Academics / Courses / DescriptionsCOMP_SCI 396, 496: AI for Science
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Prerequisites
CS seniors and CS grad students onlyDescription
Over the last decade+, due to advances in supercomputing power and in Deep Learning algorithms that learn from massive datasets, Artificial Intelligence (AI) has enabled new frontiers and paradigms that have the potential to accelerate scientific discoveries at a pace never imagined.
The main objectives of this class are to discuss, explore and understand how modern AI including Deep Learning, Transformers, Large Language Models (and Foundational Models), and data mining techniques can exploit massive amounts of data to accelerate scientific discoveries. The class will briefly introduce supercomputing/HPC, scientific simulation approaches, and discuss how AI can exploit and work alongside to solve important scientific problems. The class will discuss how AI has the potential to accelerate discoveries in various scientific applications including but not limited to materials discovery, climate and environmental science, life-science and health-care applications, astrophysics and cosmology, and AI applications at the edge including instruments deployed in various scenarios. The class will discuss Fair Data, Ethics and Trust as applied to science applications of AI. Students will have opportunities to take deeper dives into foundational technologies or one or more science application domains via projects. Class will include guest lectures by leaders and experts in AI and various science domains. The class will involve reading papers, presentations, and team project.
- This course fulfills the Technical Elective area.
- This course cross-list with CE 395-2/CE 495-2.
COURSE INSTRUCTOR: Prof. Alok Nidhi Choudhary