Faculty Directory
Daniel Apley

Professor of Industrial Engineering and Management Sciences

Contact

2145 Sheridan Road
Tech M235
Evanston, IL 60208-3109

Email Daniel Apley

Website

Professor Apley's Website

Departments

Industrial Engineering and Management Sciences

Affiliations

Master of Science in Machine Learning and Data Science Program

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Education

PhD Mechanical Engineering, University of Michigan, Ann Arbor, MI

MS Electrical Engineering, University of Michigan, Ann Arbor, MI

MS Mechanical Engineering, University of Michigan, Ann Arbor, MI

BS Mechanical Engineering, University of Michigan, Ann Arbor, MI


Research Interests

Statistical modeling and analysis of engineering, industrial, and enterprise systems; machine learning and predictive analytics; quality engineering and six sigma; manufacturing process diagnosis and control


Selected Publications

  • Zhang, K., Bui, A. T., and Apley, D. W., "Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors," Technometrics, https://doi.org/10.1080/00401706.2022.2124310, 2022.
  • Sürer, Ö., Apley, D. W., and Malthouse, E. C., "Coefficient Tree Regression: Fast, Accurate and Interpretable Predictive Modeling," Machine Learning, to appear, https://doi.org/10.1007/s10994-021-06091-7, November, 2021.
  • Zhang, K., Apley, D. W., and Chen, W. "Nonstationarity Analysis of Materials Microstructures via Fisher Score Vectors," Acta Materialia, 211(1), 116818, https://doi.org/10.1016/j.actamat.2021.116818, 2021.
  • Yang, R., Kent, D., Apley, D. W., Staum, J. and Ruppert D., "Bias-corrected Estimation of the Density of a Conditional Expectation in Nested Simulation Problems," ACM Transactions on Modeling and Computer Simulation, 31(4), 1–36, https://doi.org/10.1145/3462201, 2021.
  • Zhang, K., Apley, D. W., and Chen, W. "Nonstationarity Analysis of Materials Microstructures via Fisher Score Vectors," Acta Materialia, 211(1), 116818, https://doi.org/10.1016/j.actamat.2021.116818, 2021.
  • Yang, R., Apley, D. W., Staum, J., and Ruppert D., "Density Deconvolution with Additive Measurement Errors using Quadratic Programming," Journal of Computational and Graphical Statistics, 29:3, pp. 580-591, https://doi.org/10.1080/10618600.2019.1704294, 2020.
  • Zhang, Y., Apley, D. W., and Chen, W. "Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables," Nature Research - Scientific Reports, 10, Article 4924, https://doi.org/10.1038/s41598-020-60652-9, 2020.
  • Apley, D. W. and Zhu, J., "Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models", Journal of the Royal Statistical Society, Series B (Statistical Methodology), 82(4), pp. 1059–1086, DOI: 10.1111/rssb.12377, 2020.
  • Zhang, Y., Tao, S., Chen, W., and Apley, D. W., "Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors," Technometrics,62:3, pp. 291-302, DOI: 10.1080/00401706.2019.1638834, 2020.