
David
PhD
Expertise
neural signal processing, data science and statistics, AI/ML for medical applications

Polygence mentors are selected based on their exceptional academic background, teaching experience, and unique ability to inspire the next generation of innovative thinkers and industry leaders.

neural signal processing, data science and statistics, AI/ML for medical applications

Bioinformatics, computational biology, immunology, stem cell biology, cancer biology, robotics, and data science.

Software Engineering, Machine Learning, Data Science, Applied AI/RAG Systems, Full-Stack Development

Aging and aging-related diseases; maternal and child health; epidemiology; Alzheimer's disease and related dementia; frailty; cognitive decline

Survey research, Statistics, Quantitative research, Data analysis, Data Visualization, Business Intelligence

Mathematics, Physics, Mathematical Physics, Coding, Data Analysis. My area of expertise in mathematics is symmetry, and generalized symmetries that arise in mathematical physics.

Economics, Monetary Policy, Behavioral Economics, Game Theory, Econometrics, Forecasting

Behavioral genetics, genetic and environmental risk factors for dementia/Alzheimer's Disease, health psychology, biological aging

Health Disparities, Demography, Computational Methods, Social Networks, Social Media, Social Inequality

research methods, conference presentations, clinical psychology, neuropsychology, basic statistics, basic coding in R, Alzheimer's disease research, concussion research

Public Policy, Program Evaluation, Criminal Justice Reform, Prisoner Reentry, Education

physics (theoretical and observational cosmology, astro-particle physics), mathematics and statistics

Parenting, MRI analysis, fNIRS, substance use, mental health, emotion, statistics

Statistical analysis, including regression, longitudinal analysis, and machine learning using R. Statistical analysis in topics such as politics, education, public health, and economics. Research design, including experimental design and survey design. Comparability studies, including propensity score matching and measurement invariance.

Public health, biotech, medicine, data science, statistics, public policy