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General Information
Full Name  Hyemin Gu 
Languages  English, Korean 
Education
 2020  Now
PhD student in Mathematics
University of Massachusetts Amherst, MA, US
 Research assistant
 Specializing in Mathematical modeling
 Advised by Markos Katsoulakis
 Current GSAC member  TWIGS coordinator
 2018  2020
MSc in Mathematics
Ewha Womans University, Seoul, Republic of Korea
 Thesis title "Convolutional Neural Network for 2D Flow Estimation Problem"
 Specializing in Numerical analysis
 Advised by JuneYub Lee
 2014  2018
BSc in Mathematics
Ewha Womans University, Seoul, Republic of Korea
 Major in Mathematics and Computational Science
 Minor in Statistics
Experience
 2022  Now
Graduate research assistant
University of Massachusetts  Amherst, Amherst, MA, US
 Developed a particle transportation algorithm and implemented the algorithm as a generative model.
 Improved the base model by autoencoders and and proved a sufficient condition for the convergence of the improved model.
 2021
Graduate teaching assistant
University of Massachusetts  Amherst, Amherst, MA, US
 TA for M545 (Linear Algebra for Applied Math), M235 (Linear Algebra), M532H (Nonlinear Dynamics & Chaos with Applications).
 Hosted discussion sessions, delivered minicourses for Python ODE solving tutorials, and graded weekly assignments.
 2020
Postmaster's researcher
Ewha Womans University Seoul Hospital, Seoul, Korea
 Constructed a pipeline for gene expression data analysis using R and created a documentation.
 Trained medical school graduate students to conduct statistical analysis using R.
 2018  2020
Graduate research assistant
Ewha Womans University, Seoul, Korea
 Trained CNN to estimate a physical state variable from 2D flow velocity fields.
Projects
 2022  Now
Lipschitz regularized generative particles algorithm
 Implementation of a particle transportation algorithm through gradient flows associated with Lipschitz regularized fdivergences.
 A generative model alternative to GANs in low training data regimes.
 Mathematical interpretation of applying spectral normalization on neural network discriminators as a particle transportation speed regularization.
Academic Interests

PDE based machine learning
 Optimal transport, gradient flows, transport equation.
 Reactiondiffusion equations.
 Generative models
Other Interests
 Hobbies: Raising plants at home, visiting art gallaries, learning investment, yoga