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Rong Chen, PhD

Academic Title:

Assistant Professor

Primary Appointment:

Diagnostic Radiology and Nuclear Medicine


100 N Greene St, 411

Phone (Primary):




Education and Training

Southeast University, China, B.S. 1996, Biomedical Engineering
The Graduate School of Chinese Academy of Sciences, China, M.S. 1999, Electrical Engineering
Washington State University, Pullman, WA, Ph.D. 2003, Electrical and Computer Engineering
University of Pennsylvania, Philadelphia, PA, Postdoctoral Researcher, 2005, Radiology
University of Pennsylvania, Philadelphia, PA, M.T.R 2012, Translational Research


Dr. Chen has a strong background in computational neuroscience, machine learning, biomedical data analysis, and translational research. His research focuses on leveraging machine learning, deep learning, and computational modeling to understand the relationship between brain and behavior, leading to novel therapeutic concepts for brain disorders and brain-inspired AI. He has 20 years of experience in advanced modeling, algorithm, and software development. He has released two open-source biomedical data mining software packages on NITRC: the GAMMA suite and Advanced Connectivity Analysis. Dr. Chen is a senior member of IEEE. He is an editorial member of Frontier of computational neuroscience, Frontiers of neurorobotics, and the Open Neuroimaging journal.

Research/Clinical Keywords

Computational neuroscience, machine learning, translational medicine, biomedical data analysis

Highlighted Publications


Barbera G, Liang B, Zhang LF, Gerfen CR, Culurciello E, Chen R#, Li Y#, Lin DT#. Spatially Compact Neural Clusters In The Dorsal Striatum Encode Locomotion Relevant Information. 92(1):202-213, Neuron. 2016. # co-corresponding authors.


Chen, R., Arkuszewski M, Krejza J., Zimmerman R., Herskovits, E. H., Melhem E. R. A prospective longitudinal brain-morphometry study of children with sickle-cell disease, AJNR, 36(2), 403-410, 2015.


Chen R, Resnick S, Davatzikos C, Herskovits EH, Dynamic Bayesian network modeling for longitudinal brain morphometry. NeuroImage. 59(3):2330-2338, 2011.


Chen R, Herskovits EH, Graphical-Model-based Morphometric Analysis. IEEE Transaction on Medical Imaging. Vol 24, 1237-1248, October 2005.


Chen R, Sivakumar K, Kargupta H, Collective Mining of Bayesian Networks from Distributed Heterogeneous Data, Knowledge and Information Systems. 6(2):164-187, 2004.


