Erik Andries
Center for Advanced Research Computing (CARC)
University of New Mexico (UNM)
  1. Research Synopsis and Brief Biography
  2. Publications
  3. Contact information

Chemometrics and Spectroscopy
  1. E. Andries, R. Nikzad-Langerodi. Supervised and Penalized Baseline Correction. arXiv:2310.18306 2023.

  2. E. Andries, R. Nikzad-Langerodi. Primal and Dual Constrained Principal Component Analysis. Journal of Chemometrics 2022.
    [https://doi.org/10.1002/cem.3403] [PDF (Preprint)]

  3. R. Nikzad-Langerodi, E. Andries. A Chemometrician's Guide to Transfer Learning. Journal of Chemometrics 2021.
    [https://doi.org/10.1002/cem.3373] [PDF (Preprint)]

  4. E. Andries, J. Kalivas, A. Gurung. Sample and feature augmentation strategies for calibration updating. Journal of Chemometrics 2018.
    [PDF] [ MATLAB code ]

  5. E. Andries. Penalized eigendecompositions: motivations from domain adaptation for calibration transfer. Journal of Chemometrics 2017; 31(4)
    [PDF] [ MATLAB code ]

  6. A. Tencate, J. Kalivas, E. Andries. Penalty Processes for Combining Roughness and Smoothness in Spectral Multivariate Calibration. Journal of Chemometrics 2016; 30(4): 144-152.
    [PDF]

  7. P. Shahbazikhah, J. Kalivas, E. Andries, T. O'Loughlin. Using the L1 Norm to Select Basis Set Vectors for Multivariate Calibration and Calibration Updating. Journal of Chemometrics 2016; 30(3): 109-120.
    [PDF]

  8. J. Kalivas, K. Heberger, E. Andries. Sum of ranking differences (SRD) to ensemble multivariate calibration model merits for tuning parameter selection and comparing calibration methods. Analytica Chimica Acta 2015; 689: 21-33.
    [PDF]

  9. E. Andries, J. Kalivas. Interrelationships between generalized Tikhonov regularization, generalized net analyte signal, and generalized least squares for desensitizing a multivariate calibration to interferences. Journal of Chemometrics 2013; 27(5): 249-260.
    [PDF]

  10. E. Andries, S. Martin. Focal Point feature entitled "Sparse methods in spectroscopy: an introduction, overview, and perspective." Applied Spectroscopy 2013; 67(6): 579-589.
    [PDF]

  11. E. Andries. Sparse models by iteratively reweighted feature scaling: a framework for wavelength and sample selection. Journal of Chemometrics 2013; 27(3-4): 50-62.
    [PDF]

  12. K. Higgins, J. Kalivas and E. Andries. Evaluation of target factor analysis and net analyte signal as processes for classification purposes with application to benchmark data sets and extra virgin olive oil adulterant identification. Journal of Chemometrics 2012; 26: 66-75.
    [PDF]

  13. J. Ottaway, J. Kalivas, and E. Andries. Spectral multivariate calibration with wavelength selection using variants of Tikhonov regularization. Applied Spectroscopy 2010; 64(12): 1388-1395.
    [PDF]

  14. M. Kunz, J. Kalivas and E. Andries. Model updating for spectral calibration maintenance and transfer using 1-norm variants of Tikhonov regularization. Analytical Chemistry 2010; 82(9): 3642-3649.
    [PDF]

  15. M. Kunz, J. Ottaway, J. Kalivas and E. Andries. Impact of standardization sample designs on Tikhonov regularization variants for spectroscopic calibration maintenance and transfer. Journal of Chemometrics 2010; 24: 218-229.
    [PDF]

  16. E. Andries and J. Kalivas. Multivariate calibration leverages and spectral F-ratios via a filter factor representation. Journal of Chemometrics 2010; 24(5): 249-260.
    [PDF]

  17. P. Cutler, D. Haaland, E. Andries and P. Gemperline. Methods for kinetic modeling of temporally resolved hyperspectral confocal fluorescence images. Applied Spectroscopy 2009; 63(2): 153-163. (Winner of the 2010 Meggers Award for the best paper published in the journal Applied Spectroscopy.)
    [PDF]

  18. J. Kalivas, G. Siano, E. Andries and H. Goicoechea. Tikhonov regularization approaches for calibration maintenance and transfer. Applied Spectroscopy 2009; 63(7): 800-809.
    [PDF]


Miscellaneous Biology
  1. A. Singh, E. Andries, J. Edwards, S. Steinberg. The shuttling scaffold model for prevention of yeast pheromone pathway mis-activation. Bulletin of Mathematical Biology 2012; 74(12): 2861-74.

  2. E. Andries, T. Hagstrom, S. Atlas and C. Willman. Regularization strategies for hyperplane classifiers: application to cancer classification. Journal of Bioinformatics and Computational Biology 2007; 5(1): 79-104.

  3. E. Andries, S. Umarov and S. Steinberg. Monte Carlo random walk simulations based upon distributed order differential equations with applications to cell biology. Fractional Calculus and Applied Analysis 2006; 9(4): 351-369.
    [PDF]

  4. C. Wilson, G. Davidson, S. Martin, E. Andries, Y. Xu, J. Potter, K. Kopecky, D. Ankerst, H. Gundacker, M. Slovak, M. Mosquera-Caro, I-M Chen, K. Ar, M. Murphy, H. Kang, X. Wang, D. Stirewalt, J. Radich, F. Appelbaum, S. Atlas, and C. Willman. Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction. Blood 2006; 108: 685-696.
    [PDF]

  5. M. Mosquera-Caro, S. Martin, E. Andries, J. Potter, K. Ar, Y. Xu, X. Wang, M. Murphy, P. Helman, R. Veroff, D. Haaland, S. Atlas, J. Cowie, C. Fields, V. Sibirtsev, G. Davidson and C. Willman. Application of multidisciplinary analysis to gene expression data. Sandia National Laboratories Report 2004; SAND2004-0161.
    [PDF]

[Arizona Cactus Garden at Stanford University]
Visiting the Arizona Cactus Garden at Stanford University.