Assistant Professor in Neuroscience and Data Science, NYU
I am interested in understanding the computational principles that organize neural circuits to give rise to behavior, in particular learning and memory. The approach we take in my lab lays at the interface between data science and neuroscience, as reflected a dual affiliation with the Centers for Neural and Data Science at NYU. We use a variety of tools from machine learning and statistics to develop theoretical models of neural circuit computation - from sensory learning, to decision making and memory retrieval. We also collaborate extensively with experimental labs in US and abroad to test our theoretical predictions, and develop new statistical tools for quantifying multiunit activity from behaving animals.
I received my doctorate from Goethe University in Frankfurt/Main, Germany where I studied the role of different forms of plasticity in unsupervised learning, this was followed by postdoctoral work at Cambridge University, UK, and ENS Paris, France and one independent research fellowship at IST Austria. I have joined NYU in June 2017 as an Assistant Professor in Neural Science and Data Science.
Ongoing collaborations within NYU: Dima Rinberg, Andre Fenton and Eero Simoncelli.