Faculty member

Research Interests

The key goal of the Computational Machinery of Cognition (CMC) lab is to understand the computations that support goal-driven behavior, and also the multi-scale machinery (neurons, …, large-scale networks) that implements these computations.

Available PhD Projects

The overarching goal of the research in our lab is to understand the neural and cognitive architecture of goal-driven behavior. Our behavior is supported by a wide range of computations that are realized in the wet machinery of the brain. The two pillars of lab research are to characterize these computations and understand how neural circuits realize them. These are typically the focus of separate communities: one focusing on normative models of information processing and behavior, and the other, on the organization and dynamics of the brain. We want to integrate both of these perspectives. Such an integrative approach, i.e., concurrent investigation of both neural and computational-cognitive aspects of behavior, is crucial for two reasons. First, it provides great potential for understanding psychiatric disorders, which frequently involve deficits in both domains. For instance, Interventional treatments target different physiological
scales (pharmacological treatments target the cellular level, and brain stimulation targets the circuit level). On the other hand, behavioral therapies (such as cognitive behavior therapy - CBT) target the level of complex behaviors and computation. Second, my novel integrative approach will also improve artificial intelligence (AI) systems. Recent developments showed tremendous progress in mimicking brain computational capacities (e.g., language models, computer vision, etc), however on the implementational level, current AI systems are still inferior to biological brains by a large margin. For instance, AI models use massive computational resources to realize the computations that that does with a tiny fraction of it (e.g., in terms of energy).