Sheldon Waugh, MSc, PhD


Department of Commerece, Office of the Inspector General (DOC OIG)

I currently work the DOC OIG. I will be the Chief and principal data scientist for the DOC OIG.

Addtionally I will be:

  • Lead the Data Analytics team in conducting data science research and projects that make informed projections, data-driven decisions, and recommendations based on findings.
  • Drive analytic design/brainstorming sessions with investigators, auditors, and other data analytics professionals that incorporate advance modeling and technical methods to identify fraud, waste, and abuse.
  • Prepare, process, and transform structured and unstructured data and apply advanced scientific, mathematical, and statistical principals and theories to new and existing data sources using open source or proprietary programming languages. Apply data science methods and techniques including statistical analysis, modeling, machine learning, spatial analysis, and Natural Language Processing (NLP).

US Census Bureau

From 2021 to 2023, I worked at the US Census Bureau as a Data Scientist. I provided expertise in the applications of data science (interdisciplinary analytical, statistical, and programming skills) to develop data-driven solutions for difficult business challenges. One HUGE business challenges was the improvement of the quality of survey data collection among Field Reprsentatives (FRs).

My accomplishments at the US Census Bureau inlcudes

  • Led Audio-related Natural Language Processing project with collaboration with the Field and Social, Economic, and Housing Statistics Division. Coordinated access to Computer Audio Recorded Interview (CARI) Interactive Data Access (CIDA) system to download multiple years of SIPP interview data. Successfully submitted and approved python package Transformers through the Standards Working Group for access of open-source machine learning models through HuggingFace, a AI Repository.
  • Led and established the development of front facing ESRI Mapper dashboards, maps and tools for the American Housing Survey (AHS) and the National Health Interview Survey (NHIS), an initial and essential part of the Field Quality Monitoring Program, stood up by the Office of Census Analytics (OSCA).
  • Led and established the development of front facing Tableau dashboards for the American Housing Survey (AHS), an initial and essential part of the Field Quality Monitoring Program (FQM), stood up by OSCA. Assigned senior administrator of OSCA’s Tableau Server, a cloud-based server, responsible for the creation and management the site’s users and groups, creation of projects to organize content on the site, and ability assign permissions to allow users (groups) to access the content. Also responsible for the promotion and certification of content and measurement the use of analytics within their site.
  • Coordinated and collaborated with personnel primarily focused on data engineering, to develop schemas and tables to calculate metrics for anomaly detection. Utilized the Census Bureau’s Unified Tracking System’s (UTS) data warehouse to extract, transform and load tables for metrics calculations.
  • Developed extensive documentation of outlier/anomaly detection and metric development in the form of Jupyter Notebooks, providing a clear and robust trail of work from data extraction, data transformation and data analysis and visualization.
  • Developed and managed a Division-level Red Hat Enterprise Linux server environment, to, automate queries, metric calculations, data uploads and visualizations. Led the collection of server and software requirements.

US Army Public Health Center and One Health

I previously worked on implementing One-Health data-driven solutions on surveillance databases including incorporating spatial resolution and developing advanced data management methodologies and techniques within animal disease surveillance programs in Central Asia and with the United States Army’s Veterinary Service.

My primary research goal, at the time, was to develop and/or improve the accuracy of surveillance, spatial and genomic public health databases in semi-developing and/or developed countries, through the integration of other large heterogeneous and/or unstructured datasets. This will be done by creating health modeling programs and subroutines that will collect, compile and integrate useful health data to:

  • Observe and predict the burden of disease within companion animals groups, using surveillance data
  • Determine and predict spread and distribution of zoonotic and vector-borne infectious diseases.
  • Allow easier access to more accurate and realistic ecological data.

Additionally, I’ve focused on developing tailored ‘Big data’ approaches that can facilitate the analysis of multi-dimensional heterogenous data such as metagenomic, expression and phylogenetic data combined with clinical metadata to explore system biology approaches investigating various comorbidities associated with zoonoses.

In 2017 -2018, I joined Jason Blackburn’s Spatial Epidemiology & Ecology Research Laboratory (SEER Lab). The SEER Lab is an interdisciplinary research laboratory jointly housed in the Emerging Pathogens Institute and the Department of Geography at the University of Florida. SEER Lab is focused on questions addressing the ecology and spatio-temporal patterns of diseases. SEER Lab research is focused primarily on bacterial zoonoses, those bacterial diseases that affect both animals and humans.

From 2018 to 2021, I worked at the Army Public Health Center as an Epidemiologist for the One-Health Division, in the Veterinary Service and Public Health Sanitation Directorate. The current projects I have been focusing on are:

