Yucheng Jin 金昱成

Yucheng Jin is a tenure-track Assistant Professor in Computer Science at Duke Kunshan University. He is also a member of Positive Intelligence Lab. Prior to his current role, he was a Research Assistant Professor at Hong Kong Baptist University, where he contributed significantly to the development of Human-computer Interaction in the Department of Computer Science. Moreover, he also spent four years working as a senior UX designer at Lenovo Research. He obtained his Ph.D. in Augment Group at the University of Leuven (KU Leuven). He has co-authored over 30 peer-reviewed papers, including publications in premier conferences and journals in Human-Computer Interaction, such as CHI, CSCW, and IJHCS. His innovative work has also led to ten patents. Furthermore, he regularly serves as a (senior) program committee member for esteemed ACM conferences like RecSys and IUI.

Education

Ph.D. in Computer Science, KU Leuven, 2019
M.Sc. in Informatics, TU Munich, 2013
B.Mgt. in Information Systems, Wuhan University, 2010

📣 I am currently seeking to fill positions for research assistants and postdoctoral fellows at DKU, as well as prospective Ph.D. candidates in partnership with Hong Kong Baptist University. Should these opportunities pique your interest, feel free to drop me an email with your CV and a one-page research statement (desired).

Research Interests

His research is situated in the long-standing quest to "Augmenting human intellect." He studies how humans interact / collaborate with AI systems in two major application domains: mental well-being and augmented creativity. His research interests include the following topics:

Human-AI Interaction and Collaboration
UX of Recommender Systems (e.g., trust, explanation, personalization, and user control)
Music and Augmented Creativity
Mental Health and Well-being

Selected Publications

^♱ indicates equal contributions, and ^* indicates the corresponding author.

Jin, Y., Chen, L., Zhao, X., & Cai, W. (2024). The Way You Assess Matters: User Interaction Design of Survey Chatbots for Mental Health. In International Journal of Human - Computer Studies (IJHCS). PDF DOI

Jin, Y.^♱, Cai, W.^♱, Chen, L., Zhang, Y., Doherty, G., & Jiang, T. (2024). Exploring Generative AI for Music-based Reminiscence with Older Adults. In CHI Conference on Human Factors in Computing Systems (CHI '24). PDF DOI

Sun, J., Yang, J., Zhu, G., Jin, Y.^*, & Gong, J.^* (2024). Understanding Human-AI Collaboration in Music Therapy Through Co-Design with Therapists. In CHI Conference on Human Factors in Computing Systems (CHI '24). PDF DOI

Jin, Y., Chen, L., Cai, W. & Zhao, X. (2023). CRS-Que: A User-Centric Evaluation Framework for Conversational Recommender Systems. In ACM Transactions on Recommender Systems. PDF DOI

Cai, W.^♱, Jin, Y.^♱, Zhao, X., & Chen, L. (2023). Listen to Music, Listen to Yourself": Design of a Conversational Agent for Supporting Self-Awareness in Music Listening. In CHI Conference on Human Factors in Computing Systems (CHI '23). PDF DOI

Jin, Y.^♱, Cai, W.^♱, Chen, L., Dai, Y., & Jiang, T. (2023, Oct.). Understanding Disclosure and Support in Social Music Communities for Youth Mental Health. In Proceedings of the ACM on Human-Computer Interaction (CSCW '23). PDF DOI

Zhao, X., Chen, L., Jin, Y.^*, & Zhang, X. (2023, March). Comparing Button-Based Chatbots with Webpages for Presenting Fact-Checking Results: A Case Study of Health Information. In Information Processing & Management (IP&M) (pp. 1-17). PDF DOI

Cai, W., Jin, Y., & Chen, L. (2022, May). Impacts of Personal Characteristics on User Trust in Conversational Recommender Systems. In CHI Conference on Human Factors in Computing Systems (CHI '22) (pp. 1-14). PDF DOI [Honorable Mention Award]

Cai, W., Jin, Y., & Chen, L. (2022). Task-Oriented User Evaluation on Critiquing-Based Recommendation Chatbots. IEEE Transactions on Human-Machine Systems. (pp. 1-13). PDF DOI

Alvarado Rodriguez, O. L., Htun, N. N., Jin, Y., & Verbert, K. (2022). A Systematic Review of Interaction Design Strategies for Group Recommendation Systems. In Proceedings of the ACM on Human-Computer Interaction (CSCW '22). (pp. 1-51) PDF DOI

Jin, Y., Chen, L., Cai, W., & Pu, P. (2021, November). Key Qualities of Conversational Recommender Systems: From Users’ Perspective. In Proceedings of the 9th International Conference on Human-Agent Interaction (HAI '21) (pp. 93-102). PDF DOI

Shen, Z., Wan, X., Jin, Y.^*, Gao, G., Wang, Q., & Liu, W. (2021, July). SeatPlus: A Smart Health Chair Supporting Active Sitting Posture Correction. In International Conference on Human-Computer Interaction (pp. 531-547). Springer, Cham. PDF DOI

Cai, W., Jin, Y., & Chen, L. (2021, April). Critiquing for music exploration in conversational recommender systems. In 26th International Conference on Intelligent User Interfaces (IUI '21) (pp. 480-490). PDF DOI

