NJUST KMG

School of Computer Science and Engineering,
Nanjing University of Science & Technology

Introduction

Knowledge Mining Group (KMG) is affiliated with the PCA Lab, School of Computer Science and Engineering, Nanjing University of Science and Technology, China.
KMG focuses on multimodal learning, incremental learning, and model reuse in machine learning and data mining. We also emphasize the practical application of our research findings in real-world contexts, including image retrieval, video scene segmentation, and novelty detection. For further details on our work, please visit the Publications page.

Recruitment Introduction

We are currently in search of outstanding individuals to join our group. We welcome PhD and master's students, as well as undergraduate students interested in research training or completing their final year projects, to become part of our team. We are looking for individuals who possess a strong passion for academia, a diligent work ethic, and the drive to overcome challenges.
Furthermore, we offer opportunities for exceptional interns, including collaborative training programs with esteemed partner enterprises. As an intern with us, you will have the opportunity to engage in challenging and cutting-edge research projects, working closely with industry partners to gain invaluable practical experience.
If you are interested and meet the requirements, please do not hesitate to contact Prof. Yang Yang or Associate Prof. Weili Guo for further information and application procedures. We look forward to hearing from you and welcoming you into our group.
[Tips 1]For students aspiring to pursue a master's or doctoral degree, we encourage you to showcase your proficient programming skills, good command of English, and effective communication abilities. We will provide you with various training and guidance to support your steady growth.
[Tips 2]We expect you to engage in high-quality scientific research and strive to publish outstanding academic achievements in top-tier journals and conferences that withstand the test of time, rather than solely focusing on obtaining a degree.

News

  • Congratulations to the team members on their achievement of being crowned as Champions of the CVPR 2024 Foundational Few-Shot Object Detection Challenge! [Report]
  • Congratulations to the team members on their achievement of being crowned as Champions of the CVPR 2024 Multi-modal Aerial View Imagery Challenge - T (Translation)! [Report]
  • Congratulations to the team members on their achievement of being crowned as Champions of the 2024 ISPRS TC I Contest on Intelligent Interpretation for Multi-modal Remote Sensing Application Classification of Multiscale Marine Phenomenon in SAR Images! [Report]
  • Congratulations to the team members on their achievement of being crowned as second runner-up of the 2024 ISPRS TC I Contest on Intelligent Interpretation for Multi-modal Remote Sensing Application Forgery Detection in Multi-scenario Remote Sensing Images of Typical Objects! [Report]
  • Congratulations to the team members on having their paper accepted by the Proceedings of the 33rd International Joint Conference on Artificial Intelligence(IJCAL-2024)!
  • Congratulations to the team members on having their paper accepted by the IEEE International Conference on Multimedia and Expo(ICME-2024)!