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Alumni
- Mincheol Kang, Undergrad Intern (DGIST), Spring 2024 - Summer 2024
- Jiheon Kang, Undergrad Intern (DGIST), Spring 2024 - Summer 2024
- Yibin Moon, Undergrad Intern (DGIST), Spring 2024
- Nayoung Kim, Undergrad Intern (DGIST), Winter 2023 - Spring 2024
- Jaeyoung Choi, Undergrad Intern (DGIST), Winter 2023 - Spring 2024
- Suyeon Shin, Undergrad Intern (DGIST), Summer 2023 - Spring 2024
- Sungmin Ju, Undergrad Intern (DGIST), Summer 2023 - Spring 2024
- Jeongeon Park, Researcher, Fall 2023 - Spring 2024
- Sunoo Kim, Undergrad Intern (DGIST), Winter 2024 - Spring 2024
- Youngjin Park, Undergrad Intern (DGIST), Winter 2024
- Dain Kim, Undergrad Intern (DGIST), Winter 2023 - Fall 2023
- Sihwan Seok, Undergrad Intern (DGIST), Winter 2023 - Fall 2023
- Subeen Jo, Undergad Intern (DGIST), Winter 2023 - Fall 2023
- Minseong Kim, Undergrad Intern (DGIST), Spring 2023 - Summer 2023
- Huidam Woo, Undergrad Intern (DGIST), Spring 2023
- Chan Lee, Undergrad Intern (DGIST), Spring 2023
- Ahyeon Shin, Undergrad Intern (DGIST), Winter 2023
- Sangeun Seo, Undergrad Intern (UNIST), Summer 2022, Winter 2023
- Chanyu Moon, Undergrad Intern (DGIST), Winter 2023
- Gunuk Nam, Undergrad Intern (Handong Global University), Winter 2023
- Nayoung Kim, Undergrad Intern (DGIST), Winter 2022 - Winter 2023
- Hojin Jin, Undergrad Intern (DGIST), Winter 2022 - Fall 2022
- Hyeonho Kwon, Undergrad Intern (DGIST), Winter 2022 - Fall 2022
- Giwon Lee, Undergrad Intern (DGIST), Winter 2022 - Fall 2022
- Giwa Osaruiyobo Henrietta, Graduate Intern (DGIST), Summer 2022
Publications
Conference and Journal Papers
- Sera Lee*, Dae R. Jeong*, Junyoung Choi, Jaeheon Kwak, Seoyun Son, Jean Y. Song, and Insik Shin. "Serenus: Alleviating Low-Battery Anxiety Through Real-time Accurate and User-Friendly Energy Consumption Prediction of Mobile Applications." In Proceedings of The ACM Symposium on User Interface Software and Technology (UIST 2024). (* Equal contribution)
- Dokyun Lee, Sangeun Seo, Chanwoo Park, Sunjun Kim, Buru Chang, and Jean Y. Song. "Exploring Intervention Techniques to Alleviate Negative Emotions during Video Content Moderation Tasks as a Worker-centered Task Design." In Proceedings of the ACM Conference on Designing Interactive Systems (DIS 2024).
- Yeonsun Yang, Ahyeon Shin, Nayoung Kim, Huidam Woo, John Joon Young Chung, and Jean Y. Song. "Find the Bot!: Gamifying Facial Emotion Recognition for Both Human Training and Machine Learning Data Collection." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2024).
- Sunjae Lee*, Minwoo Jeong*, Daye Song, Junyoung Choi, Seoyun Son, Jean Y. Song†, Insik Shin†. "FLUID-IoT : Flexible and Granular Access Control in Shared IoT Environments via-UI-Level Control Distribution." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2024). (* Equal contribution, †Co-corresponding authors)
- Dongyoon Han*, Junsuk Choe*, Seonghyeok Chun, John Chung, Minsuk Chang, Sangdoo Yun, Jean Y. Song, Seong Joon Oh. "Neglected Free Lunch - Learning Image Classifiers Using Annotation Byproducts." In Proceedings of the International Conference on Computer Vision (ICCV 2023). (* Equal contribution)
- Jean Y. Song*, Sangwook Lee*, Jisoo Lee, Mina Kim, and Juho Kim. "ModSandbox: Facilitating Online Community Moderation Through Error Prediction and Improvement of Automated Rules." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2023). (* Equal contribution)
- Seoyun Son, Junyoung Choi, Sunjae Lee, Jean Y. Song, and Insik Shin. "It is Okay to be Distracted: How Real-time Transcriptions Facilitate Online Meeting with Distraction." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2023).
