Huiqi Zou | Johns Hopkins University

About Me

I am Huiqi Zou. I hold a Master’s degree in Computer Science from Johns Hopkins University, where I completed a thesis under the supervision of Prof. Ziang Xiao.
Previously, I earned a Bachelor’s degree in Computer Science (Artificial Intelligence Stream) from City University of Hong Kong, where I completed my final year project under the supervision of Prof. Linqi Song.

Research Interests

My research interest lies in human-computer interaction (HCI) and natural language processing (NLP), especially in the field of interactive evaluation. I am currently fascinated by the following research questions:

What is the role of interaction in system building and evaluation?
How to conduct evaluation in a task-driven scenarios?

My ultimate goal is to build interactive systems for more engaging human-computer communication and transition from static evaluation methods to more flexible, task-driven assessments that capture the diverse scenarios in which models are deployed.

News

[Dec. 2024] I graduated from Johns Hopkins University with an M.S.E. in Computer Science.

Publications

arxiv

Personality Structured Interview for Large Language Model Simulation in Personality Research

P. Wang, H. Zou, H. Chen, T. Sun, Z. Xiao, and F. Oswald

arxiv, 2025.

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IEEE TSE

On the Influence of Data Resampling for Deep Learning-Based Log Anomaly Detection: Insights and Recommendations

X. Ma, H. Zou, P. He, J. Keung, Y. Li, X. Yu, and F. Sarro

IEEE Transactions on Software Engineering, 2024.

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arxiv

Practitioners’ Expectations on Log Anomaly Detection

X. Ma, Y. Li, J. Keung, X. Yu, H. Zou, Z. Yang, F. Sarro, and E. T. Barr

arxiv, 2024.

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arxiv

Can LLM "Self-report"?: Evaluating the Validity of Self-report Scales in Measuring Personality Design in LLM-based Chatbots

H. Zou, P. Wang, Z. Yan, T. Sun, and Z. Xiao

arxiv, 2024.

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OSF Preprints

Not Yet: Large Language Models Cannot Replace Human Respondents for Psychometric Research

P. Wang, H. Zou, Z. Yan, F. Guo, T. Sun, Z. Xiao, and B. Zhang

OSF Preprints, 2024.

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IEEE Trans. Reliab

AttSum: A Deep Attention-based Summarization Model for Bug Report Title Generation

X. Ma, J. Keung, X. Yu, H. Zou, J. Zhang, and Y. Li

IEEE Transactions on Reliability, 2023.

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ICSR

Generating Natural Language Responses in Robot-Mediated Referential Communication Tasks to Simulate Theory of Mind

Z. Liu*, Y. Qin*, H. Zou*, E. J. Paek, D. Casenhiser, W. Zhou, and X. Zhao

International Conference on Social Robotics, 2022.

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