  • Government and Privately-owned Animal Worldwide Surveillance System (GPAWSS)
    • Chief scientist and co-project manager for GPAWSS. GPAWSS is a surveillance platform designed to provide surveillance data to inform commanders and VCOs of the distribution, frequency, and incidence of various companion animal diseases. The platform uses multiple heterogeneous data streams including: Remote Online Veternary Record (ROVR) EHR data, laboratory data, and data from a civilian corporate companion animal practice. Data in GPAWSS is managed by the One-Health Division and is displayed on an interactive, web-based platform (Tableau and R-Shiny) tracking disease frequency and incidence globally. GPAWSS also has outbreak detection capabilities.
  • Modernizing the Data infrastructure of the Veterinary Services and Public Health Sanitation Directorate (VSPHS)
    • The VSPHS is currently at a crossroads in terms of the organization of data in a manner that allows forincreased collaboration with outside organizations and encourages creativity and the discovery of noveldata sources and research methods. i) The project intends to: Establish a data etiquette protocol withinthe VSPHS in order to establish a data standardization protocol, simplifying future data integrationwith outside organizations ii) Restructure the data storage structure of the directorate, establishingstandardized databases, per division and housing them within the Army Engineer Research and Development Center (AERDC) DoD Supercomputing Resource Center’s data infrastructure (DSRC). TheAERDC’s Data Lake structures allows for the positive control of potentially all of the directorate’s datain a single source that can be updated at one point, decreasing areas of inaccessible and siloed data. My exapansive experience with data cleaning, restructuring and manipulation techniques allows me tolead this project for the directorate in terms of methodology, collaboration and planning.

I’m constantly working on new projects and seeking to connect with people! Drop me an email if you want to talk about research or academic/industry life!

Contact me



  • Bayko, H.; Watkins, S.; Waugh, S.; Moore, G.; Mullaney, S. Adaptation of the One Health Zoonotic Disease Prioritization Tool for Government- and Privately Owned Companion Animal Zoonotic Disease Surveillance. Zoonotic Dis. 2023, 3, x. https://doi.org/10.3390/xxxxx Seal, L., Mullaney, S, Waugh, S.. 2022. Leishmaniasis in the United States military veterinary patient population. Journal of the American Veterinary Medical Association. PMID: 34780354
  • Wijayabahu, A.T., Waugh, S., Ukhanova, M. and Mai, V., 2019. Dietary raisin intake has limited effect on gut microbiota composition in adult volunteers. Nutrition journal, 18(1), p.14. PMID: 30845997
  • Tagliamonte, M. S., Waugh, S., Prosperi, M., & Mai, V. (2019, September). An Integrated Approach for Efficient Multi-Omics Joint Analysis. In Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (pp. 619-625). ACM. PMID: 31588431
  • Waugh, S., and Mullaney, S. “Progress towards Companion Animal Zoonotic Disease Surveillance in the US Army.” Online Journal of Public Health Informatics 11.1 (2019). PMCID: PMC6606092
  • Ball, J. D., Fe Agana, D., Waugh, S., Wang, K., James, T. G., Nicolette, G. (2019). Systematically collected information at encounters with HIV-positive students: A review of 10 years of electronic medical records. Journal of American College Health, 1-5. PMID: 30681932
  • Spatial-Genomic Association of Co-Circulating Brucella Strains in Southern Kazakhstan: PhylogeneticInferences Using MLVA Data, Waugh, S.(Submitted)
  • Brucellosis Transmission Between Humans and Domesticated Livestock in Southern Kazakhstan: Inferences through MLVA Typing, Waugh, S.(Submitted)
  • Visualizing the Occurrence of Zoonotic Diseases among Military Associated Canines, Waugh, S.(Submitted)
  • Jennifer C. Dennis, Tyler Culpepper, Carmelo Nieves, Jr., Cassie C. Rowe, Alyssa M. Burns, CarleyT. Rusch, Ashton Federico, Maria Ukhanova, Waugh, S., Volker Mai, Mary C. Christman, BobbiLangkamp-Henken, Probiotics (Lactobacillus gasseri KS-13, Bifidobacterium bifidum G9-1, and Bi-fidobacterium longum MM-2) improve rhinoconjunctivitis-specific quality of life in individuals withseasonal allergies: a double-blind, placebo-controlled, randomized trial. Am J Clin Nutr 105, 758767(2017). PMID: 28228426
  • Waugh, S. App.: Gut Microbiota Differences in Children From Distinct Socioeconomic Levels Livingin the Same Urban Area in Brazil. Journal of Pediatric Gastroenterology and Nutrition (2016). PMID:28644365
  • Oliveira, F.P. de, Mendes, R.H., Dobbler, P.T., Mai, V., Pylro, V.S.,Waugh, S., Vairo, F., Refosco,L.F., Roesch, L.F.W., and Schwartz, I.V.D. (2016). Phenylketonuria and Gut Microbiota: A ControlledStudy Based on Next-Generation Sequencing. PLOS ONE 11, e0157513. PMID: 27336782
  • Dahl, W. J., Ford, A.L., Ukhanova, M., Radford, A., Christman, M.C.,Waugh, S., Mai, V. Resistant potato starches (type 4 RS) exhibit varying effects on laxation with and without phylum level changesin microbiota: A randomised trial in young adults. Journal of Functional Foods 23, 111 (2016).
  • Waugh, S. Apropos: Plasmodium knowlesi malaria an emerging public health problem in Hulu Se-langor, Selangor, Malaysia (20092013): epidemiologic and entomologic analysis. Parasites Vectors 8,79 (2015). PMID: 25651916
  • Mai, V.,Waugh, S., Byrd, D., Simpson, D. Ukhanova, M. Novel encapsulation improves recovery ofprobiotic strains in fecal samples of human volunteers. Appl Microbiol Biotechnol 17 (2016). PMID:27796434
  • Waugh, S., Varma, D., Striley, C., Cottler, L. Comparing Spatial Techniques to Visualize HypertensionSpread and Risk Factors for Hypertension Using Self-report from Community Participants. AppliedGeography (2015). (Submitted)