The National Center for Women & Information Technology (NCWIT) is pleased to announce the winners and honorable mentions of the 2022 NCWIT Collegiate Award, honoring the outstanding computing accomplishments of undergraduate and graduate women, genderqueer, or non-binary students. Conferred annually, the award recognizes technical contributions to projects that demonstrate a high level of innovation and potential impact.
Rachel Sterneck, Yale University, Energy Efficient and Robust Adversary Detection in Neural Networks
Although deep neural networks (DNNs) have great potential to be used in real-world vision tasks, their vulnerability to adversarial attacks – inputs that have been carefully perturbed to fool classifier networks while appearing unchanged to humans – must be addressed to ensure that machine learning applications are safe and reliable. For this project, the researchers created a structured methodology of augmenting a DNN with a detector applied to the most sensitive layer of the network. The method was shown to be an energy-efficient way to improve state-of-the-art detector robustness against adversarial examples. (View this project online.)
View a complete list of the 2022 recipients here.