Fatma Deniz

Fatma Deniz is a Full Professor at the Faculty of Electrical Engineering and Computer Science, Technische Universitaet Berlin. She combines computational neuroscience, data science, and artificial intelligence to investigate how complex information is encoded in the human brain during natural tasks. Her lab develops machine-learning approaches for analyzing multimodal brain data, with a current focus on multilingual brain representation.

• Education: PhD in Computational Neuroscience (Bernstein Center Berlin), M.Sc. in Computer Science (Technical University of Munich), thesis work at Caltech
• Past Appointments: Helen Wills Neuroscience Institute (UC Berkeley), Berkeley Institute for Data Science, International Computer Science Institute (Berkeley)

Her research spans scientific reproducibility (co-editor of a UC Press book), image-based authentication (MooneyAuth), and Mooney image databases. She has received prestigious fellowships including Moore-and-Sloan Data Science Fellow and DAAD Postdoctoral Fellowship. Her GitHub repository denizenslab/pymooney contains Python tools for generating Mooney images.

• Scientific Awards:
  • Moore-and-Sloan Data Science Fellow
  • DAAD Postdoctoral Fellow

Her work has been featured in major media outlets including Nature Neuroscience, MIT Technology Review, Discover Magazine, and ScienceDaily.