Apologies for Cross Posting The Chen Institute Symposium for AI Accelerated Science is an annual event dedicated to exploring groundbreaking advancements in AI that are reshaping scientific discovery across disciplines. Each year, leading researchers, industry innovators, and influential thought leaders gather to discuss how cutting-edge AI methodologies—such as foundational models, long-term memory mechanisms, synthetic data generation, and research process automation—are revolutionizing the scientific landscape.
We invite submissions that explore how core advancements in artificial intelligence are accelerating progress in science. This call focuses on transformative AI innovations that enable new modes of inquiry, hypothesis generation, and experimentation across scientific disciplines. We especially welcome work in the following areas: Foundational Models: Research on large-scale, pre-trained models that serve as general-purpose engines for scientific reasoning, prediction, and simulation Long-Term Memory Mechanisms: Innovations in memory architectures that enable persistent knowledge representation, context retention, and lifelong learning in AI systems Synthetic Data Generation: Novel techniques for creating high-fidelity synthetic datasets that augment or replace empirical data in research pipelines Research Process Automation: AI tools and frameworks that automate experimental design, data analysis, literature synthesis, or other components of the scientific workflow We encourage submissions from researchers working at the intersection of AI and the physical or life sciences, including but not limited to biology, chemistry, physics, medicine, and engineering. Selected papers will be presented at the conference, where authors will join a dynamic community shaping the future of AI-accelerated science. See more at https://aias2025.org/ CFP details and submissions: https://aias2025.org/call-for-papers/ Organizing Committee: - Jennifer Chayes, Deanof the College of Computing, Data Science, and Society at UC Berkeley - Yan Li, Executive Director of Scientific Programs, Chen InstitutePietro Perona - Allan E. Puckett Professor of Electrical Engineering and Computation and Neural Systems, Caltech - Mengdi Wang, Associate Professor of Electrical and Computer Engineering and the Center for Statistics and Machine Learning, Princeton - Parisa Kordjamshidi, Associate Professor of Computer Science and Engineering, Michigan State University - Hamid Karimian, Research Assistant Professor of Computer Science and Engineering, Michigan State University See more at https://aias2025.org/ CFP details and submissions: https://aias2025.org/call-for-papers/ ᐧ
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