I am a Ph.D. computational biologist and PMP-certified project leader with more than 20 years of experience spanning biomedical research, data science, and federal health missions. Much of my career was with Leidos Biomedical Research (LBR) supporting the Frederick National Lab for Cancer Research, where I collaborated closely with NIH, NCI, national labs, and other government agencies. Over the years, I have authored over 50 peer-reviewed publications, including in high-impact journals such as Nature Genetics, Nature Communications, Leukemia, Scientific Reports, and Bioinformatics. These contributions reflect my computational biology depth and my long-standing engagement with the scientific community NIH serves. This background gave me not only broad exposure across the federal health ecosystem but also a strong grounding in the values of openness, rigor, and research integrity that are central to NIH and its partners.

Since 2021, I transitioned into Leidos’ Health group, building on my prior work at the Frederick National Lab, and I now serve in the Digital Modernization group. My recent focus has been on real-world evidence (RWE) initiatives, including leading the Insilico Clinical Trial project — a Leidos effort to advance RWE through causal modeling [link]. Within ARPA-H, I advised the CTO as part of the Data Innovation team on the impact of AI applications to biomedical data, and I now serve as the Leidos technical development lead for the ARPA-H GRACE AI Assistant, where I am promoting the responsible use of AI/ML in biomedical data by developing explainable systems, reducing hallucinations, ensuring provenance, and improving reproducibility. Alongside these initiatives, I continue to mentor data scientists and teach as adjunct faculty, reaffirming my long-term commitment to advancing science through data integrity and innovation.

NIH’s mission growth today hinges not only on digital modernization and AI but also on research integrity, transparency, and reproducibility. As the NIH Director and others have emphasized, research integrity means protecting the credibility of science through openness, independence, and rigorous reproducibility. My background bridges both sides: deep NIH domain experience from my years at LBR, where I worked within NIH’s scientific culture, and cutting-edge AI/RWE innovation from my work in Health and Digital Modernization. This combination enables me to help position Leidos as a trusted partner to NIH — one that can deliver advanced, modern solutions while safeguarding the rigor and trustworthiness NIH demands. Beyond solution delivery, I bring value by advising on data and AI strategy, representing Leidos at conferences and scientific forums, and continuously upskilling to stay ahead of emerging technologies. These efforts not only strengthen our proposals and project delivery but also elevate Leidos as a visible thought leader and long-term partner in NIH’s evolving mission.