Education

 Ph.D. in Electrical and Computer Engineering (2017.03 - 2023.08)

• Seoul National University, Seoul, Korea

• Advisor: Sungroh Yoon

• Thesis: Learning from Limited Data: Deep Generative Models and Applications

 B.S. in Biomedical Engineering (2013.03 - 2016.08)

• Korea University, Seoul, Korea 

• Early graduation with great honor (GPA: 4.35/4.50, Major GPA: 4.43/4.50)

Publication (* equal contribution)

 Conference (peer reviewed)

8. Efficient Diffusion-Driven Corruption Editor for Test-Time Adaptation

Youngtak Oh, Jonghyun Lee, Jooyoung Choi, Dahuin Jung, Uiwon Hwang*, Sungroh Yoon*

ECCV 2024

[ arxiv ]

7. SF(DA)2: Source-free Domain Adaptation Through the Lens of Data Augmentation

Uiwon Hwang, Jonghyun Lee, Juhyeon Shin, Sungroh Yoon

ICLR 2024

[ paper  / code / slide / poster ]

6. Entropy is not Enough for Test-time Adaptation: From the Perspective of Disentangled Factors

Jonghyun Lee, Dahuin Jung, Saehyung Lee, Junsung Park, Juhyeon Shin, Uiwon Hwang*, Sungroh Yoon*

ICLR 2024  (Spotlight)

[ paper / code / page / slide / poster ]

5. Membership Privacy-Preserving GAN 

Heonseok Ha, Uiwon Hwang, Jaehee Jang, Ho Bae, Sungroh Yoon

BMVC 2022

[ paper / poster ]

4. Prediction of Mortality and Intervention in COVID-19 Patients Using Generative Adversarial Networks 

Uiwon Hwang, Euideuk Hwang, Minsoo Kang, Sungroh Yoon

ICML 2022 Workshop on Healthcare AI and COVID-19

[ paper / slide ]

3. Stein Latent Optimization for Generative Adversarial Networks

Uiwon Hwang, Heeseung Kim, Dahuin Jung, Hyemi Jang, Hyungyu Lee, Sungroh Yoon 

ICLR 2022

• Google Conference Scholarship 2022

• Excellent Paper Award from Hyundai Motor Company 2022

[ paper / code / slide / poster ]

2.  HexaGAN: Generative Adversarial Nets for Real World Classification

Uiwon Hwang, Dahuin Jung, Sungroh Yoon

ICML 2019

• Poster Session Award at Samsung AI Forum (SAIF) 2019

• Excellent Paper Award from Hyundai AIR Lab 2019

• Excellent Presentation Award from Hyundai AIR Lab 2019

[ paper / code / slide / poster ]

1. Reinforcement Learning based Recommender System using Biclustering Technique

Sungwoon Choi, Heonseok Ha, Uiwon Hwang, Chanju Kim, Jung-Woo Ha, Sungroh Yoon

WSDM 2018 Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization (IFUP)

[ paper / workshop ]

 Journal

8. On Mitigating Stability-plasticity Dilemma in CLIP-guided Image Morphing via Geodesic Distillation Loss

Yeongtak Oh, Saehyung Lee, Uiwon Hwang*, Sungroh Yoon*

International Journal of Computer Vision, 2024

[ paper / arxiv ]

7. Adversarial Defense on Harmony: Reverse Attack for Robust Models Against Adversarial Attacks

Yebon Kim, Jinhyo Jung, Hyunjun Kim, Hwisoo So, Yohan Ko, Aviral Shrivastava, Kyoungwoo Lee, Uiwon Hwang

IEEE Access, 2024

[ paper ]

6. Polyphonic Music Generation with Sequence Generative Adversarial Networks

Sang-gil Lee*, Uiwon Hwang*, Seonwoo Min, Sungroh Yoon

Journal of KIISE, 2024

[ paper / arxiv ]

5. Real-world Prediction of Preclinical Alzheimer’s Disease with a Deep Generative Model

Uiwon Hwang*, Sung-Woo Kim*, Dahuin Jung, SeungWook Kim, Hyejoo Lee, Sang Won Seo, Joon-Kyung Seong, Sungroh Yoon

Artificial Intelligence in Medicine, 2023

[ paper ]

4. Deep Learning-assisted Active Noise Control in a Time-varying Environment 

Seonghun Im, Siwon Kim, Sunghwa Woo, Inman Jang, Taewoo Han, Uiwon Hwang, Won-Suk Ohm, Myunghan Lee 

Journal of Mechanical Science and Technology (JMST), 2023

[ paper ]

3. Learn2Evade: Learning-based Generative Model for Evading PDF Malware Classifiers

Ho Bae, Younghan Lee, Yohan Kim, Uiwon Hwang, Sungroh Yoon, Yunheung Paek

IEEE Transactions on Artificial Intelligence (TAI), 2021

[ paper ]

