Kate Hu is an Assistant Professor from the Department of Statistics at the Ohio State Universitya. Her research interests include
- Causal inference with time series, spatial, and continuous exposure data
- Leveraging auxiliary information to address unmeasured or mismeasured confounding
- Enhancing inference precision in semiparametric models through auxiliary information
- Designing cost-effective studies with auxiliary information
- Reducing statistical bias in data collection using auxiliary information
- Developing a Z-estimation system to expediate asymptotic analysis for estimators with a square root N convergence
- Precision agriculture, with emphasis on experimental and sampling designs
- Epidemiology, particularly cardivascular diseases, case-cohort, case-control studies, and environmental epidemiology
Dr. Kate Hu was a National Research Service Award postdoctoral fellow at Harvard University. Before returning to academia Dr. Kate Hu was the Head of Data Science at Aclima Inc., where she drives the company’s data science R&D to deliver hyper-local air pollution and greenhouse gas emission maps, by dispatching a fleet of vehicles equipped with environmental sensors. This environmental “big data” fills a gap in what policymakers and activists rely on to bring environmental justice to underserved communities. During her time as the Head of Data Science, the company was honored #1 in the 10 most innovative companies in data science by Fast Company in 2021.
Prior to joining Aclima Inc, Dr. Kate Hu was a senior quantitative researcher at Climate LLC, innovating precision agriculture solutions to help farmers maximize the economic return and adapt to climate change. She first led the research program in sampling and experimental designs to collect field data scientifically for model calibration and evaluation. Then she led the interdisciplinary research efforts to develop precision nitrogen treatment algorithms that respond to local environment and real-time weather change, by combining mechanistic models, statistical models, and new sensing technologies.
Kate graduated with First Class Honours from the University of Hong Kong, received an M.S. from Harvard University, and obtained a Ph.D. in Biostatistics from the University of Washington, Seattle. Her PhD dissertation is A Z-estimation System for Semiparametric Models with Two-phase Sampling Designs under the guidance of Norman Breslow, Gary Chan, and Jon Wellner.