I am a social data scientist and digital humanist with experience in pedagogy and curriculum development, instruction, instructor coaching, consultation, mentoring and professional development, and collaborative interdisciplinary research projects. I support the computational research pursuits of students, librarians, faculty, and staff using a variety of pedagogical and methodological resources that emphasize critical thinking and data skills.
My research interests span functional biomechanics, mortuary archaeology, microbiology, teaching computational text analysis in digital humanities contexts, machine learning applications to bioarchaeology and international conflict, the science of science, deep learning, and natural language processing/computational text analysis.
Currently working on:
- Attitudes about envronmental catastrophes in the Mascarenes
- Machine learning to better understand perioperative depression
- Ecological effects of chlorinated water, disease, and conflict in Northwest Syria
- Health, agriculture, and armed conflict in Syria and Yemen
- Postoperative complications in young female diabetics
I can help with:
- R/RStudio/Tidyverse, Python/Jupyter Notebooks, Bash, Git/GitHub, Microsoft Excel, Qualtrics, Google Suite
- Data preparation: text, image, quantitative, machine/deep learning, data imputation
- Data visualization: ggplot2, geospatial mapping, matplotlib, seaborn, plotly, altair, geopandas, gnuplot
- Machine learning: caret, SuperLearner, H2O, scikit-learn, tensorflow, pytorch, keras, regression (lm, glm, penalized, step, spline, hinge), classification, tree-based methods, confusion matrix derivations, cross-validation
- Deep learning: quantitative, text, image, MLP, GAN, RNN, CNN, LSTM, transfer learning
- Text: mining, classification, word embeddings, topic modeling (assisted/anchored/weighted/neural), sentiment analysis, semantic structure/analysis
- Unsupervised methods/dimension reduction: PCA, MCA, CCA, tSNE, UMAP, clustering
- API access, social network data, webscraping
- Categorical data analysis
- Time series, forecasting
- Survey design and analysis
- Bloomberg Terminal
- PhD, Anthropology, Southern Illinois University Carbondale
- MA, Anthropology, Wichita State University
- BS, Anthropology, Michigan State University
von Vacano C, Ruiz M, Starowicz R, Olojo S, Moreno Luna AY, Muzzall E, Mendoza-Denton R, Harding DJ. 2022. Critical Faculty and Peer Instructor Development: Core Components for Building Inclusive STEM Programs in Higher Education. Frontiers in Psychology 13:754233. doi:10.3389/fpsyg.2022.754233.
Muzzall E, Perlman B, Rubenstein LS, Haar RJ. 2021. Overview of attacks against civilian infrastructure during the Syrian civil war, 2012-2018. BMJ Global Health 6:e006384. http://dx.doi.org/10.1136/bmjgh-2021-006384.
Muzzall E. 2021. A novel ensemble machine learning approach for bioarchaeological sex prediction. Technologies: Big Data in Biology, Physical Sciences and Engineering 9, 23. https://doi.org/10.3390/technologies9020023.
von Vacano C, Muzzall E, Anderson AG, Reeve J, van Neunen T. 2020. Building STEAM for DH and electronic literature: An educational approach to nurturing the STEAM mindset in higher education. Electronic Book Review [Frame]works for the Creative Digital Humanities. https://doi.org/10.7273/y68f-7313.
Muzzall E, Coppa A. 2019. Temporal and spatial biological kinship variation at Campovalano and Alfedena in Iron Age Central Italy. In Bioarchaeology of Frontiers and Borderlands; Tica, C., Martin, D.L., Eds.; University Press of Florida: Gainesville, FL, USA; pp. 107-132. https://doi.org/10.2307/j.ctvx0720b.11.
Roy-Chowdhury M, Muzzall E, Baumgardner DJ, Kennell BC, Esterbrook AC, Shurley JF, Scalarone GM. 2019. Potential clinical utility of ERC-2 yeast phase lysate antigen for antibody detection in dogs with blastomycosis. Medical Mycology 57, pp. 893-896. https://doi.org/10.1093/mmy/myy137.
Muzzall E, Campbell RM, Campbell M, Corruccini RS. 2014. Dahlberg Award Winner: The effects of dietary toughness on occlusopalatal variation in savanna baboons. Dental Anthropology Journal 27: pp. 8-15. https://doi.org/10.26575/daj.v27i1-2.39.
Muzzall E. 2022. Text Analysis and Machine Learning Jupyter Book. https://eastbayev.github.io/SSDS-TAML/intro.html.
Muzzall E. 2017. Ensemble machine learning for sex prediction of a worldwide craniometric dataset. https://github.com/EastBayEv/Ensemble-machine-learning-for-sex-prediction-of-a-worldwide-craniometric-dataset.