition of fMRI Data With Application to Alzheimer's Disease. Frontiers in Neuroscience, 16:826316.

8. Huang C and Zhu H (2022). Functional hybrid factor regression model for handling heterogeneity in imaging studies. Biometrika, 109, 1133–1148.

9. Huang C, Xu Z, Shen Z, Luo T, Li T, Nissman D, Nelson A, Golightly Y, Niethammer M, and Zhu H (2022). DADP: Dynamic abnormality detection and progression for longitudinal knee magnetic resonance images from the Osteoarthritis Initiative. Medical Image Analysis, 77, 102343.

10. Huang C, Srivastava A, and Liu R (2021). Geo-FARM: Geodesic Factor Regression Model for Misaligned Pre-shape Responses in Statistical Shape Analysis. 2021 Conference on Computer Vision and Pattern Recognition (CVPR), 11496-11505. (accepted as oral presentation, acceptance rate < 17%)

11. Zhong L, Li T, Shu H, Huang C, Johnson J, Schomer D, Liu H, Feng Q, Yang W, and Zhu H (2020). (TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients. NeuroImage, 223, 117368.

12. Huang C, Thompson P, Wang Y, Yu Y, Zhang J, Kong D, Colen R, Knickmeyer R, and Zhu H (2017). FGWAS: Functional genome wide association analysis. NeuroImage, 159, 107-121.

13. Li J, Huang C, and Zhu H (2017). A functional varying-coefficient single index model for functional response data. Journal of the American Statistical Association, 112, 1169-1181.

14. Zhang J, Huang C, Knickmeyer R, Gilmore J, Ibrahim J, and Zhu H (2017). HFPRM: hierarchical functional principal regression model for diffusion tensor image bundle statistics. Information Processing in Medical Imaging, 478-489. (acceptance rate < 32%)

15. Hyun J, Li Y, Huang C, Styner M, Lin W, and Zhu H (2016). STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data. NeuroImage, 134, 550-562.

16. Huang C, Styner M, and Zhu H (2015). Clustering high-dimensional landmark-based two-dimensional shape data. Journal of the American Statistical Association, 110, 946-961.

17. Huang C, Shan L, Charles C, Wirth W, Niethammer M, and Zhu H (2015). Diseased region detection of longitudinal knee magnetic resonance imaging data. IEEE Transactions on Medical Imaging, 34, 1914-1927. (Earlier version of this manuscript won 2014 ASA Statistics in Imaging Section Student Paper Award)

18. Huang M, Nichols T, Huang C, Yang Y, Lu Z, Feng Q, Knickmeyer R, and Zhu H (2015). FVGWAS: fast voxelwise genome wide association analysis of large-scale imaging genetic data. NeuroImage, 118, 613-627. (Earlier version of this manuscript won 2015 ENAR Distinguished Student Paper Award)

19. Huang C and Lin J (2014). Modified maximum spacings method for generalized extreme value distribution and applications in real data analysis. Metrika, 77, 867-894.

20. Huang C, Lin J, and Ren Y (2013). Testing for the shape parameter of generalized extreme value distribution based on the Lq-likelihood ratio statistic. Metrika, 76, 641-671.

21. Zhang K, Lin J, and Huang C (2013). Some new results on weighted geometric mean for copulas. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 21, 277-288.

22. Huang C, Shan L, Charles C, Niethammer M, and Zhu H (2013). Diseased region detection of longitudinal knee MRI data. Information Processing in Medical Imaging, 632-643. (acceptance rate < 32%) 

23. Yang Y, Lin J,Huang C, and Ma X (2012). The finite-time ruin probability in two non-standard renewal risk models with constant interest rate and dependent subexponential claims. Journal of the Korean Statistical Society, 41, 213-224.

24. Huang C, Lin J, and Ren Y (2012). Statistical inferences for generalized Pareto distribution based on interior penalty function algorithm and bootstrap methods and applications in analyzing stock data. Computational Economics, 39, 173-193.

25. Zhuang Q, Lin J, and Huang C (2012). Fuzzy statistical analysis of multiple regression with crisp and fuzzy covariates and applications in analyzing economic data of China. Computational Economics, 39, 29-49.

26. Lin J, Huang C, Zhuang Q, and Zhu L (2010). Estimating generalized state density of near-extreme events and its applications in analyzing stock data. Insurance Mathematics & Economics, 47, 13-20. 

Real applications

1. Huang C, Liu R, Zhao B, and Kong L (2023). Editorial: Modern Statistical Learning Strategies in Imaging Genetics, volume II. Frontiers in Neuroscience, 17:1337411.

2. Das A, Ding S, Liu R, and Huang C (2023). Quantifying the growth of glioblastoma tumors using multimodal MRI brain images. Cancers, 15(14):3614.

3. Wei M, Liu R, Wang Y, and Huang C (2023). Deep zero-inflated negative binomial model and its application in scRNA-seq data integration. SoutheastCon 2023. Orlando, FL, USA, 901-905.

4. Huang C, Liu R, Zhao B, and Kong L (2022). Editorial: Modern Statistical Learning Strategies in Imaging Genetics. Frontiers in Neuroscience, 16:957304.

