Sangwoo Mo

swmo [at] umich [dot] edu

Google Scholar / Github / CV / Twitter


I am a postdoctoral fellow at the University of Michigan, working with Prof. Stella X. Yu. Before joining UM, I earned my Ph.D. at KAIST under the supervision of Prof. Jinwoo Shin. During my Ph.D., I had the chance to intern or collaborate with various industry and academic labs, including Google AI, Meta AI, NVIDIA AI, Naver AI, and Kakao Brain, where I had the privilege of working with many outstanding mentors. I also received several student fellowships, including the ones from Samsung, Qualcomm, and Korean AI Association.


My research goal is to build the foundation for AI. To this end, I worked on perception (representation learning), creation (generative models), and action (robotics & decision making), within the domains of vision, language, and multimodality. Specifically, my previous research includes:

▪︎ Representation learning

- Vision: NeurIPS'20, NeurIPS'21, CVPRW'22, ICLR'23, ICLR'24

- Language/Multimodal: AAAI'21, NeurIPS'23, CVPR'24

- Analysis (by lottery ticket): ICLR'20, ICLR'21 

▪︎ Generative models

- Vision: ICLR'19, NeurIPS'19, CVPRW'20, ICLR'22, TMLR'23

- Language/Multimodal: ICLR'24, ICLR'24, arXiv'24

- Structured: ICMLW'21, NeurIPS'23

▪︎ Robotics & decision making

- Robotic sensing: IROS'19, T-RO'21

News

▪︎ 2024/03: I served as a reviewer at ICML, ECCV, and TPAMI.

▪︎ 2024/02: Our paper on language for vision is accepted at CVPR'24.

▪︎ 2024/02: I gave a talk at Hanyang University about foundation models for vision, language, and multimodality (slide).

▪︎ 2024/01: Our papers on visual representation (spotlight), LLM long context, and LLM reasoning are accepted at ICLR'24.

▪︎ 2023/11: I served as a reviewer at ICLR, CVPR, and TMLR.

▪︎ 2023/09: Our papers on vision-language model and structured prediction are accepted at NeurIPS'23.

▪︎ 2023/09: I started a postdoctoral fellowship at the University of Michigan.

▪︎ 2023/08: I gave a talk at Korea University about recent trends in visual representation learning (slide).

▪︎ 2023/06: I successfully defended my PhD thesis! 🧑‍🎓

Publications

C: conference, W: workshop, J: journal, P: preprint / * equal contribution


[C16] Discovering and Mitigating Visual Biases through Keyword Explanation

Younghyun Kim*, Sangwoo Mo*, Minkyu Kim, Kyungmin Lee, Jaeho Lee, Jinwoo Shin

CVPR 2024 | paper / slide / poster / code


[C15] Learning Hierarchical Image Segmentation For Recognition and By Recognition

Tsung-Wei Ke*, Sangwoo Mo*, Stella X. Yu

ICLR 2024 (spotlight) | paper / slide / poster / code


[C14] SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs

Jaehyung Kim, Jaehyun Nam, Sangwoo Mo, Jongjin Park, Sang-Woo Lee, Minjoon Seo, Jung-Woo Ha, Jinwoo Shin

ICLR 2024 | paper / slide / poster / code


[C13] Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs

Woomin Song*, Seunghyuk Oh*, Sangwoo Mo, Jaehyung Kim, Sukmin Yun, Jung-Woo Ha, Jinwoo Shin

ICLR 2024 | paper / slide / poster / code


[C12] S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions

Sangwoo Mo, Minkyu Kim, Kyungmin Lee, Jinwoo Shin

NeurIPS 2023 | paper / slide / poster / code


[C11] Diffusion Probabilistic Models for Structured Node Classification

Hyosoon Jang, Seonghyun Park, Sangwoo Mo, Sungsoo Ahn

NeurIPS 2023 | paper / code


[J2] Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling

Junhyun Nam, Sangwoo Mo, Jaeho Lee, Jinwoo Shin

TMLR 2023 | paper / slide / poster / code


[C10] RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data

Sangwoo Mo, Jong-Chyi Su, Chih-Yao Ma, Mahmoud Assran, Ishan Misra, Licheng Yu, Sean Bell

