Golnaz Taheri

Golnaz Taheri is an Assistant Professor at KTH Royal Institute of Technology and a Data-Driven Life Science SciLifeLab and Wallenberg (DDLS) Fellow. She holds a Ph.D. in Computer Science and specializes in applying machine learning to biological data, particularly in cancer genomics and personalized medicine. Her work bridges computational methods with life sciences to uncover biological system insights.

Previously, she served as an Assistant Professor at Stockholm University's Department of Computer and System Sciences (DSV), where she coordinated large-scale courses and supervised graduate students in computational biology. Her research focuses on developing novel machine learning frameworks for analyzing complex biological datasets, including cancer mutation analysis and drug interaction prediction.

• Awards: DDLS Fellowship (SciLifeLab/Wallenberg)
• Key Projects: GenePioneer Python package, drug repurposing for SARS-CoV-2
• Teaching: Examinations and course coordination for statistical methods in computer science

Her research spans machine learning applications in oncology, virology, and systems biology, with a focus on translational medicine and computational tools for healthcare innovation. Current PhD openings exist in machine learning/deep learning for cancer and drug interaction studies.