Ivan Specht

Ivan Specht builds mathematical models for analyzing, predicting, and preventing the spread of infectious diseases. A graduate of Harvard College originally from New York City, he is the principal author of four scientific papers, with publications in Nature Scientific Reports and Cell Patterns. At the height of the pandemic, the New York Times featured his research on effective COVID-19 testing strategies, which were implemented by several universities in the United States. Most recently, Ivan developed a high-accuracy tool for reconstructing disease transmission networks, for which he holds a provisional patent. He has presented this method to the Centers for Disease Control and the National Institutes of Health, and has collaborated with leading infectious disease specialists in Sierra Leone to incorporate his work into the country’s outbreak response protocol. As a PhD candidate in computational and mathematical engineering at Stanford School of Engineering, Ivan aims to create the preeminent epidemiological toolkit for stopping pandemics.