Los Angeles Hillside Road Demand Analysis
Data-Driven Graph-Based Analysis of Commonly Used Roads in a Large-Scale Transportation Network
Posts by Collection
projects
Fingerhut (Online Retailer) Strategic Consulting
Statistics M148 - Experience of Data Science Capstone Project (UCLA)
Research Paper Classification Optimization Using NLP and Instance-Based Learning
Mathematics 156 - Machine Learning (UCLA)
Developing efficient classification for Reddit posts/comments/communities with Graph Neural Networks (GNNs)
DataRes Research (UCLA), Winter 2023
publications
Synthetic Survey Data Generation and Evaluation
Published in Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’25), 2025
An end-to-end evaluation of five synthetic data generation methods for survey microdata using utility, fidelity, and privacy metrics.
Recommended citation: Yanru Jiang, Siyu Liang, and Junwon Choi. 2025. Synthetic Survey Data Generation and Evaluation. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1 (KDD ’25). Association for Computing Machinery, New York, NY, USA, 2292–2302. https://doi.org/10.1145/3690624.3709421
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talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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