My selected publications and projects at the bottom of this page (presented with the most recent first, so in reverse chronological order) have been chosen deliberately to highlight my three areas of strength, which show a lot of breadth, and which are also responsible for the very strong vision I have developed for the direction health research needs to and will very likely go. They also reflect the trajectory of my career through time, beginning with 1. my degree in genetic epidemiology and biostatistics at Case Western Reserve University and fellowship in computational genomics of cancer, followed by 2. my work with cancer prevention in underserved communities at the Cleveland Clinic Taussig Center and ending with 3. my immersion in medical education and clinical research at the Cleveland Clinic and my leadership in designing and helping execute research portfolios for pharmaceutical companies like Merck, Gilead and others, using real world data when I moved to industry.

1. Methodological expertise: I'm deeply versed in advanced statistical methodologies, in particular longitudinal and mixed effects models as well as integrative ‘omics analyses. such as association analyses (GWAS), family studies, rare variant analysis and expression analyses and the development of molecular profiles and ancestry studies. I have likewise developed instruments for measuring social and psychological level constructs in health and have collected and analyzed qualitative data for mixed methods research. I have taught epidemiological and clinical research design and biostatistics to PhD and medical students and introduced them to supervised and unsupervised machine learning when these became more popular. More recently I have developed an interest in geometric deep learning and agent-based modeling with AI which go beyond the simple development of verticals with LLM agents which are the current rage for AI in healthcare.
2. Patient-engagement and data collection through technology experience: I'm versed in patient engagement and data collection, not just for patient-reported outcomes and validated instruments, but the broader gamut of health associated variables spanning biomarkers, clinical, behavioral and socio economic and geocoded measures. I also have experience taking into account barriers in access to both research and healthcare by underserved communities, and how this impacts diversity representation in data. I have designed studies which pursue innovative ways for more effective inclusion of diverse populations.
3. Understanding of medical training and practice and the drug development ecosystem: I have a deep understanding of the nuts and bolts of the medical field. I've collaborated extensively with clinicians, trained them in research, and developed curricula to push forward that training into the digital age, the big data age, and the AI age. I understand the limitations and barriers they face. Likewise, I am familiar with the drug development ecosystem, what pharma's research priorities are, and their standard methodologies and where these fall short, particularly when it comes to precision medicine. I have studied FDA guidance documents for drug development and have an interest in the ethics and regulations behind direct-to-consumer testing.

This breadth of experience has provided me with a bird's eye view and has been instrumental in honing my vision for the future of healthcare and healthcare research. This was not by accident; I deliberately kept choosing avenues for greater meaning and impact in my work even when these did not correspond to the traditional route of a hyper specialized and publication focused, resume-building academic career. I truly believe that there are elements in the way we are doing research right now that are holding progress back and I am passionate about getting this vision out there and manifesting it in the work I continue to do - I feel a strong responsibility towards improving healthcare with the patient foremost in mind.

Below I connect my background to the insights I have distilled, which together form the three pillars of my overarching vision. My goal is to progressively expand on the reasoning underlying each of these pillars and to further build them, through social media engagement, substack articles and eventually full publications.

Projects

Validation of endpoints in Real World Data

DDISCOVRWES (Real World Data and Precision Medicine)

Developing Big Data and AI Competencies in Medical Education: A Novel Curriculum Approach

Patient activation through health information

Racial Heterogeneity in TNBC and Ovarian Cancer: Implications for PARP Inhibitor Trials

Comorbidities as quantitative traits: a study of complex disease