Adam Li selected for NSF Graduate Research and Whitaker International Fellowships

20/03/2017

Adam Li, a doctoral student in the ICM lab of Sri Sarma, associate professor of biomedical engineering, has been selected to receive the 2017-2018 Whitaker International Program Fellowship and the 2017 National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) Fellowship. The Whitaker International Program Fellowship is administered by the Institute of International Education, an organization that is “strongly committed on behalf of The Whitaker Foundation to continuing to contribute to the career development of future leaders in the field of biomedical engineering, fostering greater international cooperation within the biomedical engineering community.” The NSF Graduate Research Fellowship Program “recognizes and supports outstanding graduate students in NSF-supported science, technology, engineering, and mathematics disciplines who are pursuing research-based Master’s and doctoral degrees at accredited United States institutions.” To be selected for two highly competitive fellowships is a significant accomplishment.

Adam, a 2nd year PhD student in biomedical engineering, aims to create advanced data analytics for neurosurgeons that are treating epilepsy patients. Current state of the art surgical resection of epileptic regions in the brain require precise and reliable localisations of problematic regions in the brain. Adam’s research involves analyzing brain recordings as a networked system and characterizing network system characteristics to make predictions of the onset region in epilepsy. In addition to building clinical tools, Adam seeks to understand epilepsy and different clinical seizures through computational modeling at a whole-brain level. Through this, he aims to look at dynamical system features for different types of seizures and build algorithms that can capture this information in real clinical data for diagnostics and treatment purposes.

Congratulations, Adam!

JHU - Institute for Computational Medicine