Aug 2022 – May 2025 · 2 yrs 9 mos

• As part of the Global Biometrics and Data Management organization in the AI/ML Digital and Quantitative Sciences Group within Global Product Development (GPD), I lead a team of statisticians and data scientists to enable end-to-end clinical trial innovation with imaging, digital health technologies and statistical, AI/ML methodologies. We work across Pfizer's early, late and established portfolio and leverage models such as Bring-Your-Own-Device and Decentralized Clinical Trials to enable efficient, patient-centric trials and faster breakthroughs for patients.
• This team was part of Early Clinical Development (ECD) until December 2022

Dec 2021 – Aug 2022 · 8 mos

Jan 2019 – Nov 2021 · 2 yrs 10 mos

• My group sits within Early Clinical Development (ECD) Non-Clinical Statistics in Worldwide Research and Development. We work with ECD Digital Medicine and with research units to employ wearable, mobile and environmental sensor technology to impact clinical trials across Pfizer’s early, late, and established portfolios. We provide expertise on experimental design, data collection, data analysis, and on the development and application of state of the art statistical and machine learning methods for the discovery of new digital biomarkers from these technologies.

Jun 2017 – Dec 2018 · 1 yr 6 mos

Aug 2016 – Jun 2017 · 10 mos · Cambridge, Massachusetts

• I use data science to improve treatment discovery and delivery for patients suffering from neurodegenerative diseases.

Jan 2016 – Mar 2016 · 2 mos · Boston

• Consulted for Constant Therapy and used SQL to mine data collected by their brain rehabilitation app
• Delivered a framework that smoothens noisy behavioral data, selects features of interest from user's demographic and baseline performance and predicts user's improvement on tasks through linear, radial SVM and random forest regression
• Developed an interactive front-end using Flask, Bootstrap css, HTML, jQuery, JSON and AJAX: www.therapyprospector.me

Sep 2013 – Aug 2016 · 2 yrs 11 mos · Psychiatric Neuroimaging, Charlestown, MA

• Developed data analysis pipelines comprising time-frequency analyses, blind source separation, source localization, k-means clustering and mixed model regression to investigate the mnemonic role of brain oscillations during sleep in health and schizophrenia
• Executed data analyses of an NIH-funded pharmacological, clinical sleep study (~220 records, 8-hr sleep recordings), and data collection of an MEG-EEG study
• Secured 2-year funding from the Brain & Behavior Research Foundation NARSAD Young Investigator Grant, and act as investigator on MGH-MIT Strategic Initiative’s Grand Challenge #3 on Neurosciences grant
• Coached research assistants on clinical data collection and preprocessing

Aug 2010 – Jul 2013 · 2 yrs 11 mos · Heidelberg, Baden-Württemberg, Germany

• Employed supervised (multivariate test statistics and bootstraps) and unsupervised (Hidden Markov Models) approaches to discriminate task-specific information processing in various brain regions
• Developed a feature extraction algorithm that builds on regularized linear discriminant analysis and finds maximally predictive feature set through a forward-backward procedure
• Applied these methods to fMRI data (very high dimensional, sparse data with thousands of voxels and few time points) to study working memory and decision making in health and schizophrenia
• Delivered lectures and tutorials on statistics and computational neuroscience at the University of Heidelberg to students from backgrounds as diverse as physics, mathematics, engineering, biology, psychology, and medicine
• Coordinated weekly BCCN Heidelberg-Mannheim External Speaker Seminar Series