Persönlicher Status und Werkzeuge

Prof. Dr. Julijana Gjorgjieva

Assistant Professor

Computational Neuroscience

Contact Details

Business card at TUMonline

Academic Career and Research Areas

Professor Gjorgjieva (b. 1983) conducts research in the fields of computational and theoretical neuroscience. She is interested in how brain circuits become tuned to maintain a balance between constant change as we learn new things, and robustness to produce reliable behavior. In particular, she concentrates on two aspects of neural circuit organization, looking at how it emerges from the interaction of neuronal and synaptic properties during development, and from optimality and energy conservation principles that operate over the longer timescales of evolution.
Professor Gjorgjieva studied mathematics at Harvey Mudd College in California, USA. After obtaining a PhD in Applied Mathematics at the University of Cambridge in 2011, she spent five years in the USA as a postdoctoral research fellow at Harvard University and Brandeis University, supported by grants from the Swartz Foundation and the Burroughs-Wellcome Fund. In 2016, she set up an independent research group at the Max Planck Institute for Brain Research in Frankfurt and joined TUM as an assistant professor shortly after as part of the MaxPlanck@TUM program. She is also a member of the Bernstein Center for Computational Neuroscience in Munich.


  • Burroughs-Wellcome Career Award at the Scientific Interface (2015)
  • Swartz Foundation Postdoctoral Fellowship (2014)
  • Grass Foundation Independent Investigator Fellowship (2013)
  • University of Cambridge: Cambridge Overseas Research Fellowship (2007-2010)
  • Trinity College Cambridge: Research Scholar (2007-2010)

Key Publications (all publications)

Gjorgjieva J, Evers JF, Eglen SJ. “Homeostatic activity-dependent tuning of recurrent networks for robust propagation of activity”. Journal of Neuroscience. 2016; 36(13): 3722-3734.


Gjorgjieva J, Mease RA, Moody WJ and Fairhall AL. “Intrinsic neuronal properties govern information transmission in networks”. PLoS Computational Biology. 2014; 10(12): e1003962. Doi: doi:10.1371/journal.pcbi.1003962.


Gjorgjieva J, Sompolinsky H, Meister M. “Benefits of Pathway Splitting in Sensory Coding”. Journal of Neuroscience. 2014; 34(36): 12127-12144.


Gjorgjieva J, Berni J, Evers JF, Eglen SJ. “Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling”. Frontiers Comp Neurosci. 2013; 7(24). Doi: 10.3389/fncom.2013.00024.


Gjorgjieva J, Clopath C, Audet J and Pfister JP. “A triplet spike-timing-dependent plasticity model generalizes the Bienenstock-Cooper-Munro rule to higher-order spatiotemporal correlations”. Proc Natl Acad Sci USA. 2011; 108(48): 19383-19388.