A team of researchers at Duke and the University of Maryland have created an algorithm that attempts to reflect the ethical choices that a human would make based on responses to surveys about who should get a kidney transplant.
Professor Massimo Fornasier of the Technical University of Munich (TUM) had another reason to visit Duke this Fall when he gave a mini-course for the Mathematics Department: he wants to bring Duke’s Data+ summer program to TUM!
Duke graduate student Anna Yanchenko and statistics professor Sayan Mukherjee are teaching computers to write classical piano music in the mode of great composers like Mendelssohn and Beethoven.
The National Academy of Inventors (NAI) has elected three faculty members from Duke University's Department of Biomedical Engineering to its 2017 class of Fellows.
Launching in Fall 2018, students will be able to receive interdisciplinary training within the quantitative sciences, exposure to problems in a variety of disciplines, and direct experience in interdisciplinary team-based science.
Duke Center for Autism and Brain Development Receive $12.5 Million Grant to Study ADHD, Autism ConnectionFriday, October 13 2017
Congratulations to Dr. Guillermo Sapiro, along with Dr. Geraldine Dawson, Linmarie Sikich, Scott Kollins, Scott Compton, Kenneth Dodge, Naomi Davis and Michael Murias of the Duke Center for Autism and Brain Development. They have received a 5-year, $12.5 million grant from the NIH to study the connections between ADHD and autism in children.
From a chance meeting at a Bass Connections faculty mixer, Geri Dawson and Guillermo Sapiro collaborated to create the No. 1 health app in the Apple app store – Duke Health’s Autism & Beyond.
Duke Undergraduates Use Machine Learning Techniques to Evaluate Electricity Access in Developing CountriesThursday, September 14 2017
A team of Data+ students, led by researchers in the Energy Initiative's Energy Data Analytics Lab and the Sustainable Energy Transitions Initiative, developed means to evaluate electricity access in developing countries through machine learning techniques applied to aerial imagery data.
iiD's Ghost Bikes Data+ team created an interactive website that demonstrates how factors such as the time of day, weather conditions and demographics affect crash risk.