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Journal Papers

  1. Hu, L.S., Ning, S., Eschbacher, J.M., Baxter, L.C., Gaw, N., ,& Li, J., Radiogenomics to Characterize Regional Genetic Heterogeneity in Glioblastoma. Neuro-Oncology (impact factor: 7.371), in press.
  2. Zou, N., Li, J., “Modeling and Change Detection of Dynamic Network Data by a Network State Space Model,IIE Transactions, in press.
  3. Chong, C., Gaw, N., Fu, Y., Li, J., Wu, T., Schwedt, T., 2016, “Migraine Classification Using Magnetic Resonance Imaging Resting-State Functional Connectivity Data”, Cephalalgia (impact factor: 6.052). 0333102416652091. (This paper received the Harold Wolff-John Graham Award from the American Academy of Neurology.)
  4. Zou, N., Baydogan, M., Zhu, Y., Wang, W., Zhu, J., Li, J., 2015, “A Transfer Learning Approach for Predictive Modeling of Degenerate Biological Systems,” Technometrics, 55(3):362-373.
  5. Hu, L. S., Ning, S., Eschbacher, J. M., Gaw, N., Dueck, A. C., Smith, K. A., ... & Li, J., 2015, Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma,” PloS one, 10(11): e0141506.
  6. Titov, N., Diehl-Schmid, J., Shi, K., Perneczky, R., Zou, N., Förster, S., Grimmer, T., Li, J., Drzezga, A., Yakushev, I. “Metabolic Connectivity for Differential Diagnosis of Dementing Disorders.” 2015. Journal of Cerebral Blood Flow & Metabolism (impact factor: 4.929). 0271678X15622465.
  7. Schwedt, T., Chong, C., Gaw, N., Fu, Y., Wu, T., Li, J., 2015, “Accurate Classification of Chronic Migraine via Brain Magnetic Resonance Imaging”, Headache (impact factor: 2.961), 55(6):762-77. (This paper received the Harold G. Wolff Lecture Award from the American Headache Society.)

8.     Huang, S., Li, J., Lamb, G., Schmitt, M., and Fowler, J., 2014, “Multi-data Fusion for Enterprise Quality Improvement by a Multilevel Latent Response Model,” IIE Transactions, 46(5), 512-525.

  1. Zou, N., Chetelat, G., Baydogan, M., Li, J., Fischer, F., Titov, D., Dukart, J., Fellgiebel, A., Schreckenberger, M., Yakushev, I., 2014, “Metabolic Connectivity as Index of Verbal Working Memory, Journal of Cerebral Blood Flow & Metabolism (impact factor: 4.929)., 35:1122-1126.

10.  Li, M., Liu, J., Li, J., Kim, B., 2014, “Bayesian Modeling of Multi-state Hierarchical Systems with Multi-level Information Aggregation,Reliability Engineering & System Safety, 124, 158-164.

11.  Huang, S., Li, J., Ye, J., Fleisher, A., Chen, K., Wu, T., and Reiman, E., 2013, “A Sparse Structure Learning Algorithm for Bayesian Network Identification from High-Dimensional Data,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(6), 1328-1342.

12.  Inman, R.R., Blumenfeld, D.E., Huang, N., Li, J., and Li, J., 2013, “Survey of Recent Advances on the Interface between Production System Design and Quality,” IIE Transactions, 45(6), 557-574.

  1. Huang, S., Li, J., Chen, K., Wu, T., Ye, J., Wu, X., and Li, Y, 2012, "A Transfer Learning Approach for Network Modeling," IIE Transactions, 44(11), 1-17. (This paper received the IIE Transactions Best Paper Award.)

14.  Lyon, J., Pan, R., and Li, J., 2011, "National Evaluation of the Effect of Graduated Driver Licensing Laws on Teenager Fatality and Injury Crashes," Journal of Safety Research, 43(1), 29-37.

15.  Ye, J., Wu, T., Li, J., and Chen, K., 2011, “Machine Learning Approaches for the Neuroimaging Study of Alzheimer’s Disease,” IEEE Computer, April, 99-101.

16.  Li, J., and Jin, J., 2010, “Optimal Sensor Allocation by Integrating Causal Models and Set-Covering Algorithms,” IIE Transactions, 42(8), 564-576. (This paper received Best Paper Award in Industrial Engineering Research Conference (IERC) 2008.)

17.  Li, J., and Huang, S., 2010, “Regression-based Process Monitoring with Consideration of Measurement Errors,” IIE Transactions, 42(2), 146-160. (This paper was selected as a Feature Article by IIE Magazine.)

