Dongjae Kim is an Assistant Professor in the Department of AI at Dankook University. His research interests are rooted in understanding human intelligence-specifically, how it works and what makes it unique-using concepts from reinforcement learning. Dongjae studied biology at Korea University as an undergraduate and completed his Ph.D. in brain cognitive engineering at KAIST, later working as a postdoctoral researcher at the Center for Neural Science at New York University, a leading institute in cognitive science. With this interdisciplinary background, he now studies artificial intelligence, resulting in a broad research portfolio.

His primary goal is to bridge cognitive understanding of human intelligence with computational models, and vice versa. For example, his 2024 Nature Neuroscience paper, “Reward Prediction Errors Implement an Efficient Code for Reward,” exemplifies this approach by linking two of the most successful theories in cognitive science: efficient coding and reinforcement learning (particularly distributional reinforcement learning).

At ICOLSEI 2025, Dongjae will deliver a talk titled “Mathematical Foundations of Learning in the Brain: Reinforcement Learning to Minimize Errors and to Maximize Information.” In this talk, he will explore how reinforcement learning frameworks and efficient neural coding principles provide unified explanations for human cognition, bridging cellular mechanisms to behavioral adaptation.