Greater Seattle Area
I translate biological complexity into products that work in the real world. Over 15 years spanning epigenomics, multimodal ML, and translational diagnostics, I've led teams that delivered FDA 510(k) cleared and CE-IVDD approved products, work that required equal parts scientific rigor, regulatory fluency, and the ability to move cross-functional teams from discovery through to clinical adoption. My experience spans the full arc from discovery to translation to product. I've built and led computational biology, bioinformatics, and biostatistics functions from the ground up, designing ML pipelines, directing biomarker discovery programs, securing competitive funding, and translating molecular profiling into scalable platforms. The through-line has always been the same: rigorous science in service of something that actually reaches patients. I lead by building trust across disciplines and I'm as comfortable presenting scientific strategy to boards and investors as I am in a data review with a research team. I'm most effective in environments where the problems are hard and the stakes are high.
- Launched the Aging Research Center (ARC), a large-scale multimodal research platform supporting longitudinal longevity and sleep studies in partnership with the University of Oxford, serving as PI or Co-PI across both programs. - Expanded the APEX epigenetic platform to interoperate with ARC, extending its capabilities to support biomarker discovery at scale and personalized health modeling across multiple data modalities. - Built the scientific team, computational foundations, and external partnerships that enabled the company to grow from a single consumer test to a portfolio of 10 products on market, with 4 in late-stage development. - Built computational biology, validation, and statistical analysis frameworks underpinning epigenetic algorithm development and biomarker discovery. - Led development of predictive and generative ML systems integrating multiomics and physiological data, with contributions spanning internal research programs, peer-reviewed publications, and commercial product development. - Chaired the Diagnostics and Screening working group for the INTERBIO-21 global consortium, a multi-national initiative focused on early life determinants of abnormal fetal growth.
- Led computational biology and biostatistics programs supporting two FDA 510(k) clearances and CE-IVDD approval for genomic diagnostic products. - Developed bacterial, fungal, and viral host-response signatures achieving AUC >0.9 for infection classification and antimicrobial resistance prediction. - Secured $750K in BARDA funding to expand pathogen detection and host-response ML programs. - Designed multi-site genomic studies and data harmonization pipelines supporting biomarker discovery, clinical validation, and regulatory submission. - Acted as primary computational and statistical liaison with regulatory agencies across multiple diagnostic submissions. - Built and mentored a team of data scientists and biostatisticians, establishing reproducible computational workflows and QMS-aligned analytical best practices.
- Secured $749K in GEODESIC funding for pediatric sepsis genomics research, developing computational approaches to host-pathogen interaction modeling. - Contributed statistical analyses and computational pipelines to the FDA 510(k) submission for SeptiCyte LAB, the first host-response sepsis diagnostic of its kind, cleared in 2017. - Developed ML pipelines for discovery-phase R&D targeting infectious disease signatures across a range of pathogens and clinical settings. - Worked directly with CROs to prepare and analyze multi-site clinical data for regulatory and R&D purposes. - Inventor on multiple patents covering genomic biomarker discovery and inflammatory response modeling. - Contributed to peer-reviewed publications arising from sepsis genomics research programs.
- Secured $116,504 in competitive grant funding for virtual proteomic library development and computational biology infrastructure. - Developed ML algorithms integrating proteomic and genomic signals to classify wound healing trajectories and predict treatment responses in pediatric burn and chronic wound patients. - Discovered protein biomarker panels distinguishing burn severity through computational analysis of multi-omics datasets. - Coordinated research relationships across a consortium of partner institutions including the University of Queensland, Queensland Facility for Advanced Bioinformatics, and the Centre for Children's Burns and Trauma Research. - Built novel bioinformatics workflows spanning machine learning, statistical modeling, and data mining for clinical diagnostic applications.
- Defense Science and Technology Organization (DSTO) of the Australian Defense Force. Provided subject-matter expertise.