Harvard Catalyst Profiles

I have a broad background in clinical psychology, epidemiology, statistical modeling, in addition to specific training and expertise in electrophysiology, psychiatric genetics and cognitive neuroscience. I continue to weave these interests together in my work with patients with psychotic disorders. I have conducted several neurobiological and genetics projects and have published papers spanning from characterizing event related potentials (ERP) deficits as potential endophenotypic markers (biomarkers) across psychotic spectrum disorders; identifying distinct subgroups of psychotic patients on the basis of neurobiological signatures that transcend diagnostic classification; to examining genetic and environmental risk factors for psychiatric disorders. My long-term interests are to gain a deep insight of the interplay between neurobiological mechanisms underlying psychotic disorders and environmental risks contributing to the development of illnesses and to utilize this knowledge for developing implementable and effective precision medicine tools or strategies in clinical services.
I am the PI of a NIMH funded longitudinal study (R01) that involves leveraging multivariate biomarkers (e.g., EEG, MRI, cognition, clinical phenotypes), each of which has been well studied in the psychosis literature, to stratify first episode psychosis patients into homogeneous subgroups based on patients’ unique neuro-biological profiles and relate these profiles to their functional outcome trajectories. The goal is to identify and predict patients who are not likely to achieve functional recovery and are at risk of relapse (readmission). To achieve this goal, my team and collaborators are developing computational tools using natural language processing (NLP) and machine learning algorithms to integrate both structured biomarker and unstructured clinical electronic health records (EHRs) data in the data analysis pipeline in order to augment knowledge discovery and to develop robust risk prediction models.