Zhuhan Dai (acciojunedai@gmail.com)

I received my B.Eng. in Software Engineering from Sun Yat-sen University. My research interests lie at the intersection of cognitive science and AI, with a particular focus on developing LLM-based agents as computational models of human personality and behavior. More specifically, I am interested in both building AI agents that can credibly simulate human behavior in interactive game environments and, in turn using games as testbeds to evaluate these agents and investigate human cognition.

Hanli Fan (hanli.fan@connect.hku.hk)

I am currently a Master’s student in Psychology at HKU. My research interest focuses on human-AI collaboration in decision-making, particularly in investment decision-making. I am also interested in behavioral economics and the cognitive mechanisms underlying financial judgement. I have over ten years of experience in the finance industry. I hold an MSc in Financial Economics from the University of Oxford, and a BSc in Physics from the University of Manchester. I am a Fellow Chartered Accountant (ICAEW) and a CFA charterholder.

Menghan Qu (menghanqu@connect.hku.hk)

I hold a bachelor’s degree in Cognitive Science from the University of Southern California (USC). I’m broadly interested in how perceptual, linguistic, and social cues interact with limited cognitive resources to shape decision making in context. Methodologically, I work with large-scale behavioral and language data analysis, applying formal and computational frameworks (latent-state and neural network models) to explore how sociocognitive dynamics are represented across human and AI systems.

Wentian (Cat) Wang (catwang616@gmail.com)

I am currently a researcher specializing in artificial intelligence and robotics. My research interest focuses on building agent and robot decision-making systems using Bayesian approaches that mirror human cognition, specifically by enabling agents to interpret human decision-making trajectories. I possess cross-domain expertise spanning Embodied AI, soft robotics, and AI for healthcare. My previous research experience across industry internships and academic assistantships includes reinforcement learning (RL) interpretation, LLM infrastructure, CRISPR-Cas9, and Sim2Real transitions. I hold an MS in Computer Science from the University of Southern California (USC) and a BS in Computer Science and Engineering from The Ohio State University (OSU).

Siyu Yan (yyyansiyu@connect.hku.hk)

I received my Master’s degree from The Hong Kong University of Science and Technology in 2025, advised by Prof. Yuyu Luo and Prof. Nan Tang, and my Bachelor’s degree from Nankai University in 2023. During the summer of 2025, I gained valuable experience as a research intern at Huawei 2012 Leibniz Systems Lab. My research interest is transitioning from Data-centric AI to AI for CogSci—that is, leveraging models to reverse-engineer human decision-making and explore the cognitive foundations of cooperation or social interaction.

Xenia-alexandra Belobokov (xenia-alexandra.belobokov@student.uni-tuebingen.de)

I am an undergraduate student in Cognitive Science at the University of Tübingen, currently an exchange student at HKU. My research interests lie at the intersection of AI and cognitive science, with a focus on how large language models represent and simulate human psychological states, and what the structure of those simulations reveals about the mental concepts we bring to them. Prior to joining the lab, I gained industry experience in humanoid robotics and LLM-based agentic systems. I also have a background in computational linguistics, with research on the quantitative modeling of humor and language processing.

Sofiia Buianova (sgbuyanova_1@edu.hse.ru)

I am a fourth-year undergraduate student in Computational Social Science (double major in Sociology and Applied Mathematics and Information Science) at the Higher School of Economics, currently a visiting student at HKU MAC Lab. My research focuses on collective behavior and decision-making in digital media, using network analysis, machine learning, and LLM-based simulation to uncover the latent social and psychological processes that shape how people interact with each other and with AI systems online, with the broader aim of informing safer, less biased online communities that do not overlook underrepresented groups.

Tianxin Huang (tianxin.huang@mail.mcgill.ca)

I am currently an undergraduate student in Artificial Intelligence at McGill University, and I recently completed an exchange semester at HKU. My research focuses on understanding and evaluating the reasoning processes of large language models, particularly their robustness, internal dynamics, and failure modes.