Talking to Your Data: Building AI Co-Scientists to Accelerate Scientific Discovery
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Given the fast development of technology and automation systems, researchers are generating tons of data from scientific experiments to facilitate discoveries, especially in the areas of biology and medicine. However, large-scale biomedical data make it challenging for biologists or medical researchers to more effectively utilize these data with robust and powerful methods for novel and reproducible discoveries. Therefore, I pioneered the research for building Knowledge-Enhanced AI+Biomedicine Co-Scientist System to overcome these challenges. First, I will show the importance of having a fair evaluation framework to rank the contributions of foundation models (FMs) and AI Scientists for biological data analysis and demonstrate the importance of prior knowledge. Second, I will show the strength of leveraging knowledge to gain insights in analyzing multi-modal data for clinical and biomedical applications by building AI Bioinformaticians and biologists. Finally, I will discuss our progress of building an AI Bioengineer for accelerating scientific discoveries which facilitate generation tasks in multiple areas to enclose this robust and extensive system.
Given the fast development of technology and automation systems, researchers are generating tons of data from scientific experiments to facilitate discoveries, especially in the areas of biology and medicine. However, large-scale biomedical data make it challenging for biologists or medical researchers to more effectively utilize these data with robust and powerful methods for novel and reproducible discoveries. Therefore, I pioneered the research for building Knowledge-Enhanced AI+Biomedicine Co-Scientist System to overcome these challenges. First, I will show the importance of having a fair evaluation framework to rank the contributions of foundation models (FMs) and AI Scientists for biological data analysis and demonstrate the importance of prior knowledge. Second, I will show the strength of leveraging knowledge to gain insights in analyzing multi-modal data for clinical and biomedical applications by building AI Bioinformaticians and biologists. Finally, I will discuss our progress of building an AI Bioengineer for accelerating scientific discoveries which facilitate generation tasks in multiple areas to enclose this robust and extensive system.+