Xuhong Zhang


3012, Luddy Hall, 700 N Woodlawn Ave, Bloomington, IN, 47408 

Email contact (preferred): zhangxuh at indiana dot edu  

Office Tel: (812)-855-9035

Hello! Welcome to my webpage. I am currently an Assistant Professor researcher at the Department of Computer Science, Luddy School of Informatics, Computing, and Engineering, University of Indiana Bloomington.


My research interest covers a broad range of topics: development and application of computational and statistical techniques, machine learning and deep learning models to theoretical and methodological problems within the areas of medical image analysis, natural language processing, computational biology, social and biophysical network analysis, and pervasive computing. Currently, my work focuses on: prediction and classification of phenotypical cellular biomarkers of tumor cells for medical images; utilizing natural language processing techniques for text mining in medical field; network analysis and comparison based on massive human behavior data; Bayesian methods for clustering, inference and properties of large-scale, high-dimensional, single-cell cytometry datasets. In the past, I worked on the structure of spatially embedded large-scale interpersonal and telecommunication networks; spectural analysis and applications for cross-regional and dynamic communication data.


Assistant Professor


                                                                                                                                                                                                          August 2020 - Present

Postdoctoral Fellow


September 2017 - July 2020 

Research Assistant 


I used to be a research assistant in the lab of Networks, Computation and Social Dynamics (NCASD) led by Prof. Carter T. Butts, who is my wonderful PhD advisor.

September 2012 - July 2017 

You can get my CV from here.



  1. Artificial Intelligence for Pathology

Xing F, Zhang X, Cornish TC.

Book Chapter in Artificial Intelligence in Medicine: Technical Basis and Clinical Applications, pp. 183-221, Chapter 11, Elsevier, 2020


  1. Generative Adversarial Domain Adaption for Nucleus Quantification in Ki67 Images.
    Zhang X, Cornish TC, Yang L, Bennett T, Ghosh D, Xing F.
    (under minor revision) JCO Clinical Cancer Informatics. (2020). 
  2. Elements of Social Convoy Theory in mHealth for Palliative Care: A Scoping Review.
    Portz J, Elbernd K, Plys E, Ford KL,
    Zhang X, Gore O, Moore SL, Zhou S, Bull S.
    JMIR mHealth and uHealth. (2020)8(1):e16060. DOI: 10.2196/16060 
  3. Multiple testing approaches for hypotheses in integrative genomics.
    Rudra P, Cortès EC,
    Zhang X, Ghosh D.
    WIREs Computational Statistics. (2019):e1493 DOI: 10.1002/wics.1493 
  4. Advancing evidence-based digital health through an innovative research environment: An academic-industry partnership case report.
    Ford KL, Moore SL, Zhou S, Gore O, Protz J,
    Zhang X, Zane R, Wiler J, Bull S.
    mHealth. (2019)5:37 DOI:10.21037/mhealth.2019.08.08 
  5. Activity Correlation Spectroscopy: A New Method for Inferring Social Relationships from Activity Data.
    Zhang X, Butts CT.
    Social Network Analysis and Mining. (2017)7:1. DOI 10.1007/s13278-016-0419-9 
  6. Sequence Comparison, Molecular Modeling, and Network Analysis Predict Structural Diversity in Cysteine Proteases from the Cape Sundew, Drosera Capensis.
    Butts CT,
    Zhang X, Kelly J, Roskamp K, Unhelkar M, Freites AJ, Tahir S and Martin RW.
    Computational and Structural Biotechnology Journal. (2016)14, 271–282. DOI: 10.1016/j.csbj.2016.05.003 


  1. Mother’s Milk MessagingTM(MMM): Mixed Methods Evaluation of Bilingual App and Texting Program to Support Breastfeeding.
    Bunik M, Jimenez-Zambrano A, Beaty B, Solari M, Moore S,
    Zhang X, Bull S, Leiferman J.
    Pediatric Academic Societies Meeting. PAS 2020, Philadelphia, PA. 
  2. A Pilot Study and Ecological Model of Smoking Cues to Inform mHealth Strategies for Quitting among Low-income Smokers.
    Zhou S,
    Zhang X, Portz J, Moore S, Gore M, Li Q, Levinson A, Bull S.
    70th Annual International Communication Association Conference. ICA 2020. Gold Coast, Australia. 
  3. An Integrated Platform for Collecting Mobile Phone Data and Learning Demographic Features.
    Zhang X, Mallepudi V and Butts CT.
    IEEE International Conference on Pervasive Computing and Communications. Percom 2017. Kona, Hawaii. DOI:10.1109/PERCOMW.2017.7917514 
  4. A Novel Multivariate Spectral Regression Model for Learning Relationships Between Communication Activity and Urban Ecology.
    Zhang X, Butts CT.
    IEEE International Conference on Pervasive Computing and Communications. Percom 2016. Sydney, Australia. DOI: 10.1109/PERCOM.2016.7456525 


  1. Understanding Mobile Technology Usage among New Mothers to Support Breastfeeding: Phase I.
    Zhang X, Zhou S, Moore SL, and et al.
    (submitted to ) JMIR. (2020). 
  2. An Innovative Framework for Measuring Engagment in mHealth.
    Zhang X, Zhou S, Moore SL, and et al.
    (submitted to) JMIR protocols. (2020). 
  3. Equity in Technology for Health: Improving Care for Safety Net Patients.
    Moore SL, Gore O, Portz J, Ford KL, Durfee JM, Zhou S,
    Zhang X, Bull S and Friedman A.
  4. Distribution of Amino Acids Exposure Rates among Protein from Diverse Thermal Environments.
    Bierma JC,
    Zhang X, Montelongo D, Butts CT and Martin RW.
  5. Dynamic Networks as a Tool for Analysis of Protein Structure and Fluctuations.
    Zhang X, Freites AJ, Wong EK, Roskamp K, Martin RW, Tobias DJ and Butts CT.
  6. A Molecular Informant Model for the Prediction of Exposure Change upon Single-Point Mutation of Protein.
    Zhang X, Montelongo D, Freites AJ, Martin RW and Butts CT.
  7. Predicting RNA Secondary Structures from Informant Information.
    Zhang X, and Butts CT.



CSCI-B 659 Medical Image Analysis                                                                                                                                                                                                                                                                                                                                                                                                 

Spring, 2021 


CSCI-P 556 Applied Machine Learning 

                                                                                                                                                                                                                                                                                                                                                                                                 Fall, 2020 



Center for Innovative Design & Analysis, CSPH, Aurora, CO 

January, 2020 


BIOS 6642 Introduction to Python Programming

Biostatistics and Informatics, CSPH, Aurora, CO. 

 Spring, 2020 


BIOS 6601 Applied Statistics

Biostatistics and Informatics, CSPH, Aurora, CO. 

Fall, 2017 



M2 Catalyst & UCI Mobile Data Science 

May, 2016