中文
北京科技大学智能科学与技术学院、人工智能研究院教授、博导，智能科学与技术系副主任、智能仿生无人系统教育部重点实验室副主任。长期从事智能无人系统、仿生微型扑翼飞行器、智能控制等研究，在Automatica、IEEE汇刊等国际著名期刊上发表SCI论文50余篇，其中ESI高被引论文6篇、ESI热点论文1篇，Google学术引用2000余次，出版学术著作2部，授权发明专利5项。主持重点研发青年科学家项目、国家自然科学基金面上项目、联合基金子课题、启元实验室基金、JKW主题项目、“一带一路”创新人才交流外国专家项目、国家重点研发计划专项项目子课题等项目。曾获吴文俊人工智能自然科学奖一等奖（第四完成人）、中国仿真学会科学技术奖创新技术一等奖（第八完成人）、人工智能学会优秀博士论文提名奖、ICIUS 2019 最佳会议论文提名奖等。目前担任中国自动化学会青年工作委员会副秘书长、北京智能学会理事、IEEE SMC 学会自主仿生飞行机器人委员会委员；担任IEEE/CAA; Journal of Automatica Sinica和工程科学学报青年编委。
English language documentation files English language documentation files - 副本.docx
Artificial Intelligence, abbreviated as AI, is a crucial driving force behind the new wave of scientific and technological revolution as well as industrial transformation. It constitutes a novel technical science dedicated to researching and developing theories, methods, technologies, and application systems aimed at simulating, extending, and expanding human intelligence.
As a significant component of intelligence studies, AI seeks to understand the nature of intelligence and create intelligent machines capable of responding in ways similar to human intelligence.
It is an exceptionally broad scientific field encompassing robotics, speech recognition, image recognition, natural language processing, expert systems, machine learning, computer vision, and more.
However, the governance challenges posed by large-scale AI models cannot be overlooked. As Elon Musk pointed out, beneath the mask of machine learning, the essence of AI remains rooted in statistics. To foster a healthy innovation ecosystem, it is essential to conduct forward-looking research and establish sound laws, regulations, institutional frameworks, and ethical guidelines to ensure the responsible development of AI.
Looking ahead, while emphasizing risk prevention, it is equally important to simultaneously establish mechanisms for error tolerance and correction, striving to achieve a dynamic balance between regulation and development.
