On May 27th, Fudan University commemorated its 117th anniversary with a special session of the 56th Scientific Report Symposium, a testament to its long-standing tradition of academic excellence. Jin Li, the esteemed President of Fudan University and an Academician of the Chinese Academy of Sciences, opened the session with an insightful report. He underscored the importance of discipline construction in modern university development and emphasized Fudan's commitment to fostering an integrated, innovative academic community.

Despite the challenges posed by the recent epidemic, Fudan University's spirit of inquiry and dedication to scientific research has remained unwavering. From May 17th to 27th, the university held six academic symposiums covering a broad spectrum of disciplines, including social sciences, technology, medicine, and interdisciplinary studies. These symposiums highlighted the university's academic achievements and commemorated its 117th anniversary.

On the afternoon of May 27th, the Research Institute of Intelligent Complex Systems showcased the innovative work of its young researchers, Shi Jifan, Sun Siqi, and Zhong Haixin, who delivered reports on groundbreaking issues in their respective fields of research.

史际帆：动力学因果框架及嵌入熵

Shi Jifan presented a compelling report on 'Dynamic Causal Framework and Embedding Entropy,' exploring the philosophical and mathematical aspects of causality. His work proposed a unified dynamic causal framework and introduced an innovative index and algorithm based on embedding entropy, enhancing accuracy and robustness in causal inference across various systems.

孙思琦：语言模型在生物大分子结构预测中的应用

Sun Siqi's report, titled 'Application of Language Model to Structure Prediction of Biological Macromolecules,' delved into the use of language models for predicting macromolecular structures. The report highlighted significant advancements in operational efficiency and precision, including the development of a rapid algorithm, fastMSA, and the introduction of a pre-training model, RNA-FM, for RNA structure and function analysis.

钟海鑫: 基于bottom-up视觉通路信息衰减策略启发的图像轮廓检测算法研究

Zhong Haixin presented his research on 'Image Contour Detection Algorithm Inspired by Bottom-Up Visual Path Information Attenuation Strategy.' His model, influenced by the human visual information processing pathway, employed innovative HSV color coding and simulated photoreceptor processes. The results demonstrated superior contour detection capabilities at a lower computational cost, compared to advanced bio-inspired models.

These presentations from the Research Institute of Intelligent Complex Systems at Fudan University not only reflect the cutting-edge research being conducted but also underscore the university's role as a leader in advancing scientific knowledge and innovation.

On May 27th, Fudan University commemorated its 117th anniversary with a special session of the 56th Scientific Report Symposium, a testament to its long-standing tradition of academic excellence. Jin Li, the esteemed President of Fudan University and an Academician of the Chinese Academy of Sciences, opened the session with an insightful report. He underscored the importance of discipline construction in modern university development and emphasized Fudan's commitment to fostering an integrated, innovative academic community.

Despite the challenges posed by the recent epidemic, Fudan University's spirit of inquiry and dedication to scientific research has remained unwavering. From May 17th to 27th, the university held six academic symposiums covering a broad spectrum of disciplines, including social sciences, technology, medicine, and interdisciplinary studies. These symposiums highlighted the university's academic achievements and commemorated its 117th anniversary.

On the afternoon of May 27th, the Research Institute of Intelligent Complex Systems showcased the innovative work of its young researchers, Shi Jifan, Sun Siqi, and Zhong Haixin, who delivered reports on groundbreaking issues in their respective fields of research.

史际帆：动力学因果框架及嵌入熵

Shi Jifan presented a compelling report on 'Dynamic Causal Framework and Embedding Entropy,' exploring the philosophical and mathematical aspects of causality. His work proposed a unified dynamic causal framework and introduced an innovative index and algorithm based on embedding entropy, enhancing accuracy and robustness in causal inference across various systems.

孙思琦：语言模型在生物大分子结构预测中的应用

Sun Siqi's report, titled 'Application of Language Model to Structure Prediction of Biological Macromolecules,' delved into the use of language models for predicting macromolecular structures. The report highlighted significant advancements in operational efficiency and precision, including the development of a rapid algorithm, fastMSA, and the introduction of a pre-training model, RNA-FM, for RNA structure and function analysis.

钟海鑫: 基于bottom-up视觉通路信息衰减策略启发的图像轮廓检测算法研究

Zhong Haixin presented his research on 'Image Contour Detection Algorithm Inspired by Bottom-Up Visual Path Information Attenuation Strategy.' His model, influenced by the human visual information processing pathway, employed innovative HSV color coding and simulated photoreceptor processes. The results demonstrated superior contour detection capabilities at a lower computational cost, compared to advanced bio-inspired models.

These presentations from the Research Institute of Intelligent Complex Systems at Fudan University not only reflect the cutting-edge research being conducted but also underscore the university's role as a leader in advancing scientific knowledge and innovation.