معرفی
Carl Yang is an Assistant Professor in the Department of Computer Science at Emory University since 2020. He holds courtesy appointments as Assistant Professor in the Center for Data Science (Nell Hodgson Woodruff School of Nursing) and the Department of Biostatistics and Bioinformatics (Rollins School of Public Health). His research focuses on data mining, knowledge graphs, and trustworthy AI with applications in healthcare, neuroscience, and biomedicine. He has received prestigious awards including the NSF CAREER Award (2025), NIH K25 Career Award (2023), and the Best Paper Award at ICDM 2020. Yang earned his Ph.D. from the University of Illinois, Urbana-Champaign under Prof. Jiawei Han, and his B.Eng. from Zhejiang University under Prof. Xiaofei He.
Yang’s work spans federated learning for graph data, brain network analysis, and healthcare informatics. He leads initiatives like the FedKDD workshop series and co-organized FedGraph conferences. His research is funded by NSF, NIH, Microsoft, and OpenAI. Notable contributions include FedSage (federated graph learning), BrainGB (fMRI analysis benchmark), and KG-LLM co-learning frameworks. He advises multiple Ph.D. students whose work has been recognized with awards such as the MCBIOS Young Scientist Excellence Award and SDM Doctoral Forum honors.
Yang’s current projects include NSF-funded research on diabetes heterogeneity and brain graph mining, NIH grants for health informatics, and collaborations with Stanford, Oxford, and NTU. He also serves as a visiting faculty at Google Research/DeepMind (part-time since 2024) and has held visiting roles at Oxford and Zhejiang University.
