UW Data Science Seminar: Adam Visokay

UW Data Science Seminar: Adam Visokay

When

11/12/2024    
4:30 pm – 5:20 pm

Where

Please join us for a UW Data Science Seminar on Tuesday, November 12th from 4:30 to 5:20 p.m. PT. The seminar will feature Adam Visokay, PhD Student in the Department of Sociology at the University of Washington.

The seminar will be held in the Physics/Astronomy Auditorium (PAA), Room A118 – campus map.

“Inference on Predicted Data: Examples from Verbal Autopsies and the BMI 

Abstract: As AI and ML tools become more accessible, and scientists face new obstacles to data collection (e.g. rising costs, declining survey response rates), researchers increasingly use relatively cheap predictions from pre-trained algorithms in place of more expensive “ground truth” data. Standard tools for inference can misrepresent the association between independent variables and the outcome of interest when the true, unobserved outcome is replaced by a predicted value. In this talk, I present an overview detailing how to perform valid inference when working with predicted data. I will share two examples of this method in practice – one in the context of global public health working with Verbal Autopsy data, and the other in the context of medicine, working with BMI data.

Bio: Adam is a PhD student at the University of Washington, advised by Professor Tyler McCormick. They are also an affiliate student at the Max Planck Institute for Demographic Research. Adam’s research explores how to leverage artificial intelligence and machine learning to study social phenomena, typically motivated by questions in public health, economics, and sociology. Adam is particularly interested in improving the interpretability and transparency of language models and how to perform valid statistical inference using predictions.

The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.

 

The 2024-2025 seminars will be held in person, and are free and open to the public.