M. Chen and H. Jaenicke. An Information-theoretic Framework for Visualization. IEEE Transactions on Visualization and Computer Graphics, 16(6):1206-1215, 2010. (Presented in IEEE VisWeek 2010.) DOI, VisWeek slides(4.6M).
M. Chen and A. Golan, What may visualization processes optimize? IEEE Transactions on Visualization and Computer Graphics, 22(12):2619-2632, 2016. DOI.
M. Chen, M. Feixas, I. Viola, A. Bardera, H.-W. Shen, M. Sbert. Information Theory Tools for Visualization. A K Peters/CRC Press, 2016. ISBN: 9781498740937 - CAT# K26715.
G. K. L. Tam, V. Kothari, and M. Chen. An analysis of machine- and human-analytics in classification. IEEE Transactions on Visualization and Computer Graphics, 23(1):71-80, 2017. DOI. (Presented in IEEE VIS 2016, VAST2016 Best Paper Award.)
M. Chen and D. S. Ebert. An ontological framework for supporting the design and evaluation of visual analytics systems. Computer Graphics Forum, 38(3):131-144, 2019. DOI. (presented at EuroVis 2019.) Web site: IVAS (Improving Visual Analytics Systems).
M. Chen, A. Abdul-Rahman, D. Archambault, J. Dykes, A. Slingsby, P. D. Ritsos, T. Torsney-Weir, C. Turkay, B. Bach, A. Brett, H. Fang, R. Jianu, S. Khan, R. S. Laramee, L. Matthews, P. H. Nguyen, R. Reeve, J. C. Roberts, F. Vidal, Q. Wang, J. Wood, and K. Xu. RAMPVIS: answering the challenges of building visualisation capabilities for large-scale emergency responses. Epidemics, 39:100569, 2022. DOI.