About

I’m currently a researcher in Flatiron Institute, co-supervised by Alex Williams and Cristina Savin. I work on metrics for dynamic representations. I have an MSc degree in Computational Neuroscience from the University of Tübingen, where I was funded by the German Academic Excellence Service (DAAD). I have a bachelor’s degree in Electronics & Communication Engineering from Istanbul Technical University.

My research focus is learning, computation through dynamics, and latent variable models. In general, I approach neuroscience questions using modern machine learning tools and dynamical systems theory.

I completed my master’s thesis in Savin Lab at NYU CNS (Center for Neural Science), where I combined control and learning theory to develop a novel algorithm for recurrent neural networks (in preparation). During my second lab rotation, I worked in Macke Lab, on a project about inferring dynamical systems underlying data. Before that, I did my first lab rotation in Dayan Lab, working on three-factor Hebbian learning. During my first year of the master’s program, I worked on learning rules in Levina Lab. I completed my bachelor’s thesis with Neslihan Serap Şengör in Şengör Lab, working on spiking neural networks implementing a perceptual-decision-making task. I am utterly grateful for her guidance throughout my whole bachelor’s and for making me realize the beauty in math and neuroscience.