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"AI+Complexity" Lecture Series II: "Artificial Intelligence and Mathematics"
        Date : 2020-11-13     Clicks:

On the afternoon of November 13, 2020, Professor Dingding Han from the Complex Network Science and Intelligent Systems Laboratory invited Professor Lin Wei to give an online lecture titled "Artificial Intelligence and Mathematics."

Professor Lin Wei's research focuses on biomathematics, complex systems theory, and their interdisciplinary applications. He has received the National Outstanding Young Scientist Fund, the Ministry of Education’s New Century Talent Program, the Shanghai "Qimingxing" (Tracking) Program, and the Shuguang Scholars Award. He has also won the ICCM Best Paper Award, the Ministry of Education’s Huo Yingdong Foundation Youth Teacher Award, and has been recognized as a Highly Cited Researcher by Elsevier Group in China. He currently serves as the Deputy Director of the Ministry of Education’s Frontier Brain Science Center, the Director of the Fudan Intelligent Complex Systems Laboratory, and the Vice Dean of the Brain-like Intelligence Research Institute at Fudan University.

The lecture, titled "Artificial Intelligence and Mathematics," focused on the following key points:

1) The creation of novel intelligent algorithms to explore and predict the fundamental characteristics of spatiotemporal data.

2) The design of advanced machine learning algorithms to create new theories for interpretable learning and training.

3) The implementation of human-like intelligence and collective intelligence to build multi-space intelligent agents, with a focus on collaborative evolution and regulatory strategies aimed at achieving specific tasks.

The lecture, with its professional insights and detailed explanations, generated a strong response among the attendees. The audience actively asked questions and engaged in lively discussions, leading to an extension of the meeting by half an hour. The lecture broadened the academic horizons of the participants, and they greatly benefited in terms of establishing substantial academic collaborations, developing scientific thinking, and learning from successful research experiences.


 

 


 

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