Nathaniel Helwig

[email protected]

Psychology

N218 Elliott Hall

75 East River Parkway
Minneapolis, MN 55455

Curriculum Vitae

Collegiate Affiliation

Associate Professor,

Links

I am a tenured Associate Professor with a 50/50 joint appointment in Psychology and Statistics at the University of Minnesota, Twin Cities. I also hold a graduate faculty appointment in Data Science, and I am a "Core Member" of the University of Minnesota's Data Science and AI Hub. I have research interests in artificial intelligence, computational statistics, machine learning, and multivariate nonparametric methods with a focus on applications in the psychological and biomedical sciences. My papers and open-source software, which are inspired by my collaborations, strive to solve general methodological and computational problems in ways that work both in theory and in practice—when the data are messy.

Educational Background

Open Close

Educational Background

PhD: Quantitative Psychology, University of Illinois, 2013
MA: Psychology, University of Illinois, 2011
MS: Statistics, University of Illinois, 2010
BS: Psychology & Mathematics, University of Miami, 2007

Publications

Open Close

Publications

Helwig, N. E., & Ma, P. (2015). Fast and stable multiple smoothing parameter selection in smoothing spline analysis of variance models with large samples. Journal of Computational and Graphical Statistics, 24(3), 715-732. https://doi.org/10.1080/10618600.2014.926819
Helwig, N. E. (2017). Adding bias to reduce variance in psychological results: A tutorial on penalized regression. The Quantitative Methods for Psychology, 13(1), 1-19. https://doi.org/10.20982/tqmp.13.1.p001
Helwig, N. E. (2013). The special sign indeterminacy of the direct-fitting Parafac2 model: Some implications, cautions, and recommendations for Simultaneous Component Analysis. Psychometrika, 78(4), 725-739. https://doi.org/10.1007/S11336-013-9331-7
Helwig, N. E., & Hong, S. (2013). A critique of Tensor Probabilistic Independent Component Analysis: Implications and recommendations for multi-subject fMRI data analysis. Journal of Neuroscience Methods, 213(2), 263-273. https://doi.org/10.1016/j.jneumeth.2012.12.009
Helwig, N. E., Hong, S., & Polk, J. D. (2012). Parallel Factor Analysis of gait waveform data: A multimode extension of Principal Component Analysis. Human Movement Science, 31(3), 630-648. https://doi.org/10.1016/j.humov.2011.06.011
Helwig, N. E., Hong, S., Hsiao-Wecksler, E. T., & Polk, J. D. (2011). Methods to temporally align gait cycle data. Journal of Biomechanics, 44(3), 561-566. https://doi.org/10.1016/j.jbiomech.2010.09.015
Helwig, N. E. (2016). Efficient estimation of variance components in nonparametric mixed-effects models with large samples. Statistics and Computing, 26(6), 1319-1336. https://doi.org/10.1007/s11222-015-9610-5
Helwig, N. E., & Ma, P. (2016). Smoothing spline ANOVA for super-large samples: Scalable computation via rounding parameters. Statistics and Its Interface, 9(4), 433-444. https://doi.org/10.4310/SII.2016.v9.n4.a3
Helwig, N. E., Shorter, K. A., Ma, P., & Hsiao-Wecksler, E. T. (2016). Smoothing spline analysis of variance models: A new tool for the analysis of cyclic biomechanical data. Journal of Biomechanics, 49(14), 3216-3222. https://doi.org/10.1016/j.jbiomech.2016.07.035
Helwig, N. E., Sohre, N. E., Ruprecht, M. R., Guy, S. J., & Lyford-Pike, S. (2017). Dynamic properties of successful smiles. PLoS ONE, 12(6), e0179708. https://doi.org/10.1371/journal.pone.0179708
Helwig, N. E. (2017). Estimating latent trends in multivariate longitudinal data via Parafac2 with functional and structural constraints. Biometrical Journal, 59(4), 783-803. https://doi.org/10.1002/bimj.201600045
