2025.03-至今 KAUST （阿卜杜拉国王科技大学）
访问学者，
LSTM之父-Juergen Schmidhuber组
2023.02 —— 至今 吉林大学人工智能学院 教授
2020.12—— 2023.02 香港中文大学（深圳） 博士后，导师为查宏远老师
Zhuo Li, He Zhao, Jinke Ren,
Anningzhe Gao,
Dandan Guo*
, Xiang Wan,Hongyuan Zha.
Synthesizing Minority samples for Long-tailed Classification via Distribution Matching. TMLR （机器学习领域发起的新期刊)， 2025.
Zhuo Li, He Zhao, Anningzhe Gao,
Dandan Guo*
, Tsung-Hui Chang, Xiang Wan.Prototype-oriented Clean Subset Extraction for Noisy Long-tailed Classification [J]. In IEEE Transactions on Circuits and Systems for Video Technology, doi:10.1109/TCSVT.2025.3546031, 2025.
(TCSVT, 中科院 1 区)
Jiani Ni, He Zhao, Jintong Gao,
Dandan Guo*（通信）
, Hongyuan Zha. Balancing Two Classifiers via A Simplex ETF Structure for Model Calibration[C]//In In IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025.（CCF A 类会议）
Hairui Ren, Fan Tang, He Zhao, Zixuan Wang,
Dandan Guo*（通信）,Yi Chang
*
（通信）
. Beyond Words: Augmenting Discriminative Richness via Diffusions in Unsupervised Prompt learning//The IEEE/CVF Conference on Computer Vision and Pattern Recognition,2025. (CVPR, CCF A 类会议)
Changlong Shi, He Zhao, Bingjie Zhang, Mingyuan Zhou,
Dandan Guo*（通信）,Yi Chang
*
（通信）
. FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors[C]//In In IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025.（ CVPR, CCF A 类会议）
Changlong Shi, Jinmeng Li, He Zhao,
Dandan Guo*（通信）,Yi Chang
*
（通信）
. FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking[C]//The Thirteenth International Conference on Learning Representations,2025.(清华计算机评定 A 类会议)
Hangting Ye, He Zhao，Wei Fan, Mingyuan Zhou,
Dandan Guo
*（通信）,Yi Chang
*
（通信）
. DRL: Decomposed Representation Learning for Tabular Anomaly Detection[C]//International Conference on Learning Representations, 2025.（清华计算机评定A类会议）
Hongting Chen, Chuan Du, Jinlin Zhu,
Dandan Guo
. Target-Aspect Domain Continual Learning for SAR Target Recognition [J].
IEEE Transactions on Geoscience and Remote Sensing (TGRS,中科院1区),
2025.
Hairui Ren, Fan Tang,Huangjie Zheng,He Zhao,
Dandan Guo
*（通信）,Yi Chang
*
（通信）. Modality-Consistent Prompt Tuning with Optimal Transport[J]//
IEEE Transactions on Circuits and Systems for Video Technology
.
(TCSVT
,
中科院
1
区
)
Jintong Gao, He Zhao,
Dandan Guo*
, Hongyuan Zha. Distribution Alignment
Optimization through Neural Collapse for Long-tailed Classification [C]//
International Conference on Machine Learning,2024. (
ICML，CCF-A
)
Hangting Ye, Wei Fan , Xiaozhuang Song, Shun Zheng, He Zhao,
Dandan Guo∗
, Yi Chang∗. PTARL: Prototype-based Tabular Representation Learning via Space Calibration[C]//In International Conference on Learning Representations,2024. (ICLR,清华计算机评定A类会议, Spotlight)
Dandan Guo
, Long Tian, Chuan Du , Pengfei Xie , Bo Chen and Lei Zhang. Suspicious Object Detection for Millimeter-Wave Images with Multi-View Fusion Siamese Network[J]. IEEE Transactions on Image Processing, 2023. (
IEEE TIP
,
中科院1区，CCF-A
)
Jintong Gao, He Zhao, Zhuo Li,
Dandan Guo*
. Enhancing minority classes by mixing: an adaptive optimal transport approach for long-tailed classification[C]// Advances in Conference on Neural Information Processing Systems (2023).(
NeurIPS, CCF A
)
Dandan Guo
, Zhuo Li, Meixi zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha. Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification[C]//Advances in Conference on Neural Information Processing Systems (2022).（
NeurIPS，CCF A
）
Dandan Guo
, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha. Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport[C]//Advances in Conference on Neural Information Processing Systems (2022).（
NeurIPS，CCF A
)
Dandan Guo