Jin, Y., Deng, Y., Gong, J., Wan, X., Gao, G., & Wang, Q. (2021, April). OYaYa: A Desktop Robot Enabling Multimodal Interaction with Emotions. In 26th International Conference on Intelligent User Interfaces-Companion (IUI companion '21) (pp. 55-57). PDF ODI

Jin, Y.^*, Tintarev, N., Htun, N. N., & Verbert, K. (2020). Effects of personal characteristics in control-oriented user interfaces for music recommender systems. User Modeling and User-Adapted Interaction (UMUAI), 30(2), 199-249. PDF DOI

Jin, Y., Cai, W., Chen, L., Htun, N. N., & Verbert, K. (2019, November). MusicBot: Evaluating critiquing-based music recommenders with conversational interaction. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM '19) (pp. 951-960). PDF DOI

Jin, Y., Htun, N. N., Tintarev, N., & Verbert, K. (2019, June). Contextplay: Evaluating user control for context-aware music recommendation. In Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP '19) (pp. 294-302). PDF DOI

Jin, Y., Tintarev, N., & Verbert, K. (2018, September). Effects of personal characteristics on music recommender systems with different levels of controllability. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys '18) (pp. 13-21). PDF DOI [Best Paper Nominee]

Millecamp, M., Htun, N. N., Jin, Y., & Verbert, K. (2018, July). Controlling spotify recommendations: effects of personal characteristics on music recommender user interfaces. In Proceedings of the 26th Conference on user modeling, adaptation and personalization (UMAP '18) (pp. 101-109). PDF DOI

Jin, Y., Tintarev, N., & Verbert, K. (2018, July). Effects of individual traits on diversity-aware music recommender user interfaces. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP '18) (pp. 291-299). PDF DOI

Jin, Y., Seipp, K., Duval, E., & Verbert, K. (2016, June). Go with the flow: effects of transparency and user control on targeted advertising using flow charts. In Proceedings of the international working conference on advanced visual interfaces (AVI '16) (pp. 68-75). PDF DOI

Jin, Y., Klerkx, J., & Verbert, K. (2016, June). CircleBuy: a visual search based second screen application of buying products in videos. In Proceedings of the 8th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS '16) (pp. 287-292). PDF DOI

Prehofer, C., Wagner, A., & Jin, Y. (2016, October). A model-based approach for multi-device user interactions. In Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems (MODELS '16) (pp. 13-23). PDF DOI

Bongartz, S., Jin, Y., Paternò, F., Rett, J., Santoro, C., & Spano, L. D. (2012, November). Adaptive user interfaces for smart environments with the support of model-based languages. In International Joint Conference on Ambient Intelligence (AmI '12) (pp. 33-48). Springer, Berlin, Heidelberg. PDF DOI

Grants

Technology Start-up Support Scheme for Universities Grant, 683,500 HKD, 2023/05-2024/05, Co-I
Wofoo Foundation research grant, 1,200,000 HKD, 2022/03-2024/02, Co-PI
HKBU Service learning mini-grant, 30,000 HKD, 2023, PI
HKBU Service learning mini-grant, 30,000 HKD, 2022, PI
HKBU Start-up Grant, 120,000 HKD, 2021, PI
HKBU Service learning mini-grant, 30,000 HKD, 2021, PI
Mainland-Hong Kong University Alliances Fund, 20,000 HKD, 2021, PI

Teaching

Winter semester 24/25

STATS 401 - Data Visualization and Acquisition
ECE 551 - Programming, Data Structures, and Algorithms in C++

Winter semester 23/24

COMP 4045 - Human-Computer Interaction
COMP 3075 - User Experience Design for Human Health and Well-being

Winter semester 22/23

COMP 4045 - Human-Computer Interaction, with Dr. Li Chen
COMP 7990 - Principles and Practices of Data Analytics, with Dr. Lu Zhang and Dr. Kevin Wang

Winter semester 21/22

COMP 4045 - Human-Computer Interaction, with integrating service learing into the course.
COMP 7990 - Principles and Practices of Data Analytics, with Dr. Lu Zhang and Dr. Kevin Wang

Mentoring

MPhil/PhD

Wanling Cai (HKBU, PhD), 10/19 - 09/22, with Dr. Li Chen
Xianglin Zhao (HKBU, MPhil), 10/21 - 06/23, with Dr. Li Chen

Theses

Danqing Liu (Ludwig Maximilian University of Munich (LMU), Bachelor thesis), 01/15 - 06/15
Raphael Haase (TUM, Master thesis), 12/14 - 04/15

Internship

Minzhu Zhao (HKBU) 12/21 - 06/22
Zhiwei Wang (Beijing Institute of Technology) 03/20 - 03/21, Lenovo Research
Tiffany Ong (Stanford University), 06/19 - 08/19, Lenovo Research
Yiyun Zhai (The University of Melbourne), 01/19 - 03/19, Lenovo Research
Yuchen Jiang (Stanford University), 06/18 - 08/18, Lenovo Research
Christina Gibbs (Stanford University), 06/17 - 08/17, Lenovo Research
Xiaozhong Liu (The University of Melbourne), 01/17 - 03/17, Lenovo Research

"Everything you do in your life should be serious fun." - Erik Duval