Description of Research Expertise

Dr Piekos's research leverages artificial intelligence (AI) to quantify the interplay between biology, environment, and lifestyle, advancing precision medicine through more targeted and affordable treatments. The Piekos Lab uses a systems biology approach to study pregnancy as a model of biological transition, focusing on how physiological processes are disrupted in disease. Pregnancy’s defined timeline and profound transformations provide a unique opportunity to study dynamic changes that are difficult to capture in aging or other conditions.

The lab integrates deep phenotyping data—including longitudinal multiomics, wearable data, environmental exposures, social determinants of health, and electronic medical records—to map molecular networks using AI. Methods include machine learning (ML), network analysis, large language models (LLMs), and knowledge graphs. After establishing a healthy baseline, the lab identifies molecular network disruptions linked to obstetric syndromes by analyzing cross-sectional and longitudinal changes. The goal is to detect the earliest deviations from a healthy trajectory and enable precise, patient-specific interventions early in disease. Dr. Piekos also investigates how environmental exposures, such as wildfire smoke and extreme heat, impact pregnancy outcomes at the population level.