， Chaojie Wang , Baoxiang Wang, and Hongyuan Zha. Learning Fair Representations via Distance Correlation Minimization[J]//IEEE Transactions on Neural Networks and Learning Systems, 2022, doi: 10.1109/TNNLS.2022.3187165.(
TNNLS,中科院1区
)
Dandan Guo+
, Ruiying Lu+, Bo Chen and Mingyuan Zhou. Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning[J]//International Journal of Computer Vision , 2022, 130(8): 1920-1937. (
IJCV,CCF-A
)共同作者
Dandan Guo
, Long Tian, Minghe Zhang, Mingyuan Zhou, and Hongyuan Zha.Learning Prototype-oriented Set Representations for Meta-Learning[C]//In International Conference on Learning Representations,2022. (
ICLR,清华计算机评定A类会议
)
Dongsheng Wang+,
Dandan Guo+
, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen and Mingyuan Zhou. Representing Mixtures of Word Embeddings with Topic Embeddings[C]//In International Conference on Learning Representations,2022. (
ICLR,清华计算机评定A类会议
)
Dandan Guo
, Bo Chen, Meixi Zheng and Hongwei Liu. SAR Automatic Target Recognition based on Supervised Deep Variational Auto-encoding Model[J]// IEEE Transactions on Aerospace and Electronic Systems,57 (6), 4313-4328,2021.(
TAES,中科院2区
)
Dandan Guo
, Bo Chen, Ruiying Lu and Mingyuan Zhou. Recurrent Hierarchical Topic-Guided RNN for Language Generation [C]/In International Conference on Machine Learning, 2020. （
ICML,CCF A
）
Dandan Guo
, Bo Chen, Wenchao Chen and Mingyuan Zhou, Hongwei Liu. Variational Temporal Deep Generative Model for Radar HRRP Target Recognition[J]// IEEE Transactions on Signal Processing, 68, 5795-5809,2020. (
TSP,中科院1区
)
Dandan Guo
, Bo Chen, Hao Zhang and Mingyuan Zhou. "Deep Poisson Gamma Dynamical Systems[C]//Advances in Conference on Neural Information Processing Systems, 2018.（
NeurIPS,CCF A
）
Jinpeng Hu,
Dandan Guo
, Yang Liu , Zhuo Li , Zhihong Chen, Xiang Wan1,Tsung-Hui Chang. A Simple yet Effective Subsequence-Enhanced Approach for Cross-Domain NER. Association for the Advancement of Artificial Intelligence,2023. (
AAAI,CCF-A
)
Jinpeng Hu, He Zhao,
Dandan Guo*
, Xiang Wan*, Tsung-Hui Chang. " A Label-Aware Autoregressive Framework for Cross-Domain NER". Findings of NAACL (共同通信), 2022.
Chuan Du, Yulai Cong, Lei Zhang,
Dandan Guo
, Song Wei. "A Practical Deceptive Jamming Method Based on Vulnerable Location Awareness Adversarial Attack for Radar HRRP Target Recognition" in IEEE Transactions on Information Forensics and Security(
TIFS, SCI 一区，影响因子 7.178
)，2022.
Hao Zhang, Bo Chen, Yulai Cong,
Dandan Guo
, Hongwei Liu, and Mingyuan Zhou. “Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference”, IEEE Transactions on Pattern Analysis and Machine Intelligence (
TPAMI, 机器学习顶级期刊，CCF-A 类期刊，影响因子:17.73
), 2020.
Chuan Du, Bo Chen, Bin Xu,
Dandan Guo
, and Hongwei Liu, “Factorized discriminative conditional variational auto-encoder for radar HRRP target recognition,” Signal Processing (
SP，信号处理期刊，SCI 二区，影响因子：4.086
), vol. 158, pp. 176–189, 2019.
Hao Zhang, Bo Chen,
Dandan Guo
, and Mingyuan Zhou. “WHAI. Weibull Autoencoding Inference for Deep Topic Modeling”, in International Conference on Learning Representations（
ICLR，机器学习顶级国际会议，清华计算机评定 A 类会议
）, 2018.
1、
本组对于学生的第一要求是热爱祖国，遵纪守法，身心健康，积极开朗，遇到困难不会逃避。注：科研是一个探索未知的过程，失败是必不可少的，喜欢迎难而上、遇到困难也能保持乐观的同学请联系我；如果心理脆弱、抗压能力一般、难以经受失败或者难以接受老师的建议，请勿联系。
2、每年将招收多名硕士（保研、考研3名）、博士研究生（直博、硕博或者申请考核制1名）、博士后（欢迎了解博士后政策），欢迎highly motivated的学生，希望大家尽早联系。注：组里机会较多，欢迎大家确定之后提前进组（不强求）。
3、对于博士生的培养细致且严格，经我手里毕业的学生需要具有一定的独立科研能力，以后在人工智能领域能够做出相应贡献，对得起“某某博士”的称呼，符合课题要求且表现较好的同学会推荐与领域大佬合作、访问等。注：博士生面试需要花费双方一定时间，广撒网的同学勿扰。
4、对于硕士生有科研要求，进组之后无心科研的同学勿扰。注：有
联系我的学生问能否实习，统一回复：发表顶会（或者相应期刊等，本组这个要求不难达到）之后允许实习，另外如
研究方向符合导师与企业的合作方向会给学生机会合作或者实习。
5、欢迎对科研有兴趣并希望继续深造的本科生。欢迎想直博的本科生提前联系。
6、在统计机器学习、数学、编程等任一方面有较深的功底和较浓的兴趣。优先考虑有编程经验和科研经历的申请者。
如果你符合以上要求，并且对本组课题感兴趣，请积极联系。本组和国内外机器学习领域多名优秀学者合作机会较多，可以提供一个全新的视野，并鼓励发表文章的学生参加国内外知名学术会议。
期待你的进步与成长，让
我们一起为祖国的人工智能发展贡献自己的力量！
