Prompt Engineering for Large Language Models

Описание: Dr. Cao is an associate professor (with tenure) in the Robert H. Smith School of Business at the University of Maryland. His work includes the development of a research program focused on how unstructured big data and emerging AI technologies can help guide stock investment decisions as well as executives’ corporate decisions. Because most corporate reporting and disclosure data are unstructured and high-dimensional, such as text and images, this research topic is crucial for disclosure research in the field of accounting and Fintech, corporate finance & investment research in the field of finance.

His research has been published in premier journals in finance, accounting, and computer science, including the Journal of Financial Economics, the Journal of Financial and Quantitative Analysis, the Journal of Accounting Research, The Accounting Review, Contemporary Accounting Research, and IEEE Computer. His collaborative studies with PhD students have been published in the Journal of Accounting Research and the Journal of Financial and Quantitative Analysis as well. He serves as an ad hoc associate editor at Management Science.

Dr. Cao’s research has been featured in the Financial Times, CNBC, Bloomberg, The Guardian, and Quartz. He has been invited to give keynote addresses at multiple conferences for both academic and industrial audiences. His work has been presented at major research universities, including Harvard University and the University of Michigan as well as at national regulatory and policy-focused advisory agencies including the SEC, the Federal Reserve Bank, the NBER, and PCAOB. His research has also drawn attention and workshop invitations from leading financial and industrial AI firms such as State Street Boston, Grant Thornton, Wolfe Research, Ant Financial, Baidu, DataYes, JD.com and Founder Securities.

Dr. Cao co-chaired the 2020 GSU-RFS conference on Fintech and Machine Learning. The conference was sponsored by the Review of Financial Studies (dual submission) and Georgia State University. The conference attracts an average of 150 high-quality submissions annually in the area of emerging technologies from preeminent scholars in both finance and accounting. (See more at https://sites.google.com/view/seancao....