About Me
I am Yun Li, a postdoc fellow at CSIRO's Data61, aiming to design cutting-edge machine learning algorithms. Before that, I received my PhD degree in Computer Science from the University of New South Wales, Australia, under the supervision of Prof. Lina Yao and Prof. Wenjie Zhang. I received my M.S. and B.S. degrees from the Department of Computer Science and Engineering, Nanjing University, in 2019 and 2016, respectively.
I serve as the reviewer or program committee member for a set of prestigious conferences and journals such as MM, AAAI, CIKM, The Web Conf, TCSVT, KNOSYS, TMM, etc, and serve as the Sponsorship Chair for ADMA 2024 (Advanced Data Mining and Applications Conference). I am also a recipient of the 2021 Google PhD Fellowship (only 4 PhD student awardees in Australia) and the 2023 Dean’s Award for Outstanding PhD Theses (Top 10% of the PhD theses).
You may see my latest CV here (2024-01 edition).
[go top]
Research Interest
My research interests lie in Data-efficient Computer Vision (such as zero-shot learning and meta-learning) and Transferable Machine Learning (such as domain adaptation and transfer learning), focusing on developing deep learning algorithms using fewer resources (such as human annotations) and having more applied domains.
My research is motivated by and contributes to various applications in computer vision, genetic analysis, medical image predictions, and healthcare informatics. Additionally, I have gained research experience working with other types of data, including spatial datasets, graph datasets, and short text corpora.
[go top]
Publications (* indicates equal contribution)
Conference Papers
- Yun Li, Zhe Liu, Hang Chen and Lina Yao. ''Context-based and Diversity-driven Specificity in Compositional Zero-Shot Learning.''The 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle USA, June 17 - 21, 2024.
- Yun Li, Zhe Liu, Saurav Jha, and Lina Yao. ''Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning.'' The 2023 International Conferences on Computer Vision (ICCV-23), Paris France, October 2 - 6 2023.
- Xiaoxin Ye, Yun Li, and Lina Yao. ''DREAM: Decoupled Representation via Extraction Attention Module and Supervised Contrastive Learning for Cross-Domain Sequential Recommender.'' The 17th ACM Recommender Systems Conference (RecSys 2023), Singapore Sept. 18 - 22 2023.
- Zhe Liu, Yun Li*, Lina Yao, Xianzhi Wang. ''Task Aligned Generative Meta-learning for Zero-shot Learning.'' The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI, 2021). (CORE: A*).
- Yun Li, Zhe Liu, Lina Yao, Zihuai He. ''Non-local Self-attentive Autoencoder for Genetic Functionality Prediction.'' The 29th International Conference on Information and Knowledge Management, (CIKM 2020). (CORE: A).
- Yixiang Fang, Reynold Cheng, Gao Cong, Nikos Mamoulis, Yun Li. ''On Spatial Pattern Matching." International Conference on Data Engineering (ICDE, 2018). (CORE A*). [online demo]
Journal Articles
- Zhe Liu, Yun Li, Lina Yao, Xiaojun Chang, Wei Fang, Xiaojun Wu and Abdulmotaleb El Saddik. ''Simple Primitives with Feasibility and Contextuality-Dependence for Open-World Compositional Zero-shot Learning.'' IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2023 (to appear).
- Yun Li, Zhe Liu, Lina Yao, Jessica J.M.Monaghan, David McAlpine. ''Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis.'' IEEE Journal of Biomedical and Health Informatics (JBHI, 2022). (IF=7.021, SJR Q1, CORE A*).
- Yun Li, Zhe Liu, Xiaojun Chang, Julian McAuley, and Lina Yao. ''Diversity-boosted Generalization-Specialization Balancing for Zero-shot Learning.'' IEEE Transactions on Multimedia (TMM, 2022). (IF=8.182, SJR Q1, CORE A*) .
