Bio

I help others become empowered through data to solve challenging problems.

I am an instructor, researcher, and data scientist with 15 years’ experience across learning design and pedagogy, instruction, cross-functional collaboration for data science projects, project management, consultation, and mentorship. At Stanford, I lead a team that upskills and reskills students, faculty, and staff in group and personal settings (online and offline) to help them be successful in their computational research projects through workshops, consultations, specialized trainings, curriculum development, mentoring, and coaching using a variety of pedagogical and methodological resources that emphasize critical thinking and data skills.

Additionally, I cultivate successful cross-functional collaborations across campus as well as with external stakeholders to leverage data science and artificial intelligence to optimize workflows and processes for research teams. My personal research interests span machine learning applications to bioarchaeology and international conflict, teaching pedagogy, deep learning, and computational text analysis/natural language processing.

I earned my PhD in 2015 from the Southern Illinois University Carbondale Department of Anthropology under the guidance of Izumi Shimada and Robert Corruccini. Before joining Stanford, I was the Instructional Services Lead at the UC Berkeley D-Lab.

Contact

  • Work
    muzzall@stanford.edu
    University - Staff Department: Center for Interdisciplinary Digital Research Position: Head of Software & Services for Data Science
    • 459 LASUEN MALL
    • STANFORD,  California  94305 

Additional Info

All Publications

  • A perspective on computational research support programs in the library: More than 20 years of data from Stanford University Libraries Journal of Librariahship and Information Science Muzzall, E., Abraham, V., Nakao, R. 2022

    View details for DOI 10.1177/09610006221124619

  • Critical faculty and peer instructor development: Core components for building inclusive STEM programs in higher education Frontiers in Psychology Muzzall, E., et al 2022

    View details for DOI 10.3389/fpsyg.2022.754233

  • Overview of attacks against civilian infrastructure during the Syrian civil war, 2012–2018 British Medical Journal - Global Health Muzzall, E. 2021

    Abstract

    Hundreds of thousands of people have been killed during the Syrian civil war and millions more displaced along with an unconscionable amount of destroyed civilian infrastructure.We aggregate attack data from Airwars, Physicians for Human Rights and the Safeguarding Health in Conflict Coalition/Insecurity Insight to provide a summary of attacks against civilian infrastructure during the years 2012-2018. Specifically, we explore relationships between date of attack, governorate, perpetrator and weapon for 2689 attacks against five civilian infrastructure classes: healthcare, private, public, school and unknown. Multiple correspondence analysis (MCA) via squared cosine distance, k-means clustering of the MCA row coordinates, binomial lasso classification and Cramer's V coefficients are used to produce and investigate these correlations.Frequencies and proportions of attacks against the civilian infrastructure classes by year, governorate, perpetrator and weapon are presented. MCA results identify variation along the first two dimensions for the variables year, governorate, perpetrator and healthcare infrastructure in four topics of interest: (1) Syrian government attacks against healthcare infrastructure, (2) US-led Coalition offensives in Raqqa in 2017, (3) Russian violence in Aleppo in 2016 and (4) airstrikes on non-healthcare infrastructure. These topics of interest are supported by results of the k-means clustering, binomial lasso classification and Cramer's V coefficients.Findings suggest that violence against healthcare infrastructure correlates strongly with specific perpetrators. We hope that the results of this study provide researchers with valuable data and insights that can be used in future analyses to better understand the Syrian conflict.

    View details for DOI 10.1136/bmjgh-2021-006384

    View details for PubMedCentralID PMC8488748

  • A novel ensemble machine learning approach for bioarchaeological sex prediction Technologies Special Issue: Data Science and Big Data in Biology, Physical Science and Engineering Muzzall, E. 2021

    View details for DOI 10.3390/technologies9020023

  • Building STEAM for DH and electronic literature: An educational approach to nurturing the STEAM mindset in higher education Electronic Book Review: Electronic Literature [Frame]works for the Creative Digital Humanities Muzzall, E., et al 2020

    View details for DOI 10.7273/y68f-7313

  • Temporal and spatial biological kinship variation at Campovalano and Alfedena in Iron Age Central Italy Bioarchaeology of Frontiers and Borderlands Muzzall, E. 2019

    View details for DOI 10.2307/j.ctvx0720b

  • Potential clinical utility of ERC-2 yeast phase lysate antigen for antibody detection in dogs with blastomycosis Medical Mycology Muzzall, E., et al 2019

    View details for DOI 10.1093/mmy/myy137

  • 2014 Dahlberg Award Winner: The effects of dietary toughness on occlusopalatal variation in savanna baboons Dental Anthropology Journal Muzzall, E. 2014

    View details for DOI 10.26575/daj.v27i1-2.39

https://orcid.org/0000-0001-8258-9100