Our team of exceptional talent is led by category pioneers that shaped Scientific Wellness and Health AI.
I lead the Price Lab’s scientific vision, integrating AI, multi-omics, and deep phenotyping to advance predictive, proactive healthspan science and transform longevity research into real-world impact.
I drive the Price Lab’s strategic direction, advancing global leadership in healthspan optimization through aging science, deep data systems, and real-world translational pathways.
I lead the development of AI systems that integrate multi-omics and genetic predispositions with clinical and behavioral data to advance predictive modeling, early detection, and personalized intervention in human health.
We are guided by top minds in science and business that have helped solve big humanity problems.
President and CEO of the Buck Institute, Dr. Eric Verdin is a world-leading aging scientist advancing metabolic and epigenetic mechanisms to translate longevity science into transformative human health impact.
An interdisciplinary team advancing rigorous systems biology and AI to turn complex health data into clinically and societally meaningful insights.
I study natural products and nutraceutical interventions alongside environmental and socioeconomic exposures to understand their impact on healthspan using systems biology and curated knowledgebases.
I own the full-stack systems behind our biomedical data and AI agent platforms, turning raw research ideas into secure, scalable production applications.
I develop the Price Lab’s AI and data infrastructure, integrating multi-omic and clinical data to power intelligent healthspan models and personalized, scalable interpretation across aging.
I integrate multi-omics data with advanced AI, particularly multi-agent LLM systems, to decode mechanisms of aging and accelerate translational biomarker and therapeutic discoveries.
I lead the development of AI systems that integrate multi-omics and genetic predispositions with clinical and behavioral data to advance predictive modeling, early detection, and personalized intervention in human health.
I support the Price Lab’s AI and data infrastructure, helping integrate multi-omic, clinical, and wearable data into tools for understanding health trajectories and aging.
I investigate how the immune system ages, using quantitative and spatial profiling approaches to reveal mechanisms connecting immunity, the brain, and neurodegeneration.
I work on developing novel genomic approaches to detect signatures of improved health, resilience and early disease.
I build novel AI systems to translate multi-omic information into precise and personalized insights to target ageing related decline and early disease.
I design and implement software for the Price Lab’s AI platform, translating big health data into personalized and actionable insight.
I lead the Price Lab’s scientific vision, integrating AI, multi-omics, and deep phenotyping to advance predictive, proactive healthspan science and transform longevity research into real-world impact.
I apply multiomic analysis and machine-learning methods to investigate biological mechanisms underlying aging, microbiome function, and metabolic health.
I develop statistical methods for the analysis of multi-omics data in human populations to identify early signs of disease and avenues for personalized intervention.
I assist the development of statistical methods that integrate multi-omics to identify early signs of disease and opportunities for lifestyle interventions.
I integrate data science and environmental health to uncover environmental drivers of aging and reveal new pathways to extend lifespan, improve health, and help people live better longer.
I drive the Price Lab’s strategic direction, advancing global leadership in healthspan optimization through aging science, deep data systems, and real-world translational pathways.
Scientists and leaders shaped by the Price Lab who carry its rigor, vision, and impact into institutions advancing human health worldwide.
Dr. Wang’s work focuses on systems biology, network modeling, and computational analysis of multi-omics data, with applications in disease biology and complex trait analysis.
Dr. Ament leads research on genetic and genomic mechanisms of brain disorders, integrating large-scale sequencing, single-cell genomics, and systems biology to decipher neuropsychiatric disease pathways, including mood disorders, schizophrenia, and Huntington’s disease.
Dr. Baloni is a computational systems biologist specializing in metabolic and multi-omics modeling to uncover molecular signatures in neurodegenerative diseases (e.g., Alzheimer’s), cancer, aging, and complex gene–environment interactions.
Dr. Chandrasekaran leads the Systems Biology & Drug Discovery Lab, developing mechanistic AI and systems modeling tools for drug discovery, precision medicine, microbial metabolism, and host–pathogen interactions across cancer, infectious diseases, and regenerative medicine.
