US Biologic is a biotech company with a One Health perspective for addressing the human burden of disease through their novel patented oral vaccine platform. As they expand their vaccine product portfolio, I am bringing evidence-based intervention strategies using evidence synthesis of real-world data and high-resolution clinical data to generalize intervention prioritization.

Orange LLC has two focuses: providing expert advice on AI, data analytics, zoonotic, wt lab protocol development, and One Health/public health as well as design custom wet lab tools for scientists to reduce the burden of doing research through the creation of efficient, standardized tools that enhance the speed and reproducibility of tedious tasks.

The data and analytics technical lead for the Artificial Intelligence Center of Excellence (AI COE) responsible for prioritizing research questions, designing appropriate data science studies, and carrying out successful projects on time. In addition to leading the enterprise-wide effort across the company, I am the primary contact for the Director of Governance, Risk and Compliance, the Senior Compliance Director, the Global Information Security Director, and Director of Regulatory Affairs with regard to policies, procedures, and risk assessment for topics in scope of AI, data, and research.The creation of the group is the result of a review of the competition and a gap analysis in my previous role as a senior data scientist presented to senior company leadership for the creation of an enterprise wide group in R&D to provide AI, data, and analytics expertise. Initial priorities include establishing IT infrastructure (AWS S3/Athena storage, Jupyter/Sagemaker Studio analytics env), company wide search for actionable data assets (product customer patient data, business/sales data, commercial datasets), and R&D governance efforts.

Projects include using machine learning (tensorflow/keras) to perform deep learning on medical imaging for implant prediction, clustering/subgroup characterization of 3D anatomical models to identify variability in both derived measures (width, height, thickness, clinical measures) as well as in statistical shape modeling using principal component analysis methodologies. In collaboration with information owners and computer scientists, two large projects designing a framework for medical imaging data management, backend infrastructure, and frontend needs for data scientists in a cloud environment as well as addressing the infrastructure needs from a compliance and legal perspective drafting policies to guide information owners on data sharing with the goal of minimizing risk and formalizing protocols.

As a senior research fellow, I used whole genome sequencing (WGS) to identify a high-risk subgroup of childhood cancer survivors and sickle cell disease patients. My responsibilities included creating clinical bioinformatic analytical pipeline combining whole genome sequencing, functional histone marker data, and population level recombination clustering resulting in multiple peer reviewed publications.

Taught a genome wide association study (GWAS) course for researchers and clinicians. Attendees developed an understanding of how the data is collected, sequenced, genotyped, quality controlled, the underlying assumptions of a GWA analysis, and practical experience running a GWAS analysis during a workshop with PLINK and R Statistical Programming language.

Organized a lecture series on the R statistical programming language for postdoctoral fellows with 270 participants. After polling the St. Jude postdocs to determine what they were interested in, we invited recognized experts in the fields of statistics, biostatistics, computational biology, pharmaceutical sciences, and the hematology to speak at one of the nine lectures.The lecture topics were split into two groups: Core Concepts and Advanced Topics. Core concepts included, 'Statistical Reasoning', 'Basic R', 'Graphics with R', 'Simple Statistical Tests', 'Identifying and Characterizing Outliers', and 'Regression and other Machine Learning Algorithms', while the Advanced Topics included, 'Expression Data: RNA-seq', 'Expression Data: ChIP-seq and ATAC-seq', and 'Statistical Design, Analysis, and Interpretation of GWAS'. For each of the lectures, a separate 2 hour workshop was designed for participants to learn how to use R.

Worked quantifying the human dose-response relationships for Q fever with the goal of predicting latent outbreak infection and illness spatial dose-response modeling to estimate asymptomatic infections at risk of chronic Q fever for the government during the world's largest Q fever outbreak in the Netherlands. This work led to novel evidence synthesis methodology development combining clinical challenge data with real world outbreak data to generalize small clinical studies to the general population. The spatial predictions made could be used to estimate the bacterial exposure load of the aerosol dispersion of Coxiella burnetii. Publications from my work led to me obtaining my PhD in Clinical Epidemiology.

Working in the Epidemiology and Surveillance department of the Netherlands CDC as part of the outbreak Q Fever Group. Work included modeling serological profiles of Q fever patients to identify acute cases at risk of developing chronic forms of the illness to guide clinical protocols and serological surveillance.Invited researcher to the CDC in Atlanta representing the Netherlands CDC providing an update and overview of the world's largest Q Fever outbreak in the Netherlands, a class B bioterror agent, at the height of the outbreak.Other responsibilities included health economics work as an analyst for the 'Burden of Communicable Diseases in Europe' (BCoDE) project, a project funded by the European Centre for Disease Prevention and Control (ECDC) and led by the Dutch National Institute for Public Health and the Environment (RIVM). The aim of this ongoing project is to quantify the burden of 41 communicable disease in 30 countries in Europe in terms of Disability Adjusted Life Years (DALYs) using a standardized methodology.

Working administrative position as well as leading multiple internal projects focused on ensuring data integrity for cases and clients. Client contact and organizational skills were required daily to maintain the integrity of the organization.