Professor of Artificial Intelligence · Xiamen University

Min Jiang

Editor-in-Chief, IEEE Computational Intelligence Magazine

My research lies at the intersection of evolutionary computation, learning-driven optimization, and scientific AI, with a particular interest in how intelligent systems adapt, reason, and support decision-making in complex environments.

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Min Jiang

“There is only one heroism in the world: to see the world as it is, and to love it.”

— Romain Rolland

“人生只有一种英雄主义，那就是认清生活的真相后，仍然热爱生活。”

— 罗曼·罗兰

Research Themes

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01

Learning-driven Optimization

Enhancing evolutionary algorithms with machine learning to achieve faster convergence, better generalization, and adaptive behavior in complex optimization scenarios.
02

Evolutionary Computation for Dynamic Complex Systems

Developing evolutionary algorithms that can track moving optima and adapt to changing environments in real-time decision-making scenarios.
03

Scientific AI and Intelligent Simulation

Applying AI to scientific discovery and simulation, with emphasis on differentiable simulation, physics-informed learning, and AI for science.
04

Computational Intelligence: From Results to Insight

Advancing the field from performance-oriented benchmarking toward deeper scientific understanding of why and how computational intelligence methods work.

Recent Work

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Editorial Reflections

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  • From Results to Insight: The Next Leap for Computational Intelligence
    May 2024
  • Beyond Optimization: Towards Responsible and Human-Centered AI
    Dec 2023
  • Fostering Meaningfulness in Scientific AI
    Mar 2023
  • The Role of CI in the Era of Foundation Models
    Jul 2023
  • Reflections on Editorship and Scholarly Communication
    Nov 2022
Read all reflections