- Sunjae Lee, Hoyoung Kim, Sijung Kim, Sangwook Lee, Hyosu Kim, Jean Y. Song, Steven Y. Ko, Sangeun Oh, and Insik Shin. "A-Mash: Providing Single-app Illusion for Multi-app Use through User-centric UI Mashup." In Proceedings of the International Conference On Mobile Computing And Networking (MobiCom 2022).
- Yoonjoo Lee, John Joon Young Chung, Taesoo Kim, Jean Y. Song, and Juho Kim. "Promptiverse: Scalable Generation of Scaffolding Prompts through Human-AI Knowledge Graph Annotation." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2022).
- Sunjae Lee, Hayeon Lee, Hoyoung Kim, Sangmin Lee, Jeong Woon Choi, Yuseung Lee, Seono Lee, Ahyeon Kim, Jean Y. Song, Sangeun Oh, Steven Y. Ko, and Insik Shin. "FLUID-XP: Flexible User Interface Distribution forCross-Platform Experience." In Proceedings of the International Conference On Mobile Computing And Networking (MobiCom 2021).
- Zhefan Ye, Jean Y. Song, Zhiqiang Sui, Stephen Hart, Jorge Vilchis, Arbor, Walter S. Lasecki, and Odest C. Jenkins. "Human-in-the-loop Pose Estimation via Shared Autonomy." In Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI 2021). Best Paper Honorable Mention
- Stephan J. Lemmer, Jean Y. Song, and Jason J. Corso. "Crowdsourcing More Effective Initializations for Single-target Trackers Through Automatic Re-querying." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2021).
- Yoonjoo Lee, John Joon Young Chung, Jean Y. Song, Minsuk Chang, and Juho Kim. "Personalizing Ambience and Illusionary Presence: How People Use "Study with Me" Videos to Create Effective Studying Environments." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2021).
- Jean Y. Song, John Joon Young Chung, David F. Fouhey, and Walter S. Lasecki. "C-Reference: Improving 2D to 3D Object Pose Estimation Accuracy via Crowdsourced Joint Object Estimation." In Proceedings of the ACM International Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2020).
- Divya Ramesh, Anthony Z. Liu, Andres J. Echeverria, Jean Y. Song, Nicholas R. Waytowich, and Walter S. Lasecki. "Yesterday’s Reward is Today’s Punishment: Contrast Effects in Human Feedback to Reinforcement Learning Agents." In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020). Pragnesh Jay Modi Best Student Paper
- Yan Chen, Maulishree Pandey, Jean Y. Song, Walter S. Lasecki, and Steve Oney. "Improving Crowd-Supported GUI Testing with Structural Guidance." In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2020).
- John Joon Young Chung, Jean Y. Song, Sindhu Kutty, Sungsoo (Ray) Hong, Juho Kim, and Walter S. Lasecki. "Efficient Elicitation Approaches to Estimate Collective Crowd Answers." In Proceedings of the ACM International Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2019). Austin, TX. Best Paper Honorable Mention
- Jean Y. Song, Raymond Fok, Juho Kim, and Walter S. Lasecki. "FourEyes: Leveraging Tool Diversity as a Means to Improve Aggregate Accuracy in Crowdsourcing." In ACM Transactions on Interactive Intelligent Systems, Volume 19, Issue 1, Article No. 3 (TiiS 2019).
- Jean Y. Song, Stephan J. Lemmer, Michael Xieyang Liu, Shiyan Yan, Juho Kim, Jason J. Corso, and Walter S. Lasecki. "Popup: Reconstructing 3D Video Using Particle Filtering to Aggregate Crowd Responses." In Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI 2019). Los Angeles, CA.
