Contact Information


Dr. Lauren Sugden is an assistant professor of Statistics at Duquesne University, and serves as the faculty director for the Data Science B.S. program. Her research interests lie at the intersection of population genetics and machine learning, with an emphasis on interpretability. She regularly supervises undergraduate and Master's research projects, with students presenting their work in both regional and national meetings, and in co-authored manuscripts.


Ph.D., Applied Mathematics, Brown University 2014
B.A., Mathematics and Physics, Wesleyan University 2008


Profile Information

  • DTSC 220 Data Exploration and Visualization
  • MATH 225 Introduction to Biostatistics I
  • MATH 301 Introduction to Probability and Statistics I
  • MATH 302 Introduction to Probability and Statistics II
  • MATH 473/CPMA 573 Statistical Computing
  • McAnulty College and Graduate School Pre-tenure Faculty Excellence in Teaching Award, 2022
  • MAA Project NExT Fellowship, Mathematical Association of America, Summer 2019 - Summer 2020
  1. Cecil, R.M., Sugden, L.A. "On convolutional neural networks for selection inference: revealing the lurking role of preprocessing, and the surprising effectiveness of summary statistics." bioRxiv (2023) preprint, under revision for PLoS Computational Biology 
  2. Ahlquist, K. D., Sugden, L.A., and Ramachandran S. "Enabling interpretable machine learning for biological data with reliability scores." PLOS Computational Biology 19, no. 5 (2023): e1011175. 
  3. Provenzano, D.A., Leech, J.E., Kilgore, J.S., and Sugden, L.A. "Evaluation of lumbar medial branch blocks: how does the second block influence progression to radiofrequency ablation? An infographic." Regional Anesthesia & Pain Medicine 48, no. 2 (2023): 80-81. 
  4. Provenzano, D.A., Leech, J.E, Kilgore, J.S., and Sugden, L.A.. "Evaluation of lumbar medial branch blocks: how does the second block influence progression to radiofrequency ablation?" Regional Anesthesia & Pain Medicine (2022). 
  5. Sugden, A.U., Zaremba, J.D., Sugden, L.A., McGuire, K.L., Lutas, A., Ramesh, R.N., Alturkistani, O.A., Lensjø, K.K., Burgess, C.R., Andermann, M.L. "Cortical Reactivations of Recent Sensory Experiences Predict Bidirectional Network Changes During Learning." Nature Neuroscience (2020): 1-11.
  6. Livneh, Y., Sugden, A.U., Madara, J.C., Essner, R.A., Flores, V.I., Sugden, L.A., Resch, J.M., Lowell, B.B., Andermann, M.L. "Estimation of Current and Future Physiological States in Insular Cortex." Neuron 105 (2020): 1-18.
  7. Sugden, L.A., Atkinson, E.G., Fischer, A.P., Rong, S., Henn, B.M., Ramachandran, S. "Localization of adaptive variants in human genomes using averaged one-dependence estimation." Nature Communications 9 (2018): 703.
  8. Sugden, L.A., and Ramachandran, S. "Integrating the signatures of demic expansion and archaic introgression in studies of human population genomics." Current Opinion in Genetics & Development 41 (2016): 140-149. 
  9. Sugden, L.A., Tackett, M.R., Savva, Y.A., Thompson, W.A., Lawrence, C.E. "Assessing the validity and reproducibility of genome-scale predictions." Bioinformatics29.22 (2013): 2844-2851. 
  10. Savva, Y.A., Jepson, J.E.C., Sahin, A., Sugden, A.U., Dorsky, J.S., Alpert, L., Lawrence, C., Reenan, R.A. "Auto-regulatory RNA editing fine-tunes mRNA re-coding and complex behaviour in Drosophila." Nature communications 3 (2012): 790. 
  11. Wei, D., Alpert, L.V., and Lawrence, C.E. "RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences." Bioinformatics 27.18 (2011): 2486-2493. 
  12. Reid, D.C., Chang, B.L., Gunderson, S.I., Alpert, L., Thompson, W.A., Fairbrother, W.G. "Next- generation SELEX identifies sequence and structural determinants of splicing factor binding in human pre-mRNA sequence." RNA 15.12 (2009): 2385-2397.