bio

Maruan Al-Shedivat is a Director of Machine Learning at Genesis Therapeutics. His research is broadly focused on data-efficient machine learning, deep learning, probabilistic modeling, new computational frameworks for adaptation, personalization, and interpretability of statistical models learned from data, and applications to life sciences and engineering. He holds a Ph.D. degree in Machine Learning from Carnegie Mellon University, 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 data-efficient machine learning and explainable AI were recognized with multiple awards, including a best paper award at ICLR 2018, a CMLH Fellowship in Digital Health 2018, and a Google Fellowship in Machine Learning 2019-21.