Additional Publication Citations

  1. Liang B., Zhang LF., Barbera G., Fang WT., Zhang J., Chen XC, Chen R., Li Y., LinDT., Distinct and Dynamic ON and OFF Neural Ensembles in the Prefrontal Cortex Code Social Exploration, Neuron, in press, 2018
  2. Chen R.*, Lin DT., Decoding brain states based on microcircuits, in press, IEEE CBS, 2018
  3. Qiu WL, Chen R., Chen X, Zhang HF, Song L, Cui WJ, Zhang JJ, Ye DD, Zhang YF, Wang ZQ, Oridonin-loaded and GPC1 Targeted Gold Nanoparticle for Multimodal Imaging and Therapy in Pancreatic Cancer, in press, International Journal of Nanomedicine, 2018
  4. Liang HJ., Chang L., Chen R., Oishi K., Ernst T., Independent and Combined Effects of Chronic HIV-Infection and Tobacco Smoking on Brain Microstructure, Journal of Neuroimmune Pharmacology, in press, 2018
  5. Yan T., Wang W., Yang L., Chen K., Chen R., Han Y., Rich club disturbances of the human connectome from subjective cognitive decline to Alzheimer’s disease, 8(2), Theranostics, 2018
  6. Naragum V., Jindal G., Miller T., Kole M., Shivashankar R., Merino J., Cole J., Chen R., Kohler N., Gandhi D., Functional Independence After Stroke Thrombectomy Using Thrombolysis in Cerebral Infarction Grade 2c, A New Aim of Successful Revascularization, World Neurosurgery, 2018
  7. Lee Y., Madayambath S., Liu YZ., Lin DT., Chen R., Bhattacharyya SS., Online Learning in Neural Decoding Using Incremental Linear Discriminant Analysis, IEEE International Conference on Cyborg and Bionic Systems, 2017
  8. Dreizin D., Bodanapally U., Boscak A., Tirada N., Issa G., Nascone J., Bivona L., Mascarenhas D., O’Toole R., Nixon E., Chen R., Siegel E., Development and validation of an MDCT-based prediction model for major arterial injury after blunt pelvic trauma incorporating segmented pelvic hematoma volume as a quantitative imaging biomarker, Radiology, in press, 2017
  9. Chen R.*, Zheng YJ, Nixon E, Herskovits E, Dynamic network model with continuous valued nodes for longitudinal brain morphometry, 155:605-611, NeuroImage, 2017
  10. Chen HJ#, Shi HB#, Jiang LF, Chen L, Chen R.*#, Disrupted topological organization of brain structural network associated with prior overt hepatic encephalopathy in cirrhotic patients, in press, European Radiology, 2017. # Co-corresponding authors.
  11. Jiao Y, Wang XH, Chen R, Tang TY, Zhu XQ, Teng GJ., Predictive models of minimal hepatic encephalopathy for cirrhotic patients based on large-scale brain intrinsic connectivity networks, Sep 14;7(1):11512, Sci Rep. 2017
  12. Barbera G, Liang B, Zhang LF, Gerfen CR, Culurciello E, Chen R*#, Li Y#, Lin DT#. Spatially compact neural clusters in the dorsal striatum encode locomotion relevant information. 92(1):202-213, Neuron. 2016. # Co-corresponding authors.
  13. Chen, R.*#, Krejza, J.#, Arkuszewski, M., Zimmerman, R., Herskovits, E., Melhem, E., Brain morphometric analysis predicts decline of intelligence quotient in children with sickle cell disease: a preliminary study, 62(1): 151-157, Advances in Medical Sciences, 2017. # Co-corresponding authors.
  14. Chen, R.*, Nixon, E., Herskovits, E. H., Advanced Connectivity Analysis (ACA): a large scale functional connectivity data mining environment, Neuroinformatics, 14(2): 191-9, 2016
  15. Wang Z*, Wu W, Liu Y, Wang T, Chen X, Zhang J, Zhou G, Chen R*. Altered cerebellar white matter integrity in patients with mild traumatic brain injury in the acute stage. PLoS One, 11(3), 2016
  16. Chen, R.*, Herskovits, E. H. and ADNI, Predictive structural dynamic network analysis, Journal of neuroscience methods, 245:58-63, 2015.
  17. Wang Q, Chen R, JaJa J, Jin Y, Hong LE. Herskovits EH, Connectivity-Based Brain Parcellation  - A Connectivity-Based Atlas for Schizophrenia Research, Neuroinformatics, 14(1):83-97, 2016
  18. Herskovits EH, Hong LE, Kochunov P, Sampath H, Chen R. Edge-Centered DTI Connectivity Analysis: Application to Schizophrenia. Neuroinformatics. 13(4):501-509, 2015