ICLR 2023 | paper / slide / poster / code


[W3] OAMixer: Object-aware Mixing Layer for Vision Transformers

Hyunwoo Kang*, Sangwoo Mo*, Jinwoo Shin

CVPRW 2022 (Transformers for Vision) | paper / poster / code

Best paper award, Korean AI association fall conference, 2022


[C9] Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks

Sihyun Yu*, Jihoon Tack*, Sangwoo Mo*, Hyunsu Kim, Junho Kim, Jung-Woo Ha, Jinwoo Shin

ICLR 2022 | paper / demo / slide / poster / code

Media coverages (1)


[C8] Object-aware Contrastive Learning for Debiased Scene Representation

Sangwoo Mo*, Hyunwoo Kang*, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin

NeurIPS 2021 | paper / slide / poster / code

Qualcomm innovation fellowship korea, 2021


[W2] Abstract Reasoning via Logic-guided Generation

Sihyun Yu, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin

ICMLW 2021 (Self-SL for Reasoning and Perception) | paper / slide / poster / code


[C7] Layer-adaptive Sparsity for the Magnitude-based Pruning

Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin

ICLR 2021 | paper / slide / poster / code


[C6] MASKER: Masked Keyword Regularization for Reliable Text Classification

Seung-Jun Moon*, Sangwoo Mo*, Kimin Lee, Jaeho Lee, Jinwoo Shin

AAAI 2021 | paper / slide / poster / code


[J1] Deep Neural Network Based Electrical Impedance Tomographic Sensing Methodology for Large-Area Robotic Tactile Sensing

Hyunkyu Park, Kyungseo Park, Sangwoo Mo, Jung Kim

T-RO 2021 | paper


[C5] CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances

Jihoon Tack*, Sangwoo Mo*, Jongheon Jeong, Jinwoo Shin

NeurIPS 2020 | paper / slide / poster / code

Qualcomm innovation fellowship korea, 2020


[W1] Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs

Sangwoo Mo, Minsu Cho, Jinwoo Shin

CVPRW 2020 (AI for Content Creation) | paper / slide / code

Media coverages (1, 2, 3)


[C4] Lookahead: A Far-sighted Alternative of Magnitude-based Pruning

Sejun Park*, Jaeho Lee*, Sangwoo Mo, Jinwoo Shin

ICLR 2020 | paper / slide / code


[C3] Mining GOLD Samples for Conditional GANs

Sangwoo Mo, Chiheon Kim, Sungwoong Kim, Minsu Cho, Jinwoo Shin

NeurIPS 2019 | paper / slide / poster / code


[C2] Deep Neural Network Approach in Electrical Impedance Tomography-Based Real-Time Soft Tactile Sensor

Hyunkyu Park, Hyosang Lee, Kyungseo Park, Sangwoo Mo, Jung Kim

IROS 2019 | paper / slide


[C1] InstaGAN: Instance-aware Image-to-Image Translation

Sangwoo Mo, Minsu Cho, Jinwoo Shin

ICLR 2019 | paper / slide / poster / code

▸ Bronze prize, Samsung humantech paper awards, 2019 / Media coverages (1, 2, 3, 4)

Work Experience

Research Experience

▪︎ U Michigan, Research Fellow (host: Prof. Stella X. Yu) / Ann Arbor, MI / Sep 2023 - current

▪︎ NVIDIA AI, Research Intern (host: Dr. Weili Nie) / Santa Clara, CA (remote) / Oct 2022 - Jan 2023

▪︎ Meta AI, Research Intern (host: Dr. Jong-Chyi Su) / Menlo Park, CA / Jun 2022 - Sep 2022

▪︎ Naver AI, Collaborator (host: Dr. Jung-Woo Ha) / Jeongja, South Korea / Jun 2021 - Sep 2021

▪︎ Google AI, Collaborator (host: Dr. Kihyuk Sohn) / Sunnyvale, CA (remote) / Nov 2020 - May 2021

▪︎ Kakao Brain, Research Intern (host: Dr. Sungwoong Kim) / Pangyo, South Korea / Feb 2019 - May 2019

