Annie Qu
Chancellor’s Professor
Email: aqu2@uci.edu
Phone: 949-824-9070
Mailing address:
Donald Bren Hall 2212
Department of Statistics, UCI
Irvine, CA 92697
Qu’s research focuses on solving fundamental issues regarding unstructured large-scale data, developing cutting-edge statistical methods and theory in machine learning and algorithms on text sentiment analysis, automatic tagging and summarization, recommender systems, tensor imaging data and network data analyses for complex heterogeneous data, and achieving the extraction of essential information from large volume high-dimensional data. Her research has impacts in many different fields such as biomedical studies, genomic research, public health research, and social and political sciences.
Before she joins the UC Irvine, Dr. Qu is Data Science Founder Professor of Statistics, and the Director of the Illinois Statistics Office at the University of Illinois at Urbana-Champaign. She was awarded as Brad and Karen Smith Professorial Scholar by the College of LAS at UIUC, a recipient of the NSF Career award in 2004-2009, and is a Fellow of the Institute of Mathematical Statistics, a Fellow of the American Statistical Association, and a fellow of American Association for the Advancement of Science. She is current Co-Editor of Journal of the American Statistical Association, Theory and Methods.
Google Scholar
Recent Research Interests:
- Data integration for heterogeneous data, Active learning, Deep learning from statistics perspective, NLP and LLM, high-dimensional mediation analysis, Causal inference (de-confounder), Reinforcement learning, Dynamic treatment, Differential Privacy, Mobile Health (Sleep and Stress), DNA Methylation for PTSD, Precision medicine
Other Research Interests:
- Machine Learning, Tensor Data, Medical Imaging, Recommender Systems, Network Data, Longitudinal/Correlated Data Analysis, Missing Data, High-dimensional Data, Model Selection, Nonparametric Models
Grants:
- Principal investigator: NCI R01 grant 1R01CA297869-01, “SCH: Individualized learning and prediction for heterogeneous multimodal data from wearable devices.” 2024-2028.
- Co-Principal Investigator (PI: Hengrui Cai), NSF Grant CDS&E-MSS 2401271, “Collaborative Research: Causal Discovery and Individualized Policy Optimization for Human Text Data” 2024-2027.
- Principal investigator: NSF Grant DMS 2210640, “Collaborative Research: Integrative Heterogeneous Learning for Intensive Complex Longitudinal Data” 2022-2025.
- Principal investigator: NSF Grant DMS 1952406, “FRG: Collaborative Research: Generative Learning on Unstructured Data with Applications to Natural Language Processing and Hyperlink Prediction” 2020-2023.
- Principal investigator: NSF Grant DMS 1821198, “Collaborative Research: New Statistical Learning for Complex Heterogeneous Data.” 2018-2021.
- Principal Investigator: NSF, DMS 1613190, “Group-Specific Individualized Modeling and Recommender Systems for Large-Scale Complex Data.” 2016-2019.
- Principal Investigator: NSF, DMS1415308, “Collaborative Research: New Statistical Learning and Scalable Computing for Large Unstructured Data.” 2014-2017.
- Principal Investigator: NSF, DMS1308227, “Personalized classification, moment selection, and time-varying networks for large-scale longitudinal data.” 2013-2016.
- Principal Investigator: NSF, DMS 0906660, “Model selection and efficient learning for high dimensional clustered data.” 2009-2012.
- Principal Investigator: NSF, DMS 0348764, “CAREER: Semiparametric and nonparametric models for correlated data.” 2004-2009.
- Co-Principal Investigator (PI: John Fowler, Botany and Plant Pathology, Oregon State): EPA, “Indicators of fitness in the maize pollen transcriptome: A screen for correlation between gene expression and pollen competitve ability.” 2006-2008.
- Principal Investigator: NSF, DMS 0103513 “Semiparametric models for correlated data: The quadratic inference function approach.”2001-2004.
- Co-investigator (P.I.: W.C. Hayes): NIH, “Fall biomechanics and hip fracture risk.” 2002-2003.