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

Advised by Professor Kazuo Hiekata

Portrait of Yichuan Zhang

Recent

Updates

  1. Paper accepted at CIKM 2026 — Sensing How Users Adapt to AI Decision Support: A Multimodal Eye and Mouse Tracking Study

  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 IJHCI — Calibrated Intervention in Human-AI Collaborative Forecasting.

Currently working on

Selected Research

Yichuan wearing eye-tracking glasses, interacting with a Human-AI electricity-demand forecasting interface (SHAP interpretability + adjustment panel)
Active2023 – Present

Human-AI Collaboration in High-Risk Decision Domains with Eye Tracking

Modelling human behaviour in high-risk decision workflows using eye-tracking data — the empirical arm of the PhD, spanning six papers across IJHCI, TOCHI, TE, and INCOSE CAS.

Read more →
Radar planview display used in the ATC eye-tracking study — Fukuoka/Naha sector with live flight tracks
Active2026 – Present

Human-AI Collaboration in ATC — Contrail Avoidance with Eye Tracking

Studying how air traffic controllers process contrail-avoidance guidance on radar displays — and how AI decision-support can surface climate-relevant information without adding to their workload.

Read more →

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

    Sensing How Users Adapt to AI Decision Support: A Multimodal Eye and Mouse Tracking Study

    Y. Zhang

    Accepted · 35th ACM International Conference on Information and Knowledge Management (CIKM 2026)

  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

    Preprint · Under Review · 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.