<p>About Maura Pintor</p>
<p>Maura Pintor (female) is a Ph.D. Student at the University of Cagliari, Italy. She received the MSc degree in Telecommunications Engineering with honors in 2018, from the University of Cagliari (Italy) discussing a graduation thesis titled &quot;A novel temporal descriptor for analyzing small and large crowds by computer vision algorithms&quot;. Her research interests include adversarial machine learning and machine learning explainability methods, with applications in cybersecurity. She is co-author of the paper &quot;Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks&quot;, recently accepted to USENIX 2019. She is currently collaborating with Pluribus One in the European Project ALOHA, aimed to create a framework for optimizing the design of Deep Learning systems on heterogeneous low-energy computing platforms. Her contribution to the project focuses on the security evaluation and mitigation strategies against adversarial perturbations. She is currently enrolled in a PhD course on adversarial machine learning, and was visiting student at Eberhard Karls Universität Tübingen, from March to June 2020.</p>

Maura Pintor