- Jean Y. Song, Raymond Fok, Alan Lundgard, Fan Yang, Juho Kim, and Walter S. Lasecki. "Two Tools are Better Than One: Tool Diversity as a Means of Improving Aggregate Crowd Performance." In Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI 2018). Tokyo, Japan. Best Student Paper Honorable Mention
Posters, Demos, and Workshop Papers
- Jeongeon Park, Bryan Min, Jean Y. Song, Xiaojuan Ma, and Juho Kim. "How do multiple LLM-powered conversational agents assist sensemaking and decision-making in an unfamiliar domain?" In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2024).
- Hyungyu Shin, Nabila Sindi, Yoonjoo Lee, Jaeryoung Ka, Jean Y. Song, and Juho Kim. "XDesign: Integrating Interface Design into Explainable AI Education." In Proceedings of the ACM Technical Symposium on Computer Science Education (SIGCSE TS 2022).
- Andrew M. Vernier, Jean Y. Song, Edward Sun, Allison Kench, and Walter S. Lasecki. "Towards Universal Evaluation of Image Annotation Interfaces." In Proceedings of the ACM Symposium on User Interface Software and Technology (UIST 2019). New Orleans, LA.
- Jean Y. Song, Raymond Fok, Fan Yang, Kyle Wang, Alan Lundgard, and Walter S. Lasecki. "Tool Diversity as a Means of Improving Aggregate Crowd Performance on Image Segmentation Tasks." In HCOMP Workshop on Human Computation for Image and Video Analysis (HCOMP GroupSight 2017). Quebec City, Quebec. 2017.
- Sai R. Gouravajhala, Jean Y. Song, Jinyeong Yim, Raymond Fok, Yanda Huang, Fan Yang, Kyle Wang, Yilei An, and Walter S. Lasecki. "Towards Hybrid Intelligence for Robotics." In Collective Intelligence Conference (CI 2017). New York, NY.
Projects
Our research projects include but are not limited to the following list. We are open to discuss new project ideas in the topic of Human-Computer Interaction, Human-AI Interaction, Crowdsourcing, Human Computation, or any other related domains. Please feel free to contact us if you have exciting ideas.
Facilitating Online Community Moderation using AI Techniques
Communities on social platforms have a group of users who volunteer to moderate their communities, called online moderators. They respond to the behavior of community members that violate rules and work to improve overall interaction experiences between community members. This project aims to build human-AI interaction tools to support moderators to more easily and transparently moderate their online communities.
Improving Facial Emotion Recognition for both Human and AI
This project focuses on enhancing Facial Emotion Recognition(FER) for individuals who struggle with recognizing facial expressions, as well as for current models with low FER performance. To address these challenges, we developed a gamified application called "Find the Bot!" that re-labels FER datasets and trains individuals with difficulties in recognizing facial emotions simultaneously. Our vision is to improve FER abilities for individuals with weak FER, leading to enhanced relationship quality, social acceptance, and increased social productivity, while also contributing to the development of reliable multi-labeling for facial expression datasts.
Reducing Negative Emotions for Crowd Workers Exposed to Disturbing Content
Often times crowd workers who do content moderation or data annotations are exposed to harmful content in their daily routines. This project explores UI intervention techniques that can prevent crowd workers from getting too much negative emotional impacts when conducting these tasks. Through this study, we aim to find ways to maintain the quality and cost of the crowdsourced work while protecting the emotions and mental health of crowd workers.
Continual Learning from a Data Science Perspective
Implementing a model created in a controlled environment into the real world requires solving the problem of Catastrophic Forgetting. To solve that problem, we seek to draw inspiration from the Human Complementary Learning Systems (CLS) from a data science perspective. Through this research, we hope that the model created in a controlled environment can continuously learn in the real world, and through this, the controlled model can be applied to daily life.
Augmenting QnA Dataset for Technical Documents with Crowdsourcing
This project proposes a new sentence structuring method and crowdsourcing interface to augment rich Korean dataset in text documents specialized in technology and science. Our novel authoring tool enables to efficiently generating various question and answer pairs for technical documentation by breaking down sentences into elements that can be recombined to form new sentences.
Contact
We welcome collaborations!
If you have any questions or would like to hear more about our research, please feel free to shoot us an email:
jeansong@yonsei.ac.kr