AP Humanities Scoring
AP 人文自动评分Automated scoring for AP history, literature & foreign-language writing — accurate, transparent, and equitable.
Publications, conference talks, and academic honors. Highlight markers in the author lists denote me.
Complete publication record across peer-reviewed venues and arXiv preprints.
Automated scoring for AP history, literature & foreign-language writing — accurate, transparent, and equitable.
Tokenization & dataset-size effects on identifying AI-generated text — Frontiers in AI 2024 & IMPS 2024.
Comparing scoring rationales between large language models and human raters — arXiv 2025.
Cost-efficient generative-AI summarization for scalable automated essay scoring — arXiv 2026.
Deep-learning pipelines for genomic sequence modeling and molecular phenotype prediction — Westlake.
Multimodal machine learning on human behavior and communication in online discourse — Princeton.
Features for Detecting Essays Produced by Generative AI — with Hong Jiao, C. Yadav, and L. Wan. Research on identifying features useful for detecting essays generated by emerging generative-AI systems. International Meeting of the Psychometric Society, July 24–28, 2023 · Conference Abstracts p. 217.
Exploring Classic Machine Learning Models and Large Language Models in Detecting Chat-GPT Generated Essays in Writing Assessments — with Jiayu Yao. Comparative evaluation of classical ML and LLM approaches, including how human rewriting, AI rewriting, and grammar-based revisions affect detection. 89th International Meeting of the Psychometric Society, July 15–19, 2024.
Evaluation of the Performance for Automated Essay Scoring in Long Context — with K. Wang, Hong Jiao, and Dan Song. Approaches to scoring long-form essays and the limitations of conventional language-model architectures on extended text. National Council on Measurement in Education Annual Meeting, April 23–26, 2025.
Scoring Rationale Comparison between Large Language Models and Human Raters: Insights from Automated Scoring Systems — with Hong Jiao (University of Maryland) and Dan Song (University of Iowa). Examined how LLM-generated scoring rationales compare with human raters’, with implications for interpretability and reliability of AI-assisted automated scoring. International Meeting of the Psychometric Society, 2025.
Exploration of Summarization by Generative Language Models to Enhance Automated Scoring of Long Essays — with Hong Jiao (University of Maryland) and Xinyi Wang (University of Maryland / Beijing Normal University). A generative-AI approach to long-form essay scoring using LLM summarization to address input-length limits of transformer models. October 29, 2025.
International data-science competition focused on machine-learning methods for medical imaging and lumbar spine degeneration classification.
Achieved Gold-level ranking in the United States of America Computing Olympiad.
Earned first place at the state level and advanced to international-level competition.
Received the Senior Division Award for work in psychology.
Awarded in recognition of exceptional leadership and administrative performance, including service in senior cadet leadership and unit administrative roles.
Reproducible code and datasets for the essay-scoring and AI-detection projects will be linked here as they are released.
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