Assistant Professor
Duke University
Daniel Reker is a tenure-track Assistant Professor of Biomedical Engineering at Duke University and a Duke Science and Technology Fellow. He holds degrees in Computer Science (B.Sc., with honors) and Computational Biology and Bioinformatics (M.Sc., with honors), and earned his PhD in Pharmaceutical Sciences at ETH Zurich. He completed postdoctoral training at MIT as a SNSF Fellow with Bob Langer and Giovanni Traverso.
At Duke, he leads an integrated experimental and computational laboratory that develops active machine learning approaches for molecular discovery and delivery, aiming to accelerate and optimize therapeutic development. His work has been recognized with honors including Forbes 30 Under 30 in Science and Healthcare, the NIBIB “Trailblazer” Award, and the NIGMS “Outstanding Investigator” Award. His research has produced 50 peer-reviewed publications and eight provisional patents on drugs, formulations, and algorithms.
Daniel is also a devoted teacher, mentoring students from high school to clinical residency and teaching courses on topics ranging from biomaterials to machine learning. He was honored with Duke’s Klein Family Distinguished Teaching Award.
In his free time, he is an avid runner and recently completed his third marathon in 3 hours and 15 minutes.
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Keynote: Machine Learning for Small Molecule Drug Development and Delivery
Monday, November 10, 2025
1:30 PM - 2:30 PM CT