I am an (aspiring) Cognitive Computational Neuroscientist.

I currently work as a postdoctoral fellow at the Data Science Institute and the Zuckerman Brain Mind Behavior Institute at Columbia University, working with by Prof. Michael Shadlen and Prof. Rich Zemel. Prior to this, I was a PhD student for Computational Neuroscience at the Edmond and Lily Safra Center for Brain Sciences (ELSC) at the Hebrew University of Jerusalem. And prior to that, I completed a BSc in Abstract Mathematics (see my CV here).

Broadly, I am interested in how cognitive functions emerge from neural dynamics, and in the computational principles that link perception, decision-making, and subjective experience. My research utilizes computational modeling of behavior and large-scale neural recordings, including EEG and intracranial recordings from humans, and more recently, neural recordings from non-human primates.

My current research focuses on perceptual decision-making in complex settings, where decisions depend on multiple evidence streams rather than a single source (e.g. this study). I study how such decisions are formed using human behavioral data and electrophysiological recordings from non-human primates, and develop computational models that bridge normative, algorithmic, and neural levels of description. In parallel, I am developing new paradigms and models to study iconic memory, and even expanding to work on large language models (see here).

In my PhD work, I studied how visual experience is represented over time (see here), how temporal anticipation shapes our behavior (here), and how sensorimotor synchronization is shaped by computational constraints in special populations (here). Alongside this, I occasionally dabbled in philosophy (for example, here). I continue to work on all of these topics alongside my main line of work, through ongoing collaborations.

I really enjoy working across disciplines and am always happy to talk science, exchange ideas, or explore new collaborations. Please feel free to reach out.