Suh, Jina

Guidelines for Human-AI Interaction

Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P. N., Inkpen, K., et al. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 2,439

Grounding Interactive Machine Learning Tool Design in How Non-Experts Actually Build Models

Yang, Q., Suh, J., Chen, N.-C., & Ramos, G. (2018) · Proceedings of the 2018 Designing Interactive Systems Conference

Spreadsheets and End-User ComputingData Visualization and Analytics

Cited by 156

Using Machine Learning to Support Qualitative Coding in Social Science: Shifting the Focus to Ambiguity

Chen, N.-C., Drouhard, M., Kocielnik, R., Suh, J., & Aragon, C. R. (2018) · ACM Transactions on Interactive Intelligent Systems

Computational and Text Analysis MethodsQualitative Research Methods and Applications

Cited by 152

MeetingCoach: An Intelligent Dashboard for Supporting Effective & Inclusive Meetings

Samrose, S., McDuff, D., Sim, R., Suh, J., Rowan, K., Hernandez, J., Rintel, S., Moynihan, K., & Czerwinski, M. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 72

From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents

Chandra, M., Naik, S., Ford, D., Okoli, E., De Choudhury, M., Ershadi, M., Ramos, G., Hernandez, J., Bhattacharjee, A., Warreth, S., et al. (2025) · Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIDigital Mental Health Interventions

Cited by 44

Standardizing and Scaffolding Health Care AI-Chatbot Evaluation: Systematic Review

Hua, Y., Xia, W., Bates, D., Hartstein, G. L., Kim, H. T., Li, M., Nelson, B. W., Stromeyer IV, C., King, D., Suh, J., et al. (2025) · JMIR AI

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 30

The No Worries Trial: Efficacy of Online Dialectical Behaviour Therapy Skills Training for Chronic Pain (iDBT-Pain) Using a Single Case Experimental Design

Norman-Nott, N., Wilks, C. R., Hesam-Shariati, N., Schroeder, J., Suh, J., Czerwinski, M., Briggs, N. E., Quidé, Y., McAuley, J., & Gustin, S. M. (2022) · The Journal of Pain

Digital Mental Health InterventionsPersonality Disorders and Psychopathology

Cited by 17

ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems

Simard, P., Chickering, D., Lakshmiratan, A., Charles, D., Bottou, L., Suarez, C. G. J., Grangier, D., Amershi, S., Verwey, J., & Suh, J. (2014) · arXiv

Machine Learning and AlgorithmsRecommender Systems and Techniques

Cited by 15

Dear Diary: A Randomized Controlled Trial of Generative AI Coding Tools in the Workplace

Butler, J., Suh, J., Haniyur, S., & Hadley, C. (2025) · 2025 IEEE/ACM 47th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 12

Rethinking technology innovation for mental health: framework for multi-sectoral collaboration

Suh, J., Pendse, S. R., Lewis, R., Howe, E., Saha, K., Okoli, E., Amores, J., Ramos, G., Shen, J., Borghouts, J., et al. (2024) · Nature Mental Health

Digital Mental Health InterventionsImpact of Technology on Adolescents

Cited by 8

AI red-teaming is a sociotechnical problem: on values, labor, and harms

Gillespie, T., Shaw, R., Gray, M. L., & Suh, J. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 6