2. PuVAE: A Variational Autoencoder to Purify Adversarial Examples 

Uiwon Hwang*, Jaewoo Park*, Hyemi Jang*, Sungroh Yoon, Nam Ik Cho 

IEEE Access, 2019 

[ paper ]

1. How Generative Adversarial Networks and Their Variants Work: An Overview

Yongjun Hong, Uiwon Hwang, Jaeyoon Yoo, Sungroh Yoon 

ACM Computing Surveys (CSUR), 2019

[ paper ]

 Preprint

5. Improving Diffusion-Based Generative Models via Approximated Optimal Transport

Daehyu Kim, Jooyoung Choi, Chaehun Shin, Uiwon Hwang*, Sungroh Yoon*

arXiv, 2024

[ arxiv / code ]

4. Gradient Alignment with Prototype Feature for Fully Test-time Adaptation

Juhyeon Shin, Jonghyun Lee, Saehyung Lee, Minjun Park, Dongjun Lee, Uiwon Hwang*, Sungroh Yoon*

arXiv, 2024

[ arxiv ]

3. On Mitigating Stability-plasticity Dilemma in CLIP-guided Image Morphing via Geodesic Distillation Loss

Yeongtak Oh, Saehyung Lee, Uiwon Hwang*, Sungroh Yoon*

arXiv, 2024

[ arxiv ]

2. Deep Trustworthy Knowledge Tracing

Heonseok Ha, Uiwon Hwang, Yongjun Hong, Sungroh Yoon

arXiv 2018

[ arxiv ]

1. Adversarial Training for Disease Prediction from Electronic Health Records with Missing Data

Uiwon Hwang, Sungwoon Choi, Han-Byoel Lee, Sungroh Yoon 

arXiv 2017

• Earlier version received Excellent Presentation Award at Korea Software Congress (KSC) 2017

[ arxiv / paper(Korean) ]

Invited Talk

Oral presentation, Wonju Severance Christian Hospital, 2024

Oral presentation, Korea Computer Congress, 2024

Oral presentation, SNU Genomic Medicine Institute Seminar, 2024

Oral presentation, KBESA 의공인의 밤, 2023

Poster presentation, SNU AIIS Autumn Retreat, 2022

Poster presentation, ICLR 2022 Social: ML in Korea, 2022

Oral presentation, SNU AIIS Spring Retreat, 2022

Oral presentation, Hyundai Motor Company, 2020

Oral presentation, Korea Software Conference (KSC), 2019

Poster presentation, Samsung AI Forum (SAIF), 2019

Poster presentation, SNU Center for Artificial Intelligence (SCAI) Summer Retreat, 2019

Oral presentation, Hyundai AIR Lab, 2019

Experience

 Professional Experience

 Assistant Professor (2023.09 - Present)

• Division of Digital Healthcare, Yonsei University - Mirae Campus, Wonju, Korea

• Biomedical Data Science Laboratory (BDSL), Yonsei University - Mirae Campus, Wonju, Korea

 Reviewer Experience

 Conference: ICML, NeurIPS, ICLR, ICIBM 

 Journal: TPAMI, TNNLS, CSUR, BMEL, YMJ, IEEE Access, Computational Intelligence and Neuroscience 

 Teaching Experience

 Assistant Professor at Div. of Digital Healthcare, Yonsei University - Mirae Campus

• AI Mathematics (Fall 2024)

• Medical Artificial Intelligence (Spring 2024)

• Healthcare Application Software (Spring 2024)

• Computational Thinking (Fall 2023, Spring 2024)

• Fundamentals of Algorithm (Fall 2023, Fall 2024)

 Teaching Assistant at Dept. of ECE, Seoul National University

• Deep Learning (Head TA, Fall 2021)

• Machine Learning Fundamentals and Applications in ECE (Head TA, Spring 2020)

• Theory and Practice of IoT, AI, and Big Data (Spring 2019)

• Topics in Computer and VLSI (AI: NUGU & Aibril with Watson) (Fall 2017) 

Honors

 Award

Excellent Paper Award, Hyundai Motors Company, 2022

Poster Session Award, Samsung AI Forum, 2019 

Excellent Presentation Award, Hyundai AIR Lab, 2019 

Excellent Paper Award, Hyundai AIR Lab, 2019 

Excellent Presentation Award, Korea Software Congress, 2017 

Finalist, Spark Design Awards: Spring Concept, 2016 

President’s List, Fall 2015 

Semester Highest Honors, Fall 2014 & Spring 2015 

Semester High Honors, Fall 2013, 2014, 2015 & Spring 2014, 2015, 2016 

 Scholarship

Google Conference Scholarship, 2022

OK Leadership Scholarship, OK Bae & Jung Scholarship Foundation, 2020 

The Education and Research Foundation College of Engineering SNU Scholarship, 2019

Academic Excellence Scholarship, Korea University, 2014-2016