讲座摘要

The human brain can process information efficiently and reliably. However, the neuronal principles underlying these computations remain unclear. It is essential to consolidate our expanding knowledge of ion channel dynamics, neuronal properties, and circuit structure into computational principles for neural circuits. In the first part, the speaker will introduce his work exploring the biological mechanisms of robust neural computations. In the second part, he will share his work on the potential roles of biological algorithms in artificial intelligence.

报告人介绍

臧蕴亮，天津大学英才教授，2013年于浙江大学生物医学工程专业取得博士学位。之后在日本和美国基于类小脑结构围绕神经系统鲁棒性和高效性从事多年研究。代表性工作以一作发表在PNAS (2023 & 2021)、Current Biology (2023)、eLife (2020)、Cell Reports (2018)等专业期刊,受邀为Current Opinion in Neurobiology (2023)撰写约稿综述，2023年放弃美国教职offer，入职天津大学。主持科技部重点研发计划“生物与信息融合”重点专项项目以及国家自然科学基金面上项目，实验室研究方向包括基于小脑和果蝇嗅觉环路启发的人工智能、小脑功能复用理论模型、树突计算、计算神经科学。