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Hi there, I’m Junjie (Jorji) Chen (陈俊杰) 👋

🚀 About Me

I am currently a third-year master’s student at Anhui Polytechnic University (AHPU), supervised by Prof. Subin Huang. My hometown is Lu’an, Anhui, China.

I am a Research Intern at the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, supervised by Prof. Meng Wang, and I plan to apply for PhD studies in Fall 2026. I am also working with Linfeng Zhang and his research group, where I am learning and exploring research problems related to Efficient AI.

💡 I am broadly interested in understanding how AI systems can better model human psychological and emotional states, and how such understanding can be incorporated into practical and efficient interactive systems.


🎯 Research Focus

I am primarily interested in the following research question:

How can we build psychologically grounded, fine-grained, multimodal, efficient, and full-duplex conversational AI systems that better understand and respond to human emotions?

In particular, I am learning and exploring:

  • 🧠 Psychology-informed modeling of emotion and cognition in dialogue systems.
  • 🎭 Fine-grained emotion perception, including subtle, dynamic, and context-dependent affect.
  • 🔊🖼️ Multimodal interaction, combining language with visual, acoustic, and behavioral cues.
  • Efficiency-aware methods for building deployable and scalable dialogue models.

For a deeper dive into my long-term roadmap and methodology, please visit my Research Vision.


🔬 Research Interests

The following areas reflect my current interests and learning directions, which support the above research focus:

  • 🧠 AI4Psychology
    Computational approaches to modeling psychological processes.

  • Efficient AI
    Model compression, acceleration, and efficiency-oriented learning.

  • 🎭 Multimodal AI
    Representation learning and fusion across multiple modalities.

  • 🖌️ Generative AI
    Controlled and interpretable generation for dialogue and simulation.

  • 🧭 Spatial Intelligence
    Embodied and environment-aware reasoning related to interaction and behavior.

These directions are not independent goals, but are explored as part of a broader effort to understand and build psychologically informed conversational AI.


💬 Let’s Collaborate!

I am always happy to learn from and collaborate with researchers interested in:

  • Emotion and affect modeling grounded in psychology
  • Multimodal dialogue systems
  • Efficient and practical conversational AI

If our interests overlap, I would be glad to connect and exchange ideas.

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