Maruan Al-Shedivat is a PhD student in the Machine Learning Department at Carnegie Mellon University, advised by Prof. Eric Xing. His research interests are in probabilistic modeling, multi-task learning, and deep learning, with a focus on computational frameworks for adaptation, personalization, and interpretability of statistical models learned from data. Maruan holds a Bachelor’s degree in Physics from Moscow State University (where he was a Lomonosov Fellow) and Master’s degrees in Data Analysis and Computer Science from Yandex School of Data Analysis and KAUST, respectively. His work on meta-learning and continuous adaptation in multi-agent systems has received a best paper award at ICLR 2018. He is a recipient of the 2018 CMLH Fellowship in Digital Health and 2019 Google PhD Fellowship in Machine Learning.