ESP Biography

In this cutting-edge course on AI for Scientific Discovery, students will explore the transformative potential of artificial intelligence in accelerating scientific breakthroughs. The curriculum will delve into key topics such as active learning, a paradigm that enables AI systems to intelligently query and learn from strategically selected data points. Additionally, students will gain expertise in Bayesian optimization, a powerful technique for efficiently searching complex parameter spaces to identify optimal experimental conditions. The course will also cover the principles of design of experiments (DoE), empowering students to create efficient and informative experimental plans. Lastly, we will investigate the emerging role of large language models (LLMs) in scientific research, from automating literature reviews to generating hypotheses and aiding in data interpretation. Through hands-on projects and case studies, students will develop practical skills in applying these AI techniques to real-world scientific challenges, positioning themselves at the forefront of this transformative field.