Tin Nguyen is a PhD Student at MIT. He is advised by Tamara Broderick. His research develops computational methods for inference and sensitivity detection in Bayesian inference.
Reduced runtime of approximate cross-validation for structured models including hidden Markov models and conditional random fields.
Research Intern
IBM Research
June 2022 –
August 2022
Cambridge, MA
Developed specification tests to reject the null hypothesis that neural networks trained on clean image data are well-specified for corrupted image data.