- Zhe Liu, Yun Li, Lina Yao, Molly Lucas, Jessica~J.M.Monaghan, and Yu Zhang. ''Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus.'' IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE, 2022). (IF=4.528, SJR Q1).
- Zhe Liu, Yun Li*, Lina Yao, and Julian McAuley. ''Rethink, Revisit, Revise: Spiral Reinforced Self-Revised Learning for Zero-Shot Learning.'' IEEE Transactions on Neural Networks and Learning Systems (TNNLS, 2022). (IF=14.255, SJR Q1, Core A*).
- Yun Li, Zhe Liu, Lina Yao, Xianzhi Wang, Julian McAuley, Xiaojun Chang. ''An Entropy-Guided Reinforced Partial Convolutional Network for Zero-Shot Learning.'' IEEE Transactions on Circuits and Systems for Video Technology (TCSVT, 2022). (IF=5.859, SJR Q1).
- Yun Li, Zhe Liu, Lina Yao, Xiaojun Chang. ''Attribute-Modulated Generative Meta-Learning for Zero-shot Learning.'' IEEE Transactions on Multimedia (TMM, 2021). (IF=8.182, SJR Q1, CORE A*).
- Xiaocong Chen, Yun Li, Lina Yao, Ehsan Adeli, Yu Zhang, Xianzhi Wang. ''Generative adversarial U-Net for domain-free few-shot medical diagnosis.''[J], Pattern Recognition Letters (PRL, 2021). (IF=5.67, SJR Q1, CORE B).
- Zhe Liu, Xianzhi Wang, Yun Li, Lina Yao, Lei Bai and Ee-Peng Lim. ''Face to Purchase: Predicting Consumer Choices with Structured Facial and Behavioral Traits Embedding.'' Knowledge-based System (KNOSYS, 2021) (IF=8.038, JCR Q1, SJR Q1).
- Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Feipinng Nie. ''Agglomerative Neural Networks for Multi-view Clustering.'' IEEE Transactions on Neural Networks and Learning Systems (TNNLS, 2021). (IF=14.255, SJR Q1, Core A*)1.
- Yun Li, Yixiang Fang, Reynold Cheng, Wenjie Zhang. ''Spatial pattern matching: A new direction for finding spatial objects. "[J], SIGSPATIAL Special, 2019, 11(1): 3-12.
- Yixiang Fang, Yun Li, Reynold Cheng, Nikos Mamoulis, Gao Cong. ''Evaluating Pattern Matching Queries for Spatial Databases." The International Journal on Very Large Data Bases (VLDBJ, 2019). (IF=4.243, SJR Q1, CORE A*).
- Hengyang Lu, Yun Li, Chi Tang, Chongjun Wang, Junyuan Xie. ''Constructing Pseudo Documents with Semantic Similarity for Short Text Topic Discovery." International Conference on Neural Information Processing (ICONIP, 2018). (CORE A).
- Yankai Chen, Yixiang Fang, Reynold Cheng, Yun Li, Xiaojun Chen, Jie Zhang. ''Exploring Communities in Large Profiled Graphs." IEEE Transactions on Knowledge and Data Engineering (TKDE, 2018). (IF=9.235, SJR Q1, CORE A*)
[go top]
Awards & Honors
- Dean’s Award for Outstanding PhD Theses, 2023
- Google PhD Fellowship in Machine Learning, 2021
- CIKM student travel grant, 2020
- Computer Science funded Top-ups Scholarships, 2020
- University International Postgraduate Award (UIPA), from 2019 to 2023
- First Prize of Academic Scholarships, 2017, 2016
- ... ...
[go top]
Professional Services
- Organizing Committee: ADMA 2024 (Sponsorship Chair)
- Conference Reviewer: AAAI, KDD, CIKM, WWW, etc.
- Journal Reviewer: TCSVT, TIST, TMM, KNOSYS, TOSN, JBHI, etc.
[go top]
Teaching Assistant
- Introduction to Java Programming, for undergraduate student. fall, 2016.
[go top]