Li Dong Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Federal Grant PI

Researcher

University of Arkansas at Fayetteville

faculty

12 h-index 97 pubs 553 cited

Research Areas

Atmospheric Chemistry and Aerosols Air Quality and Health Impacts Advanced Neural Network Applications Hydrology and Watershed Management Studies Health Literacy and Information Accessibility Machine Learning Techniques Environmental Analysis Causal Inference and Fairness in Machine Learning

Links

ORCID Lab Website

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OverviewAI-generated summary

Li Dong's research focuses on atmospheric science, environmental analysis, and the application of machine learning techniques to complex data sets. Dong has investigated the characteristics of air pollution in China, including the estimation of PM2.5 concentrations using hybrid machine learning models. Their work also examines the vertical distribution and transport paths of atmospheric aerosols, utilizing long-term satellite data. Further environmental research includes the analysis of watershed evaporation indicated by isotopic differences under varying land uses.

In addition to environmental studies, Dong has explored the intersection of technology and human behavior, such as analyzing university students' information service needs in the post-COVID-19 era. Dong also contributes to the field of causal inference and fair machine learning, having served as PI and Co-PI on NSF grants totaling $634,828. These grants support research into counterfactually fair machine learning through causal modeling and fair regression under sample selection bias. Dong has authored 97 publications, with an h-index of 12 and 553 total citations, and maintains an active lab website.