Wonyeol Lee

Registered user since Fri 3 Jul 2015

Name:Wonyeol Lee
Bio:

Wonyeol Lee is a final year PhD student in Computer Science at Stanford University advised by Alex Aiken. In 2017-2020, he was a researcher at KAIST mentored by Hongseok Yang, serving mandatory military service. He received a BS degree in Computer Science & Mathematics from POSTECH. He was a recipient of the Samsung Scholarship.

His research has been in the intersection of programming languages (PL) and machine learning (ML). He is most interested in identifying and addressing various theoretical/practical challenges in ML that arise from the discrepancy between the theory and practice of ML, particularly the following: in theory, mathematical functions of interest are assumed to be “well-behaved”, but in practice, they are represented by programs which can be easily “ill-behaved”.

Country:United States
Affiliation:Stanford University
Personal website:https://wonyeol.github.io
Research interests:Correctness (verification | program analysis), Numerical Programs (probabilistic | differentiable | floating-point), Probabilistic Inference (variational inference), Differentiation (non-differentiability | automatic differentiation | gradient estimation)

Contributions

POPL 2023 Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference
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