18.  Huang, S., Li, J., Sun, Li., Ye, J., Fleisher, A., Wu, T., Chen, K., and Reiman, E., 2010, “Learning Brain Connectivity of Alzheimer’s Disease by Sparse Inverse Covariance Estimation,” NeuroImage, 50, 935-949.

19.  Huang, S., Pan, R., and Li, J., 2010, “A Graphical Technique and Penalized Likelihood Method for Identifying and Estimating Infant Failures,” IEEE Transactions on Reliability, 59(4), 650-660.

20.  Li, J., Xie, H., and Jin, J., 2010, “Optimal Process Adjustment by Integrating Production Data and Design of Experiments,” Quality and Reliability Engineering International, 27(3), 327-336.

21.  Jin, J. and Li, J., 2009, “Multiscale Mapping of Aggregated Signal Features to Embedded Time-Frequency Localized Operations Using Wavelets,” IIE Transactions, 41(7), 615-625. (This paper was selected as a Feature Article by IIE Magazine.)

22.  Li, J., Jin, J., and Shi, J., 2008, “Causation-based T2 Decomposition for Multivariate Process Monitoring and Diagnosis,” Journal of Quality Technology, 40(1), 46-58. (This paper received Best Paper Award in Industrial Engineering Research Conference (IERC) 2006.)

23.  Li, J., Huang, K.Y., Jin, J., and Shi, J., 2008, “A Survey on Statistical Methods for Health Care Fraud Detection,” Health Care Management Science, 11, 275-287.

24.  Li, J., Shi, J., and Satz, D., 2008, “Modeling and Analysis of Disease and Risk Factors through Learning Bayesian Network from Observational Data,” Quality and Reliability Engineering International, 24, 291-302.

25.  Li, J., and Shi, J., 2007, “Knowledge Discovery from Observational Data for Process Control using Causal Bayesian Networks,” IIE Transactions, 39 (6), 681 – 690.

  1. Li, J., Shi, J., and Chang, T.S., 2007, “On-line Seam Detection in Rolling Processes using Snake Projection and Discrete Wavelet Transform,” ASME Transactions, Journal of Manufacturing Science and Engineering, 129(5), 926-933.

27.  Lin, G., Li, J., Hu, S. J., and Cai, W., 2007, “A Computational Response Surface Study of 3D Aluminum Hemming using Solid-to-Shell Mapping,” ASME Transactions, Journal of Manufacturing Science and Engineering, 129(2), 360-368.

28.  Jin, R., Li, J., and Shi, J., 2007, “Quality Prediction and Control in Rolling Processes using Logistic Regression,” Transactions of NAMRI/SME, 35, 113-120.

29.  Liu, J., Li, J., and Shi, J., 2005, “Integration of Engineering Knowledge Driven Cause-Effect Modeling and Statistical Analysis for Multi-Operational Machining Process Diagnosis,” Transactions of NAMRI/SME, 33, 65-72.

 

NIPS and KDD Conference Papers

30.  Huang, S., Li, J., Ye, J., Wu, T., Chen, K., Fleisher, A., Reiman, E., “Identifying Alzheimer’s Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis,” The 25th Annual Conference on Neural Information Processing Systems (NIPS 2011) (paper acceptance rate 4.8%) December 13-15, 2011, Granada, Spain. Supplemental Material.

31.  Huang, S., Li, J., Ye, J., Fleisher, A., Chen, K., and Wu, T., Reiman, E., “Brain Effective Connectivity  modeling for Alzheimer’s Disease by Sparse Bayesian Network,” The 17th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2011) (paper acceptance rate 17.5%), August 21-24, 2011, San Diego, USA.

32.  Huang, S., Li, J., Sun, Li., Ye, J., Chen, K., and Wu, T., Fleisher, A., and Reiman, E., "Learning Brain Connectivity of Azheimer's Disease from Neuroimaging Data," The 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009) (paper acceptance rate 8%), December 7-9, 2009, Vancouver, B.C., Canada. Supplemental Material.

33.  Sun, L., Patel, R., Liu, J., Chen, K., Wu, T., Li, J., Reiman, R., and Ye, J., 2009, “Mining Brain Region Connectivity for Alzheimer's Disease Study via Sparse Inverse Covariance Estimation,” The 15th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2009) (paper acceptance rate 9.8%), June 28-July 1, 2009, Paris, France.

34.  Ye, J., Chen, K., Wu, T., Li, J., Zhao, Z., Patel, R., Bai, M., Janardan, R., Liu, H., Alexander, G., and Reiman, E., 2008, “Heterogeneous Data Fusion for Alzheimer’s Disease Study,” The 14th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2008) (paper acceptance rate 14%), August 24-27, 2008, Las Vegas, USA.