FODI LAB
FODI LAB
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From Observed Data to Identifiability
From Observed Data to Identifiability
What can data tell us,
and under what conditions?
What can data tell us,
and under what conditions?
We begin with prediction, open it, guarantee it, verify it, and only then ask about identification.
WHAT WE WORK ON
WHAT WE WORK ON
Across these areas, we study how what is observed constrains what can be predicted, inferred, and ultimately identified.
Prediction with Imperfectly Observed Information
Prediction with Imperfectly Observed Information
How can we build and validate predictions when available data are incomplete, noisy, or indirect representations of the target?
Causal Inference
with Incomplete Information
Causal Inference
with Incomplete Information
What causal questions remain answerable when treatment, outcome, confounding, or temporal information is imperfectly observed?
Identification from Partial
& Distributed Information
Identification from Partial
& Distributed Information
What can be identified when information needed for inference is only partially observed or distributed across data sources and populations?
DATA WE WORK WITH
DATA WE WORK WITH
JOIN FODI
JOIN FODI
Bring us a question that does not have an obvious answer.
We welcome students and collaborators who want to develop statistical ideas around challenging questions in human data.
For prospective students, we are more interested in how you challenge an open problem than in a polished statement about yourself.
FODI LAB
College of Natural Sciences, Chungbuk National University
S1-5, Room 106 · Chungdae-ro 1, Seowon-gu, Cheongju, Chungbuk 28644, Korea
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