Summary
Daniel Vis is a postdoctoral research fellow with nine years of experience developing mathematical and statistical tools to predict patient-specific interventions, with a particular focus on time, stress, and personalized medicine. Trained as a PhD chronobiologist with a background in medical biology and a computer science minor, he blends multivariate and megavariate analysis, causal inference, Bayesian methods, and nonlinear dynamics to tackle complex biomedical problems. Currently at the Netherlands Cancer Institute’s Center for Personalized Cancer Treatment, he translates high-dimensional tumor data into actionable, individualized treatment strategies. Daniel’s work bridges academic rigor and practical impact—he has investigated hidden dynamics in regulatory systems and previously ran a biotech entrepreneurship venture, giving him a rare mix of technical depth and real-world product sensibility.
9 years of coding experience
8 years of employment as a software developer
PhD, Chronobiology, data analysis, time series, endocrinology, econometrics, PhD, Chronobiology, data analysis, time series, endocrinology, econometrics at University of Amsterdam