Education:
🎓 Dr. Li earned her Ph.D. in Intelligent Information Processing from Xidian University, China (2017). She also holds a Bachelor’s degree in Electronic Information Engineering from the same university (2011). From 2013 to 2014, she was a visiting scholar at the University of the Basque Country in Spain, enhancing her global research perspective. 🌍
Experience:
👩🏫 Since 2020, Dr. Li has served as an Associate Professor at the School of Artificial Intelligence, Xidian University. Prior to this, she was a Lecturer at the same institution. She has supervised 16 master’s students and co-supervised 6 Ph.D. students, establishing herself as a leader in AI and remote sensing image interpretation. 💼
Research Focus:
🔍 Dr. Li’s research revolves around deep learning, quantum evolutionary optimization, and multi-scale geometric analysis. She works on complex image interpretation and target recognition, contributing to advancements in AI-powered remote sensing. Her research addresses pressing issues in multi-objective learning and large-scale remote sensing image retrieval. 🚀
Awards and Honours:
🏆 Dr. Li has received multiple national-level funding grants, including projects funded by the National Natural Science Foundation of China and Xidian University. Her research accomplishments are well-recognized in the academic community. 💡
Publications Top Notes:
📚 Dr. Li has contributed to top-tier journals and conferences, collaborating with renowned researchers. Some of her most notable works include:
“Region NMS-based deep network for Gigapixel Level Pedestrian Detection with Two-Step Cropping” – Neurocomputing, 2021 Cited by: 45
“Deep multi-level fusion network for multi-source image pixel-wise classification” – Knowl. Based Syst., 2021 Cited by: 50
IPGN: Interactiveness Proposal Graph Network for Human-Object Interaction Detection” – IEEE Trans. Image Process., 2021 Cited by: 78
“C-CNN: Contourlet Convolutional Neural Networks” – IEEE Trans. Neural Networks Learn. Syst., 2021 Cited by: 120
“Multi-Scale Progressive Attention Network for Video Question Answering” – ACL/IJCNLP, 2021 Cited by: 34