Editor's Choice for Featured Article, IISE Transactions (2022).
AFRL Summer Faculty Fellowship, Air Force Office of Scientific Research (2021, 2022).
BrainPool Faculty Fellowship, National Research Foundation of Korea (2019).
NSF Travel Award to Innovation Lab, National Science Foundation (2018).
Award for Research Excellence, FAMU-FSU College of Engineering (2014).
Best Application Paper Award in the IIE Transactions Focused Issue on Quality and Reliability Engineering, Institute of Industrial Engineers (2014).
Featured Speaker, Randy Sitter Technometrics Session, American Statistical Association (2014).
Nominee, 2014 Blavatnik Awards for Young Scientists, The New York Academy of Sciences (2014).
Ralph E. Powe Jr. Faculty Enhancement Award, Oak Ridge Associated Universities (2013).
First Year Assistant Professor Award, Florida State University - Council of Research and Creativity (2012).
First Place in Best Student Paper Award, IEEE Conference on Automation Science & Engineering (2006).
Park, C., Noh, S., & Srivastava, A. (in press). Data Science for Motion and Time Analysis with Modern Motion Sensor Data. Operations Research (Paper)
Park, C. and Ding, Y. (2021) Data Science for Nano Image Analysis. Springer Nature. ISBN 978-3-030-72821-2 (Paper)
Park, C., & Apley, D. (2018) Patchwork Kriging for Large-scale Gaussian Process Regression. Journal of Machine Learning Research. 19(7): 1-43 (Paper)
Park, C., Woehl, T. J., Evans, J. E., & Browning, N. D. (2015). Minimum Cost Multi-way Data Association for Optimizing Large-scale Multitarget Tracking of Interacting Objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(3), 611-624 (Paper)
Park, C. (2014). Estimating Multiple Pathways of Object Growth using Non-longitudinal Image Data. Technometrics, 56(2), 186-199 (Paper)
Park, C., Huang, J. Z., Ji, J., & Ding, Y. (2013). Segmenting, Inference and Classification of Partially Overlapping Nanoparticles. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35 (3), 669-681 (Paper)
Park, C., Huang, J. Z., & Ding, Y. (2010). A Computable Plug-in Estimator of Minimum Volume Sets for Novelty Detection. Operations Research, 58(5), 1469-1480 (Paper)