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Welcome to the Machine Intelligence and Nature-Inspired Computing (MIND) Lab, located in the Department of Computing at The Hong Kong Polytechnic University. Our lab is at the forefront of research in the exciting and rapidly evolving field of nature-inspired artificial intelligence. We are dedicated to exploring the latest advancements in AI and their applications in diverse fields such as material science, healthcare, logistics, robotics, and speech processing. 

At MIND, we are proud to have an exceptional research team, whose contributions have been recognized with numerous prestigious awards. These include the IEEE Computational Intelligence Magazine Outstanding Paper Award in both 2019 and 2024, the IEEE Transactions on Cybernetics Outstanding Paper Award in 2020, the IEEE Transactions on Neural Networks and Learning Systems Award in 2016, and the 1st Prize of International Competition for Brain-inspired Computing in 2018. 

We welcome individuals who are passionate about cutting-edge AI research and who want to make a difference in the world. Join us at MIND and be a part of our dynamic and innovative team!


Congratulations to Dr. Jibin WU's GRF fund entitled "Sense Like Your Brain: Advancing Audio-Visual Perception and Understanding with Brain-inspired Technologies" has been funded by RGC.

Jun 2024

Congratulations to Prof Tan's GRF fund entitled "Towards Efficient Large Model Training via Learning from Small Models" has been funded by RGC.

Jun 2024

Congratulations to Mr. Xiang Hao for his work "Pink-Eggs Dataset: A Step Toward Invasive Species Management Using Deep Learning Solutions" accepted by The 11th IEEE International Conference on Cybernetics and Intelligent Systems & Robotics, Automation and Mechatronics (CIS-RAM 2024).

Jun 2024

Congratulations to Dr. Yinglan Feng for her work “Towards Multi-Objective High-Dimensional Feature Selection via Evolutionary Multitasking” accepted by Swarm and Evolutionary Computation.

Jun 2024


The Hong Kong Polytechnic University,

Hung Hom, Kowloon, Hong Kong SAR

+852 2766 7301

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