▪︎ POSTECH, Collaborator (host: Prof. Minsu Cho) / Pohang, South Korea (remote) / Jul 2018 - Feb 2020


Business Experience

▪︎ Boston Consulting Group, Research Assistant / Seoul, South Korea / Sep 2014 - Oct 2014

▪︎ Fast Track Asia (venture capital), Business Intern / Seoul, South Korea / Jun 2014 - Aug 2014

Education

▪︎ KAIST, M.S./Ph.D. in Electrical Engineering (advisor: Prof. Jinwoo Shin) / Daejeon, South Korea / Aug 2023

▪︎ POSTECH, B.S. in Mathematics & Industrial Engineering (minor) - summa cum laude / Pohang, South Korea / Feb 2016

▪︎ Hansung Science High School / Seoul, South Korea / Feb 2011

Mentoring

▪︎ Zilin Wang (PhD @ UM). Co-advised a project, working in progress.

▪︎ Woomin Song (PhD @ KAIST). Co-advised a project, paper accepted at ICLR'24.

▪︎ Younghyun Kim (MS @ KAIST). Co-advised a project, paper accepted at CVPR'24.

▪︎ Hyosoon Jang (PhD @ POSTECH). Co-advised a project, paper accepted at NeurIPS'23.

▪︎ Hyunwoo Kang (MS @ KAIST). Co-advised projects, papers accepted at NeurIPS'21 and CVPRW'22.

▪︎ Seung-Jun Moon (MS @ KAIST). Co-advised a project, paper accepted at AAAI'21.

Honors & Awards

Research Honors & Awards

▪︎ Bronze Prize, Samsung Humantech Paper Awards, 2019 ($5,000)

▪︎ Qualcomm Innovation Fellowship Korea, 2020 ($4,000)

▪︎ Qualcomm Innovation Fellowship Korea, 2021 ($4,000)

▪︎ Best Paper Award, Korean AI Association Fall Conference, 2022 ($2,000)

▪︎ Reviewer Award: ICML'20, NeurIPS'20, ICLR'21, ICML'21


Business Honors & Awards

▪︎ 1st Prize, Nomura Consulting Case Competition, 2013

▪︎ 1st Prize, Maeil Business Newspaper Case Competition, 2012

▪︎ 1st Prize, GE-McKinsey Leadership Workshop Idea Competition, 2014

▪︎ 23th President of Postech Management Strategy Club (MSSA)

▪︎ Senior member of Young Engineers Honor Society (YEHS)

▪︎ Visiting student at UC Berkeley and Peking university

Selected Talks

▪︎ Hanyang Uni., AI Dept., "Foundation Models for Vision, Language, and Multimodality," Feb 2024

▪︎ U Michigan, CV Group, "Learning Visual Representations from Uncurated Data," Sep 2023

▪︎ Korea Uni., Stats Dept., "Learning Visual Representations from Uncurated Data," Aug 2023

▪︎ KIAS, AI Group, "Robust Semi-supervised Learning from Uncurated Data,'' Mar 2023

▪︎ UCSD, Wang Lab, "Learning Visual Representations from Uncurated Data," Dec 2022

▪︎ Stanford, Wu Lab, "Learning Visual Representations from Uncurated Data," Nov 2022

▪︎ POSTECH, EffL Lab, "Robust Semi-supervised Learning from Uncurated Data," Oct 2022

▪︎ UNIST, AI Dept., "Object-aware Contrastive Learning for Debiased Scene Representation," Nov 2021

Services

▪︎ Conference Reviewer: NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI

▪︎ Journal Reviewer: TPAMI, TMLR, TNNLS, IJCV, TCSVT, ML

▪︎ Workshop Reviewer: NeurIPS-DGM, CVPR-AICC, ICML-TEACH, NeurIPS-DistShift

Projects

▪︎ ADD, "Interpretability Method for Object Detection in Remote Sensing," 2020-2022

▪︎ IITP, "Continual and Transfer Learning for Generative Models," 2019-2020

▪︎ ETRI, "Anomaly Detection for Time-Series Data from Smart Grids," 2017-2018

▪︎ WiderPlanet, "Online Ads Recommendation Using Deep Contextual Bandits," 2016