  19. Yang M, Yang YR, Li HJ, Lu XS, Shi YM, Liu B, Chen HJ, Teng GJ, Chen R, Herskovits EH. Combining diffusion tensor imaging and gray matter volumetry to investigate motor functioning in chronic stroke. PLoS One. May 12;10(5), 2015
  20. Chen, R.*, Arkuszewski M, Krejza J., Zimmerman R., Herskovits, E. H., Melhem E. R. A prospective longitudinal brain-morphometry study of children with sickle-cell disease, AJNR, 36(2), 403-410, 2015.
  21. Chen, HJ., Chen, R., Yang, M., Teng, GJ., Herskovits, E. H., Identification of Minimal Hepatic Encephalopathy in Cirrhotic Patients Based on White Matter Imaging and Bayesian Data Mining, AJNR, 36(3):481-7, 2015.
  22. Chen, R.*, Herskovits, E. H., Bayesian predictive modeling based on multidimensional connectivity profiling, Neuroradiol J. 28(1), 5-11, 2015
  23. Hickok, G., Rogalsky, C., Chen, R., Herskovits, E. H., Townsley, S., Hillis, A., Partially Overlapping Sensorimotor Networks Underlie Speech Praxis and Verbal Short-Term Memory: Evidence from Apraxia of Speech Following Acute Stroke, 8:649, Front. Hum. Neurosci. 2014.
  24. Chen, R.*, Herskovits, E. H., Examining the multifactorial nature of a cognitive process using Bayesian brain-behavior modeling. Comput Med Imaging Graph, 41:117-25, 2014.
  25. Liu, Y., Wang, T., Chen, X., Zhang, J., Zhou, G., Wang, Z.*, Chen, R.*, Tract-based Bayesian multivariate analysis of mild traumatic brain injury. Comput Math Methods Med. 2014.
  26. Arkuszewski, M., Krejza, J., Chen, R., Ichord, R., Kwiatkowski, JL., Bilello, M., Zimmerman, R., Ohene-Frempong, K., Melhem, E., Sickle cell anemia: intracranial stenosis and silent cerebral infarcts in children with low risk of stroke. Adv Med Sci. Mar;59(1):108-13, 2014.
  27. Arkuszewski, M., Krejza, J., Chen, R.,  Ichord, R., Kwiatkowski, J., Bilello M., Zimmerman R., Ohene-Frempong K., Melhem, E. R., Prevalence of intracranial stenosis and silent cerebral infarcts in children with sickle cell anemia and low risk of stroke, International Journal of Stroke. 8(7):E50-1. DOI:10.1111/ijs.12115. 2013.
  28. Arkuszewski M., Krejza J., Chen R., Melhem E. R., Sickle cell anemia: reference values of cerebral blood flow determined by continuous arterial spin labeling MRI. Neuroradiol J. 10;26(2):191-200. 2013
  29. Chen, R.*, Wang, S., Poptani, H., Melhem, E. R., Herskovits, E. H. A Bayesian diagnostic system to differentiate glioblastomas from solitary brain metastases. Neuroradiol J. 10;26(2):175-83. 2013
  30. Kumar, M., Kim, S., Pickup, S., Chen, R., Fairless A., Ittyerah, R., Abel, T., Brodkin, E., Poptani, H., Longitudinal in-vivo diffusion tensor imaging for assessing social behavioral abnormalities in the BALB/cJ mouse brain, Brain Research, 2012.
  31. Chen, R.*, Young, K., Chao L. L., Miller, B., Yaffe K., Weiner, M., Herskovits E. H., Prediction of Conversion from Mild Cognitive Impairment to Alzheimer Disease Based on Bayesian Data Mining with Ensemble Learning, The Neuroradiology Journal, 25:1, 2012
  32. Chen, R.*, Resnick, S., Davatzikos, C., Herskovits E. H., Dynamic Bayesian network modeling for longitudinal brain morphometry, 59(3):2330-8, NeuroImage, 2011.
  33. Chen, R.*, Herskovits E. H, Graphical model based multivariate analysis (GAMMA): an open-source, cross-platform neuroimaging data analysis software package, Neuroinformatics, 2011.
  34. Jiao, Y., Chen, R., Ke, X., Cheng Li, Chu, K., Lu ZH, Herskovits, E. H., Single Nucleotide Polymorphisms Predict Symptom Severity of Autism Spectrum Disorder, Journal of Autism and Developmental Disorders, 2011.
  35. Jiao, Y., Chen, R., Cheng, L., Ke, X., Chu K., Lu ZH., Herskovits. E. H., Predictive models for subtypes of autism spectrum disorder based on single-nucleotide polymorphisms and magnetic resonance imaging, Advance in Medical Sciences, 56(2):334-42, 2011.
  36. 29.  Arkuszewski, M., Krejza, J., Chen, R., Kwiatkowski, J., Ichord, R., Zimmerman, R., Ohene-Frempong, K., Desiderio, L., E.R. Melhem, Sickle Cell Disease: Reference Values and Interhemispheric Differences of Nonimaging Transcranial Doppler Blood Flow Parameters, American Journal of Neuroradiology, 32(8):1444-50, 2011.
