NJUST KMG
School of Computer Science and Engineering,
Nanjing University of Science & Technology
Group Introduction
KMG is affiliated with the School of Computer Science and Engineering at Nanjing
University of Science and Technology, located in the Dingxin Building of the Nanjing Campus. The group is led
by Professor Yang Yang.
The meaning of KMG is "Knowledge Mining Group". KMG's main research interests include
data mining, machine learning, pattern recognition, as well as fundamental, cutting-edge, and innovative
research work in related fields. At present, research on open environment data mining mainly focuses on
multimodal learning, open set learning, incremental learning, as well as research in practical scenarios. For
more detailed research information, please visit
Publications.
Recruitment Introduction
We welcome students who are interested in applying for postdoctoral
positions, pursuing Ph.D. or Master's degrees, as well as undergraduates who wish
to participate in scientific research training or complete their graduation thesis to join our group.
If you wish to apply for a postdoctoral position or pursue a Ph.D. degree at KMG,
please contact Professor Yang Yang; if you wish to pursue a Master's
degree at KMG, please contact Professor Yang Yang, Professor Wei Li Guo, or Professor Qing Yuan Jiang via email. If you are interested in
undergraduate research training or a graduation thesis (limited to Nanjing University of Science and
Technology students), please contact the specific teacher via email. PS: Please attach your resume to the
above emails.
Before sending the email, please take the time to read the following instructions to
confirm that we share the same research concepts and interests:
- Research Qualifications We expect you to have a solid mathematical foundation, proficient English reading and writing skills, strong programming abilities, and excellent team collaboration spirit.
- Personal Qualities We expect you to possess the spirit of hard work, optimism, and positivity in scientific research (the path of scientific research is not always smooth), as well as to be honest and trustworthy (this is the basic requirement for scientific research), and to have a sense of responsibility (responsible for your own research, and also for the team and society).
- Future Planning We expect you to be clear about whether you are inclined to continue in academic research or to work in a company (we will design different training methods accordingly).
Please carefully consider and self-assess based on the above requirements, and then describe in detail in the email how you meet these conditions. We are very keen to understand your background and experience, especially in terms of research qualifications, personal qualities, and future planning. This will help both parties to better judge whether we can work together in the future academic journey. We look forward to receiving your feedback and sincerely hope that we can become like-minded partners, exploring the vast world of academia together.
News
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Congratulations to the team members on having their paper accepted by the Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence (AAAI-2025)!
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Congratulations to the team members on having their paper accepted by the IEEE Transactions on Image Processing (IEEE TIP-2024)!
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Congratulations to the team members on their achievement of being crowned as runner-up of the
Fourth "Tianzhi Cup" Artificial Intelligence Challenge - In the Remote Sensing Application Track, the subject of image content generation based on large models in the field of remote sensing applications.!
[news]
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Congratulations to the team members on their achievement of being crowned as Champion of the
2024 ECCV Temporal Action Localisation Track.!
[news]
Congratulations to the team members on their achievement of being crowned as Champion of the
2024 ECCV Single Object Tracking Track.!
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