Dr. Chia uses computational and ecological modeling of the microbiome to investigate how microbial community structure and function influence human health and disease, including colorectal cancer and host–microbiome interactions with clinical and translational impact.
Dr. Ghosh is a systems biologist and metabolic engineer whose research spans genome-scale metabolic modeling, synthetic biology, multi-omics systems analysis, and machine learning applied to bioenergy, metabolic networks, and microbial community metabolism.
Dr. Li’s work focuses on machine learning, data mining, and computational modeling, with applications in biological data analysis, complex systems, and large-scale data integration.
Dr. Ma is a computational biologist studying gene regulation, single-cell and multi-omics data, and systems-level mechanisms underlying human disease and development.
Dr. Paquette focuses on systems genomics and network biology, applying computational approaches to understand immune function, development, and disease mechanisms.
Dr. Piekos specializes in computational genomics and precision medicine, leveraging large-scale biobank and EHR-linked datasets to study disease risk, progression, and population health.
Dr. Samal is a theoretical and systems biologist whose research spans network biology, metabolic systems, and evolutionary dynamics of complex biological systems.
Dr. Sung conducts research in systems biology and multi-omics integration, focusing on metabolic health, disease mechanisms, and translational applications in clinical populations.
Dr. Vellaichamy’s research centers on proteomics, systems biology, and computational analysis to uncover molecular mechanisms of disease and cellular regulation.
Dr. Wainberg develops statistical and computational genomics methods, applying them to large-scale genetic datasets to understand complex traits, disease architecture, and biological networks.
Dr. Benedict applies systems modeling and data-driven decision frameworks to accelerate R&D innovation and complex problem-solving in industrial and materials science contexts.
Dr. Eddy focuses on computational biology and translational data science, supporting therapeutic discovery and precision medicine initiatives.
Dr. Funk leads biological strategy and translational research in neuroscience, bridging experimental biology with data-driven therapeutic development.
Dr. Heath works at the intersection of open science, neurodegenerative disease research, and collaborative data platforms to advance Alzheimer’s discovery.
Dr. Imam applies advanced analytics and machine learning to large-scale biomedical datasets to enable AI-powered drug discovery.
Dr. Levy develops computational and statistical models for population-scale health data, precision medicine, and longitudinal human studies.
Dr. Milne specializes in computational genomics and large-scale data analysis supporting collaborative biomedical research.
Dr. Pearl leads translational and therapeutic development programs, advancing discoveries from systems biology into clinical impact.
Dr. Raju applies data-driven strategy and operational analytics to optimize global biopharmaceutical supply chains.
Dr. Richards develops machine learning and data science solutions for large-scale visual, metadata, and content intelligence systems.
Dr. Sangar works on machine learning research and applied AI systems, translating advanced models into scalable real-world applications.
Dr. Wang builds machine learning systems and scalable AI infrastructure for large-scale consumer and research platforms.
Dr. Wang leads engineering teams and advanced ML system development, bridging research innovation with production-scale deployment.
Dr. Wilmanski develops health algorithms and digital biomarker models, translating multi-omics and lifestyle data into actionable health insights.
We collaborate with leading institutions worldwide to co-create large-scale, data-driven initiatives advancing precision health, longevity science, and population-level healthspan impact.
National precision health partnership advancing population-scale genomics, AI, and multi-omics to extend healthspan across the UAE.
Up to $52M ARPA-H award advancing AI-driven multi-omic analytics for personalized, proactive, and scalable precision health.
International clinical consortium advancing multi-omics biomarkers for early diagnostics, intervention tracking, and evidence-based healthspan extension.
Landmark longitudinal cohort integrating multi-omics, clinical labs, and lifestyle data to discover actionable health and aging signatures.
Decade-long contribution integrating human brain multi-omics to map disease networks and enable open-science Alzheimer’s discovery.
Led systems biology modeling integrating genetics and multi-omics to uncover mechanisms and pathways of healthy aging.
