UniSQ–BUPT Joint Lab

Human-centric
Intelligence Lab

We develop AI systems that understand, serve, and empower people — bridging large language models, computational social systems, and responsible AI to address real-world human needs.

A joint research initiative under the UniSQ–BUPT Cotutelle Program, connecting the University of Southern Queensland (Australia) and Beijing University of Posts and Telecommunications (China).

Explore Our Research → Open Positions
About Us

Where Human Needs Meet AI Innovation

The Human-centric Intelligence Lab (HI Lab) operates under the UniSQ–BUPT Joint Lab framework, leveraging the Cotutelle Program to foster cross-border doctoral research in AI.

Our lab brings together researchers from the University of Southern Queensland and Beijing University of Posts and Telecommunications to tackle fundamental challenges in human-centered artificial intelligence. We believe that AI should be designed, developed, and deployed with people at the center.

Through the Cotutelle Program, our PhD students receive co-supervision from both institutions, spending research time across Australia and China. This dual-perspective approach produces graduates who understand diverse research cultures and can bridge academic traditions.

Our work spans large language models, computational social systems, AI safety, recommender systems, and emergency management — always grounded in real human needs and societal impact.

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Dual Supervision

PhD students co-supervised by faculty from both UniSQ and BUPT

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Cross-Cultural Research

Research conducted across Australia and China

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Top Venue Publications

Papers at NeurIPS, ICML, ICLR, KDD, ACL, and more

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Industry Impact

Research addressing real-world social and technological challenges

Lab photo coming soon
UniSQ × BUPT

Established under the UniSQ–BUPT Cotutelle Agreement for joint doctoral training and collaborative research.

Research

Research Areas

Our research focuses on building AI systems that are safe, socially aware, and centered on human values — from foundational models to real-world applications.

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Large Language Models

Advancing the capabilities and understanding of large language models, with a focus on safety, alignment, bias mitigation, and natural language generation for social good.

LLM Safety Alignment NLG Bias
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Computational Social Systems

Modeling and analyzing complex social phenomena through computational methods, including social network analysis, opinion dynamics, and collective intelligence.

Social Networks Opinion Dynamics Misinformation
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Agentic AI

Designing autonomous AI agents that can plan, reason, and act in complex environments, with emphasis on human oversight, controllability, and collaborative interaction.

AI Agents Planning Human-AI Collaboration
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Recommender Systems

Building recommendation algorithms that are fair, explainable, and aligned with user preferences, incorporating graph-based methods and knowledge-aware approaches.

Recommendation Fairness Graph Mining
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Urban Computing & Emergency Management

Applying AI to understand urban environments and improve emergency response, including disaster prediction, resource allocation, and crisis communication.

Smart Cities Disaster Response Crisis AI
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Brain-Inspired AI

Drawing inspiration from neuroscience to develop more efficient and robust AI architectures, exploring the intersection of cognitive science and machine learning.

Neuroscience Cognitive AI Neural Architecture
People

Our Team

Our lab brings together faculty and students from UniSQ and BUPT, united by a shared commitment to human-centric AI research.

Faculty

UniSQ Team
Prof. Xiaohui Tao

Prof. Xiaohui Tao

Professor & Director (UniSQ)
University of Southern Queensland, Australia
Knowledge Graphs, Health Informatics, AI for Healthcare, NLP, Semantic Web, Machine Learning
Profile Scholar
Dr. Kaize Shi

Dr. Kaize Shi

Lecturer & Deputy Director (Research, UniSQ)
University of Southern Queensland, Australia
LLMs, Computational Social Systems, Emergency Management, Urban Computing, NLG, Recommender Systems
Profile Scholar
BUPT Team
Prof. Zhonghong Ou

Prof. Zhonghong Ou

Professor & Director (BUPT)
Beijing University of Posts and Telecommunications, China
Network Intelligence, Internet of Things, Edge Computing, 5G/6G Networks, AI for Networks
Profile Scholar
Dr. Yifan Zhu

Dr. Yifan Zhu

Associate Professor & Deputy Director (Research, BUPT)
Beijing University of Posts and Telecommunications, China
Agentic AI, LLM Safety, Graph Mining, Brain-Inspired AI, Recommender Systems
Profile Scholar

PhD Students (Cotutelle Program)

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Positions Available

UniSQ–BUPT Cotutelle PhD
We are actively recruiting PhD students for the Cotutelle Program. See Join Us for details.
News

Latest Updates

Recent highlights, announcements, and milestones from our lab.

May
01
2026
Announcement

PhD Positions Available

We are recruiting PhD students for the Cotutelle Program. Strong candidates in LLM, social computing, and AI safety are encouraged to apply.

May
01
2026
Announcement

HI Lab Website Launched

The Human-centric Intelligence Lab officially launches its website, marking a new chapter in our research communication.

Apr
15
2026
Event

UniSQ–BUPT Joint Lab Established

The Cotutelle agreement between UniSQ and BUPT has been signed, establishing the framework for our joint doctoral program.

Opportunities

Join Our Lab

We are looking for motivated researchers who are passionate about building AI that truly serves humanity.

Cotutelle PhD Program

Our PhD students are jointly enrolled at both the University of Southern Queensland and Beijing University of Posts and Telecommunications through the Cotutelle Program. Students receive co-supervision from Dr. Kaize Shi (UniSQ) and Dr. Yifan Zhu (BUPT), spending research time at both institutions.

Upon completion, graduates receive recognition from both universities for their doctoral work, reflecting the international nature of their training.

What We Look For

  • Strong background in computer science, AI, or related fields
  • Research experience in one or more of our focus areas
  • Publications at recognized venues (preferred but not required)
  • Strong programming skills (Python, deep learning frameworks)
  • Excellent written and spoken English
  • Self-motivated with strong communication skills

Research Topics

  • Large language model safety, alignment, and bias
  • Agentic AI and human–AI collaboration
  • Computational social systems and misinformation detection
  • Graph-based recommendation and knowledge-aware systems
  • AI for emergency management and urban computing
  • Brain-inspired architectures for efficient AI

Benefits

  • International research experience across two countries
  • Co-supervision by experts from both institutions
  • Access to computing resources at both universities
  • Opportunities to publish at top-tier venues
  • Scholarship support (subject to eligibility)

How to Apply

Interested candidates should send an email to either supervisor with:

  • 1. Your CV / Resume
  • 2. Academic transcripts
  • 3. Research statement (1-2 pages)
  • 4. Representative publications (if any)
  • 5. English proficiency (IELTS/TOEFL)
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UniSQ Supervisor
kaize.shi@unisq.edu.au
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BUPT Supervisor
yifan_zhu@bupt.edu.cn
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UniSQ Campus
Brisbane, QLD, Australia
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BUPT Campus
Haidian, Beijing, China
Send Application →