Cecilia Ying

Biography

Cecilia Ying is a Ph.D. candidate in Analytics at the Smith School of Business at Queen’s University. Her research focuses on the application of large language models and the potential societal impacts of such models, including the investigation of model explainability, model biases, and model corrections.

Educational Background

• BA in Joint Honours Mathematics and Applied Economics - University of Waterloo
• MMA and MSc in Analytics - Queen's University

Published Papers

• Purda, L., & Ying, C. (2022). Consumer Credit Assessments in the Age of Big Data. In Big Data in Finance: Opportunities and Challenges of Financial Digitalization (pp. 95-113). Cham: Springer International Publishing.
• Ying, C., & Thomas, S. (2022, May). Label errors in BANKING77. In Proceedings of the Third Workshop on Insights from Negative Results in NLP (pp. 139-143).
• Ying, C., & Thomas, S. (2024). Improving Fairness in Credit Lending Models using Subgroup Threshold Optimization. arXiv preprint arXiv:2403.10652.
• Jenkin, T., Kelley, S., Ovchinnikov, A., & Ying, C. (2022). Explanation Seeking and Recommendation Adherence in Human-to-Human versus Human-to-Artificial Intelligence Interactions. Available at SSRN 4330472.

Conferences & Presentations

• Ying, C., Thomas, S., 2024. CORS/INFORMS International Conference. Oral presentation: Impact of Covert Dialectic Prejudice in Large Language Model in Operations.
• Ying, C., Thomas, S., 2024. Production and Operations Management Society (POMS).  Oral presentation: Detecting and Mitigating Bias in LLMs
• Ying, C., 2024. Production and Operations Management Society (POMS).  Oral presentation: Bias Mitigation for Financial Inclusion in Machine Learning Credit Assessment Models
• Ying, C., Thomas, S., 2023. INFORMS Annual Meeting. Finalist in Poster Competition: Improving Fairness in Machine Learning via Subgroup Threshold Optimization.  Jenkin, T., Kelley, S., Ovchinnikov, A.,
• Ying, C., 2023. Behavioral Operations Conference (BOC) Oral presentation: Explanation Seeking and Recommendation Adherence in Human-to-Human versus Human-to-Artificial Intelligence Interactions.
• Ying, C., Abuhay, T., Thomas, S., 2023. Production and Operations Management Society (POMS). Oral presentation: Natural Language Processing for Understanding Customer Voices in OM.
• Ying, C., Thomas, S., 2022. INFORMS Annual Meeting. Oral presentation: Improving Conversation Analytics Through Hyperparameter Tuning with and Without Labels.
• Ying, C., Thomas, S., 2022. CORS/INFORMS International Conference. Oral presentation: Customer Insights Through Hierarchical Clustering: A New Methodology.
• Ying, C., Thomas, S., 2022. CORS/INFORMS International Conference. Oral presentation: Unsupervised Conversation Analytics.
• Ying, C., Thomas, S., 2022. Association for Computational Linguistics Conference, The Third Workshop on Insights from  Negative Results in NLP. Poster presentation: Label Errors in BANKING77.
• Ying, C., 2022. Vector Institute Research Symposium. Poster presentation: Unsupervised Conversation Analytics.
• Ying, C., Thomas, S., 2021. Conference on Neural Information Processing Systems (NeurIPS), Learning and Decision-Making with Strategic Feedback workshop (StratML). Poster presentation: Improving Fairness in Credit Lending Models using Subgroup Threshold Optimization.
• Ying, C., 2021. Vector Institute Research Symposium. Poster presentation: Improving Fairness in Credit Lending Models with Machine Learning.

Awards & Honours

• Joseph-Armand Bombardier Canada Graduate Scholarships - SSHRC
• New PhD Student Research Excellence Award - Smith School of Business, Queen's University
• Alan R. Dennis Doctoral Award - Smith School of Business, Queen's University
• Melville S. Hatch Memorial Fellowship - Smith School of Business, Queen's University
• R. Samuel McLaughlin Fellowship - Smith School of Business, Queen's University
• D.D. Monieson Graduate Business Scholarship - Smith School of Business, Queen's University