Yichuan Zhang
The University of Tokyo2025 Google PhD Fellow

Yichuan Zhang

PhD Candidate in Human–AI Collaboration

I design intelligent systems that strengthen human decision-making — combining multimodal behavioral analysis with cognitive state modeling to make AI collaboration trustworthy and useful in practice.

  • · Human–AI Collaboration
  • · Time-Series Forecasting
  • · Cognitive State Modelling
  • · Multimodal Behavioural Analysis
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Advised by Professor Kazuo Hiekata

Portrait of Yichuan Zhang

Recent

Updates

  1. Paper published in IJHCI — Calibrated Intervention in Human–AI Collaborative Forecasting is now online.

  2. Built and presented the first LLM-powered paper network at a conference — CAS 2026.

    An interactive 3D semantic map (51 papers · 125 links; SPECTER embeddings + PCA) that lets every author see where their work sits. A team effort.

    CAS 2026 interactive 3D semantic map of accepted papers

  3. Paper accepted at TE2026 — Behavioral Adaptation in Human-AI Decision Making.

  4. Paper accepted at IJHCI — Calibrated Intervention in Human-AI Collaborative Forecasting.

View all updates →

Currently working on

Selected Research

Multimodal data collection setup
Active2023 – Present

Human–AI Collaboration in Forecasting Systems

Frameworks that enhance expert decision-making through synergistic human–AI interaction in time-series forecasting.

Read more →

Building

Selected Projects

Writing

Recent Publications

  1. 2026

    Calibrated Intervention in Human-AI Collaborative Forecasting: How Modification Intensity and Direction Interact to Determine Performance

    Zhang, Y., Hiekata, K., & Nakashima, T.

    Published · International Journal of Human-Computer Interaction

  2. 2026

    Behavioral Adaptation in Human-AI Decision Making: A Longitudinal Study Using Synchronized Eye and Mouse Tracking

    Y. Zhang, K. Hiekata, T. Nakashima, Q. Shao

    Accepted · 33rd Int. Conf. Transdisciplinary Engineering (TE2026)

  3. 2026

    Process-Informed Crowd Selection: Recovering Collective Prediction Gains Under AI Anchoring Through Eye-Tracking-Based Evidence Engagement Estimation

    Y. Zhang, K. Hiekata, T. Nakashima, Q. Shao

    Submitted · ACM Transactions on Computer-Human Interaction (TOCHI)

  4. 2025

    Bridging Human Cognition and AI Systems: A Transdisciplinary Engineering Study of Temporal Interaction Patterns in Collaborative Forecasting

    Y. Zhang, K. Hiekata, T. Nakashima, Q. Shao

    Accepted · 32nd Int. Conf. Transdisciplinary Engineering (TE2025)

Get in touch

Open to research collaborations and meaningful conversations.

7211395887@edu.k.u-tokyo.ac.jpGitHubLinkedInGoogle Scholar