5. Kuhn T, Jin Y, Huang C, Kim Y, Nir T, Gullett J, Jones J, Chung C, Dang B, Singer E, Shattuck D, Jahandshad N, Bookheimer S, Hinkin C, Zhu H, and Thompson P (2019). The joint effect of aging and HIV infection on microstructure of white matter bundles. Human Brain Mapping, 40, 4370-4380.

6. Schilling KG, Nath V, Hansen C, Parvathaneni P, Blaber J, Gao Y, Neher P, Aydogan D B, Shi Y, Ocampo-Pineda M, Schiavi S, Daducci A, Girard G, Barakovic M, Rafael-Patino J, Romascano D, Rensonnet G, Pizzolato M, Bates A, Fischi E, Thiran JP, Canales-Rodriguez EJ, Huang C, Zhu H, Zhong L, Cabeen R, Toga AW, Rheault F, Theaud G, Houde JC, Sidhu J, Chamberland M, Westin CF, Dyrby TB, Verma R, Rathi Y, Irfanoglu MO, Thomas C, Pierpaoli C, Descoteaux M, Anderson AW, and Landman BA (2019). Limits to anatomical accuracy of diffusion tractography using modern approaches. NeuroImage, 185, 1-11.

7. Shoukri B, Prieto JC, RuellasA, Yatabe M, Sugai J, Styner M, Zhu H, Huang C, Paniagua B, Aronovich S, Ashman L, Benavides E, de Dumast P, Ribera NT, Mirabel C, Michoud L, Allohaibi Z, Ioshida M, Bittencourt L, Fattori L, Gomes LR, and Cevidanes L (2019). Minimally invasive approach for diagnosing TMJ Osteoarthritis. Journal of Dental Research, 98, 1103-1111.

8. Zhao B, Ibrahim JG, Li Y, Li T, Wang Y, Shan Y, Zhu Z, Zhou F, Zhang J, Huang C, Liao H, Yang L, Thompson PM, and Zhu H (2019). Heritability of regional brain volumes in large-scale neuroimaging and genetic studies. Cerebral Cortex, 29, 2904-2914.

9. Michoud L, Huang C, Yatabe M, Ruellas A, Ioshida M, Paniagua B, Styner M, Gon alves J, Bianchi J, Cevidanes L, and Prieto J (2019). A web-based system for statistical shape analysis in temporomandibular joint Osteoarthritis. Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109530T.

10. de Dumast P, Mirabel C, Cevidanes L, Ruellas A, Yatabe M, Ioshida M, Ribera NT, Michoud L, Gomes L, Huang C, Zhu H, Muniz L, Shoukri B, Paniagua B, Styner M, Pieper S, Budin F, Vimort JB, Pascal L, and Prieto JC (2018). A web-based system for neural network based classification in temporomandibular joint osteoarthritis. Computerized Medical Imaging and Graphics, 67, 45-54.

11. Elhalawani H, Lin TA, Volpe S, Mohamed A SR, White AL, Zafereo J, Wong AJ, Berends JE, AboHashem S, Williams B, Aymard JM, Kanwar A, Perni S, Rock CD, Cooksey L, Campbell S, Yang P, Nguyen K, Ger RB, Cardenas CE, Fave XJ, Sansone C, Piantadosi G, Marrone S, Liu R, Huang C, Yu K, Li T, Yu Y, Zhang Y, Zhu H, Morris JS, Baladandayuthapani V, Shumway JW, Ghosh A, Pohlmann A, Phoulady HA, Goyal V, Canahuate G, Marai GE, Vock D, Lai SY, Mackin DS, Court LE, Freymann J, Farahani K, Kaplathy-Cramer J, and Fuller CD (2018). Machine learning applications in head and neck radiation oncology: lessons from open-source radiomics challenges. Frontiers in oncology, 8, 294.

12. Liu R, Huang C, Li T, Yang L, and Zhu H. Statistical disease mapping for heterogeneous neuroimaging studies (2018). 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 1415-1418.

13. Vicory J, Pascal L, Hernandez P, Fishbaugh J, Prieto J, Mostapha M, Huang C, Shah H, Hong J, Liu Z, Michoud L, Fillion-Robin J C, Gerig G, Zhu H, Pizer SM, Styner M, and Paniagua B (2018). SlicerSALT: shape anaLysis toolbox. International Workshop on Shape in Medical Imaging, 65-72.

14. Jin Y, Huang C, Daianu M, Zhan L, Dennis E, Reid R, Jack C, Zhu H, and Thompson P (2017). 3D tract-specific local and global analysis of white matter integrity in Alzheimer’s disease. Human Brain Mapping, 38, 1191-1207.

15. Yu K, Zhang Y, Yu Y, Huang C, Liu R, Li T, Yang L, Morris J S, Baladandayuthapani V, and Zhu H (2017). Radiomic analysis in prediction of Human Papilloma Virus status. Clinical and Translational Radiation Oncology, 7, 49-54.

16. Seyednasrollah F. et al. including Huang C (2017). A DREAM Challenge to Build Prediction Models for Short-Term Discontinuation of Docetaxel in Metastatic Castration-Resistant Prostate Cancer. JCO clinical cancer informatics, 1, 1-15.

17. Guinney J. et al. including Huang C (2017). Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data. The Lancet Oncology, 18, 132-142.

18. Allen GI. et al. including Huang C (2016). Crowdsourced estimation of cognitive decline and resilience in Alzheimer’s disease. Alzheimer’s & Dementia, 12, 645-653.