Hi, I am Xue Jiang, a joint Ph.D. student at Trustworthy Machine Learning and Reasoning (TMLR) Group in Department of Computer Science, Hong Kong Baptist University, advised by Dr. Bo Han and Southern University of Science and Technology, advised by Prof. Feng Zheng. In TMLR Group, I am also co-supervised by Dr. Feng Liu and work closely with Dr. Zhen Fang.
My research interests mainly include out-of-distribution detection, trustworthy in MLLM and diffusion models (like hallucination, safety).
Please feel free to email me for research, collaborations, or a casual chat.
๐ Educations
- 2022.09 - present, Southern University of Science and Technology (SusTech) & Hong Kong Baptist University (HKBU), Ph.D. in Computer Science.
- 2019.09 โ 2022.06, Wuhan University, M.E. in Computer Science.
- 2015.09 - 2019.06, Wuhan University, B.E. in Electronic Information Engineering.
๐ Publications
โ๏ธ Corresponding author.
![sym](/_pages/data/figures/neg_label_fig1.png)
![sym](/_pages/data/figures/lt_ood.jpg)
![sym](/_pages/data/figures/aaai.jpg)
On the stability and generalization of triplet learning.
[paper]
Jun Chen, Hong Chenโ๏ธ, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng
![sym](/_pages/data/figures/kd.jpg)
๐ Awards
- Best Research Performance Award, HKBU 2024.05.
- Research Excellence Award, HKBU 2023.11.
- Excellent Postgraduate, Wuhan University 2020.
- 2nd Prize Excellent Academic Scholarship, Wuhan University 2020.
- Meritorious Winner (9\%), The Interdisciplinary Contest in Modeling 2018.
- Excellent Student, Wuhan University 2016 & 2017.
- 3rd Prize Scholarship, Wuhan University 2016 & 2017.
๐ป Services
- Conference Reviewer for ICML (22-24), NeurIPS (22-24), ICLR (22-24), MM 24.
- Journal Reviewer for TMLR, TNNLS, JAIR.
๐ซ Teaching
- 2024 Spring, TA for CS308: Computer Vision, SusTech.
- 2023 Fall, TA for CS205: C/C++ Program Design, SusTech.
- 2019 Fall, TA for Fundamentals of circuit and electronics, WHU.
๐ Experiences
- 2021.05 - 2021.12, Internship @Horizon Robotics, focusing on self-supervised learning related to object detection.