  37. Chen, R.*, Jiao Y., Herskovits E. H, Structural MRI in Autism Spectrum Disorder, invited paper, Pediatric Research, 2011.
  38. Krejza J, Chen R, Romanowicz G, Kwiatkowski JL, Ichord R, Arkuszewski M, Zimmerman R, Ohene-Frempong K, Desiderio L, Melhem ER., Sickle cell disease and imaging: inter-hemispheric differences in blood flow Doppler parameters, Stroke.42:1, 81-6, 2011.
  39. Chen, R.*, Herskovits E. H, Machine-learning techniques for building a diagnostic model for very mild dementia, NeuroImage, 52(1):234-44, 2010.
  40. Chen, R.*, Herskovits E. H, Voxel-based Bayesian lesion-symptom mapping, NeuroImage, 49:1, 597-602, 2010.
  41. Jiao, Y., Chen, R., Ke, X, Chu, KK, Lu ZH, Herskovits, E. H, Predictive models of autism spectrum disorder based on brain regional cortical thickness, NeuroImage, 50(2):589-99, 2010.
  42. Chen, R.*, Pawlak, M., Flynn, T., Krejza, J., Herskovits, E. H., Melhem, E., Brain morphometry and IQ measurements in children with sickle cell disease, Journal of Developmental & Behavioral Pediatrics, 30(6):509-17, 2009.
  43. Chen, R.*, Herskovits E. H, Bayesian Classifier Combination for Microarray Classification, Proceedings of Biocomp, July, 2009
  44. Herskovits E. H., Chen, R., Integrating Data-Mining Support into a Brain-Image Database Using Open-Source Components, 18:1-10, Advance in Medical Sciences, Apr. 2008.
  45. Chen, R.*, Hillis A. E., Pawlak M., and Herskovits E. H., Voxelwise Bayesian Lesion Deficit Analysis, Vol 40, 1633-1642, NeuoImage, May, 2008.
  46. Chen, R.*, Herskovits E. H., Graphical-model-based Multivariate Analysis of Functional Magnetic Resonance Data, NeuroImage, Vol 35, 635-647, Apr. 2007.
  47. Chen, R.*, Herskovits E. H., Clinical Diagnosis based on Bayesian Classification of Functional Magnetic-resonance Data. 5(3):178-88, Neuroinformatics, Fall, 2007.
  48. Chen, R.*, Herskovits, E. H., Network analysis of Mild Cognitive Impairment, NeuroImage, Vol 29, 1252-1259, 2006.
  49. Chen, R.*, Herskovits, E. H., Graphical-Model-based Morphometric Analysis, IEEE Transaction on medical imaging, Vol 24, 1237-1248, Oct. 2005.
  50. Chen, R.*, Herskovits, E. H., A Bayesian Network Classifier with Inverse Tree Structure for Voxel-wise MR Image Analysis, Proceedings of the eleventh conference of SIGKDD, 2005
  51. Chen, R., Sivakumar, K, Kargupta, H, Collective Mining of Bayesian Networks from Distributed Heterogeneous data, Knowledge and Information Systems, 6(2):164-187, 2004.
  52. Chen. R, Giannella. C, Sivakumar. K, and Kargupta. H, Distributed Data Mining for Earth and Space Science Applications, Proceeding of the fourth annual Earth Science Technology conference (ESTC), June, 2004
  53. Chen. R, Sivakumar. K, and Kargupta, H., Learning Bayesian Network Structure from Distributed Data, Proceedings of SIAM Data Mining 03, 2003
  54. Chen, R., Sivakumar, K., A New Algorithm for Learning Parameters of a Bayesian Network from Distributed Data, Proceedings of the IEEE International Conference on Data Mining, 2002
  55. Chen, R., Sivakumar, K., Kargupta, H., Distributed Web Mining Using Bayesian Networks from Multiple Data Streams, Proceedings of the IEEE Conference on Data Mining, Nov. 2001
  56. Chen, R., Sivakumar, K., Kargupta, H., An Approach to Online Bayesian Learning from Multiple Data Streams, Proceedings of Workshop on Mobile and Distributed Data Mining, PKDD '01, July, 2001
  57. Chen, R., Liu, X.J., Zou, M.Y., Binary Image Restoration Based on MRF, Journal of Image and Graphics, Oct. 1999
  58. Chen, R.*, Hyperparameter Estimation for Markov Random Fields Using Genetic Algorithm, Proceedings of ICNN&B'98, Oct.1998
  59. Chen, R., Liu, X.J., Zou, M.Y., New Gibbs Sampling Algorithm with Application to Texture Synthesis, Proceedings of SPIE, Vol 3545, Aug.1998
  60. Chen, R.*, Zhang, X.M., The Development of a New Type of Intelligent Surface Pressure Measuring Instrument, Instrument Technique and Sensor, Dec. 1997