I am a research scientist in the neuroscience group. My current research interests are in theoretical and computational neuroscience and machine learning.
Before joining the Simons Foundation, I was a postdoctoral associate at the Janelia Research Campus of the Howard Hughes Medical Institute. Previously, I was a Swartz fellow at Harvard University. I hold a doctorate in physics from Brown University.
My Google Scholar profile can be found here.
My ResearchGate profile can be found here.
The schedule of the Computational and Systems Neuroscience Journal Club can be found here.
Pehlevan C, Sengupta A, Chklovskii DB. Adversarial synapses: Hebbian/anti-Hebbian learning optimizes min-max objectives. arXiv:1703.07914
Chen Y, Pehlevan, C, Chklovskii DB. Self-calibrating neural networks for dimensionality reduction. 50th Asilomar Conference on Signals, Systems, and Computers. 2016
Abbasi-Asl R, Pehlevan C, Yu B, Chklovskii DB. Do retinal ganglion cells project natural scenes to their principal subspace and whiten them? 50th Asilomar Conference on Signals, Systems, and Computers. 2016
Pehlevan C, Paoletti P, Mahadevan L. Integrative neuromechanics of crawling in D. melanogaster larvae. eLife. 2016;5:e11031
Otchy TM, Wolff SBE*, Rhee JY*, Pehlevan C*, Kawai R, Kempf A, Gobes SMH, Ölveczky BP. Acute off-target effects of neural circuit manipulations. Nature. 2015; 528:358-363. (*equal contribution)
Pehlevan C, Ali F, Ölveczky BP. Flexibility in motor timing constrains the topology and dynamics of pattern generator circuits. bioRxiv preprint 2015.
Pehlevan C, Chklovskii DB. A normative theory of adaptive dimensionality reduction in neural networks. Advances in Neural Information Processing Systems 28. 2015;2260-2268.
Pehlevan C, Chklovskii DB. Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening. 53rd Annual Allerton Conference on Communication, Control, and Computing
Pehlevan C, Hu T, Chklovskii DB. A Hebbian/anti-Hebbian neural network for linear subspace learning: a derivation from multidimensional scaling of streaming data. Neural Comput. 2015;27(7):1461-1495.
Hu T, Pehlevan C, Chklovskii DB. A Hebbian/anti-Hebbian network for online sparse dictionary learning derived from symmetric matrix factorization. 48th Asilomar Conference on Signals, Systems, and Computers. 2014;613-619.
Guralnik Z, Pehlevan C, Guralnik G. On exact statistics and classification of ergodic systems of integer dimension. Chaos. 2014;24(2):023125.
Pehlevan C, Chklovskii DB. A Hebbian/anti-Hebbian network derived from online non-negative matrix factorization can cluster and discover sparse features. 48th Asilomar Conference on Signals, Systems, and Computers. 2014;769-775.
Pehlevan C, Sompolinsky H. Selectivity and sparseness in randomly connected balanced networks. PLoS One. 2014;9(2):e89992.
Ali F, Otchy T*, Pehlevan C*, Fantana A, Burak Y, Ölveczky BP. The basal ganglia is necessary for learning spectral, but not temporal, features of birdsong. Neuron. 2013;80(2):494-506. (*equal contribution)
Ferrante DD*, Guralnik G*, Guralnik Z*, Pehlevan C*. Complex path integrals and the space of theories. arXiv preprint 2013; arxiv:1301.4233. (*alphabetical order)
Guralnik Z, Pehlevan C, Guralnik G. On the asymptotics of the Hopf characteristic function. Chaos. 2013;22(3):033117.
Hu T, Towfic ZJ, Pehlevan C, Genkin A, Chklovskii DB. A neuron as a signal processing device. 47th Asilomar Conference on Signals, Systems, and Computers. 2013;362-366.
Guralnik G*, Guralnik Z*, Pehlevan C*. Dynamics of the chiral phase transition from AdS/CFT duality. J High Energy Phys. 2011;2011(12):111. (*alphabetical order)
Guralnik G*, Pehlevan C*. Complex Langevin equations and Schwinger-Dyson equations. Nucl Phys B. 2009;811(3):519-536. (*alphabetical order)
Guralnik G*, Pehlevan C*. Effective potential for complex Langevin equations. Nucl Phys B. 2009;822(3):349-366. (*alphabetical order)