Helwig, N. E. (2017). Regression with ordered predictors via ordinal smoothing splines. Frontiers in Applied Mathematics and Statistics, 3(15), 1-13. https://doi.org/10.3389/fams.2017.00015
Helwig, N. E., & Ruprecht, M. R. (2017). Age, gender, and self-esteem: a sociocultural look through a nonparametric lens. Archives of Scientific Psychology, 5(1), 19-31. https://doi.org/10.1037/arc0000032
Lyford-Pike, S., Helwig, N. E., Sohre, N. E., Guy, S. J., & Hadlock, T. A. (2018). Predicting perceived disfigurement from facial function in patients with unilateral paralysis. Plastic and Reconstructive Surgery, 142(5), 722e-728e. https://doi.org/10.1097/PRS.0000000000004851
Whiteford, K. L., Schloss, K. B., Helwig, N. E., & Palmer, S. E. (2018). Color, music, and emotion: Bach to the blues. i-Perception, 9(5), 1-25. https://doi.org/10.1177/2041669518808535
Helwig, N. E. (2019). Statistical nonparametric mapping: Multivariate permutation tests for location, correlation, and regression problems in neuroimaging. WIREs Computational Statistics, 11(2), e1457. https://doi.org/10.1002/wics.1457
Helwig, N. E., & Snodgress, M. A. (2019). Exploring individual and group differences in latent brain networks using cross-validated simultaneous component analysis. NeuroImage, 201, 116019. https://doi.org/10.1016/j.neuroimage.2019.116019
Helwig, N. E. (2019). Robust nonparametric tests of general linear model coefficients: A comparison of permutation methods and test statistics. NeuroImage, 201, 116030. https://doi.org/10.1016/j.neuroimage.2019.116030
Hammell, A. E., Helwig, N. E., Kaczkurkin, A. N., Sponheim, S. R., & Lissek, S. (2020). The temporal course of over-generalized conditioned threat expectancies in posttraumatic stress disorder. Behaviour Research and Therapy, 124, 103513. https://doi.org/10.1016/j.brat.2019.103513
Helwig, N. E. (2020). Multiple and generalized nonparametric regression. In P. Atkinson, S. Delamont, A. Cernat, J. W. Sakshaug, & R. A. Williams (Eds.), SAGE Research Methods Foundations. https://doi.org/10.4135/9781526421036885885
Almquist, Z. W., Helwig, N. E., & You, Y. (2020). Connecting Continuum of Care point-in-time homeless counts to United States Census areal units. Mathematical Population Studies, 27(1), 46-58. https://doi.org/10.1080/08898480.2019.1636574
Kage, C. C., Akbari-Shandiz, M., Foltz, M. H., Lawrence, R. L., Brandon, T. L., Helwig, N. E., & Elllingson, A. M. (2020). Validation of an automated shape-matching algorithm for biplane radiographic spine osteokinematics and radiostereometric analysis error quantification. PLoS ONE, 15(2), e0228594. https://doi.org/10.1371/journal.pone.0228594
For a full list of publications, see my website.

Awards

Open Close

Awards

Distinguished Dissertation Award, American Psychological Association (Division 5), Spring 2014
Student Paper Competition Winner, American Statistical Association (Statistical Computing Section), Spring 2013
Nancy Hirschberg Award (for outstanding original research or scholarship), Department of Psychology, University of Illinois, Spring 2013
Woodrow Fellowship (for outstanding original research or scholarship), Department of Psychology, University of Illinois, Spring 2011
Outstanding Quantitative Psychology Doctoral Student, Department of Psychology, University of Illinois, Spring 2010
Graduate Teaching Certificate, Center for Teaching Excellence, University of Illinois, Spring 2010
Outstanding Teacher, Incomplete List of Teachers ranked as Excellent, University of Illinois, Fall 2009 - Spring 2010