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Golnaz Taheri holds a Ph.D. in Computer Science and currently serves as an Assistant Professor at KTH Royal Institute of Technology. Her academic journey has instilled a deep interest in machine learning and its transformative applications across various domains. Her research primarily focuses on advancing the field of machine learning, with a particular emphasis on developing novel methodologies to apply these methods to real-world problems. She is especially interested in leveraging machine learning techniques to analyze large-scale, complex biological data. Her fundamental goal is to enable a deeper understanding of biological systems through data-driven insights, facilitating developmental, temporal, and spatial explorations. By integrating machine learning into biological research, she aims to uncover patterns and relationships that contribute to advancements in personalized medicine, cancer genomics, and other life science fields. Previously, Golnaz designed and coordinated large-scale courses and supervised graduate-level research for Master's and Ph.D. students at DSV Stockholm University, promoting a collaborative learning environment to ensure students acquire the necessary knowledge and skills to excel in computational biology.
Master's programs are organized under Schools; departments listed are units within these schools (e.g., EECS, ABE, CBH, ITM, SCI).