Professional AssociationsProfessional Associations: ACM SIGKDD | ACM SIGSAC | American Mathematical Society (AMS) | American Medical Informatics Association | Association for the Advancement of Artificial Intelligence (AAAI) | IEEE Computer Society | IEEE Systems, Man, and Cybernetics Society | INFORMS | Institute of Industrial Engineers (IIE) | Society for Industrial and Applied Mathematics | Society of Women Engineers
Cao (Danica) Xiao is a Research Staff Member in the AI for Healthcare Team of IBM Research AI, located in Cambridge, Massachusetts. Before joining IBM, she got her Ph.D. degree from University of Washington, Seattle in 2016. Her thesis focused on machine learning and data mining with medical and healthcare applications. During her PhD training, she also worked as research intern at Group Health Research Institute in 2013, data scientist intern at LinkedIn from 2014 to 2015, and research intern at IBM Research in 2016, respectively.
Her research interests focus on developing novel machine learning and data mining models to solve real world healthcare challenges. Particularly, she is interested in deep computational phenotyping, risk prediction and patient subtyping for neurodegenerative diseases (e.g. Parkinson's disease, Alzheimer's disease), adverse drug reaction signal detection from heterogeneous real world evidence, tensor decomposition for integrating multiple medical data sources, graph based learning, causal inference from observational data, as well as translational informatics research. The results of her research have been published and presented in leading conferences in artificial intelligence (AAAI) and data mining (KDD, SDM). She led a team to develop a mobile health (mHealth) app that won the national 3rd prize in the sixth IISE-CIS Mobile App Competition. She was also in the team that won the PPMI Data Challenge in 2016 (https://www.michaeljfox.org/foundation/grant-detail.php?grant_id=1518).