Zheda Mai

1.0k total citations · 1 hit paper
15 papers, 549 citations indexed

About

Zheda Mai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Zheda Mai has authored 15 papers receiving a total of 549 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 3 papers in Information Systems. Recurrent topics in Zheda Mai's work include Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Recommender Systems and Techniques (3 papers). Zheda Mai is often cited by papers focused on Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Recommender Systems and Techniques (3 papers). Zheda Mai collaborates with scholars based in Canada, United States and Australia. Zheda Mai's co-authors include Scott Sanner, Hyunwoo Kim, Ruiwen Li, Jihwan Jeong, Jongseong Jang, Zhibo Zhang, Wei‐Lun Chao, Mohamed Reda Bouadjenek, Zhaolin Gao and M. Caccia and has published in prestigious journals such as Neurocomputing, Information Processing & Management and Journal of Visual Communication and Image Representation.

In The Last Decade

Zheda Mai

10 papers receiving 542 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Online continual learning in image classification: An empirical survey

2021 229 citations Zheda Mai, Ruiwen Li et al. Neurocomputing profile →

Peers

Zheda Mai

AI

CVPR

RNMI

IS

MT

Ruiwen Li China

Massimiliano Mancini Italy

Jihwan Jeong South Korea

Songlin Dong China

Da-Wei Zhou China

Xinyuan Chang China

Ruoxi Sun China

Ji Wan China

Haifeng Xia United States

Ruiwen Li China

Zheda Mai

299 ×0.7

AI

195 ×0.7

CVPR

38 ×0.7

RNMI

17 ×0.5

IS

23 ×0.8

MT

Citations per year, relative to Zheda Mai Zheda Mai (= 1×) peers Ruiwen Li

Countries citing papers authored by Zheda Mai

Since Specialization

Citations

This map shows the geographic impact of Zheda Mai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zheda Mai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zheda Mai more than expected).

Fields of papers citing papers by Zheda Mai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zheda Mai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zheda Mai. The network helps show where Zheda Mai may publish in the future.

Co-authorship network of co-authors of Zheda Mai

This figure shows the co-authorship network connecting the top 25 collaborators of Zheda Mai. A scholar is included among the top collaborators of Zheda Mai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zheda Mai. Zheda Mai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

1.

Zhang, Ziheng, et al.. (2025). Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation. 9611–9620. 2 indexed citations

2.

Mai, Zheda, et al.. (2025). Attention-Driven Causal Discovery: From Transformer Matrices to Granger Causal Graphs for Non-Stationary Time-series Data. 1–5.

3.

Mai, Zheda, Jianyang Gu, Ziheng Zhang, et al.. (2025). Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis. 4375–4385.

4.

Mai, Zheda, et al.. (2025). Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition. 14845–14857. 1 indexed citations

5.

Berger‐Wolf, Tanya, Wei‐Lun Chao, Song Gao, et al.. (2024). Fine-Tuning is Fine, if Calibrated. 136084–136119.

6.

Li, Ruiwen, Zheda Mai, Zhibo Zhang, Jongseong Jang, & Scott Sanner. (2023). TransCAM: Transformer attention-based CAM refinement for Weakly supervised semantic segmentation. Journal of Visual Communication and Image Representation. 92. 103800–103800. 41 indexed citations

7.

Mai, Zheda, et al.. (2023). Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. 7725–7735. 20 indexed citations

8.

Lomonaco, Vincenzo, Lorenzo Pellegrini, Pau Rodríguez, et al.. (2022). CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions. CINECA IRIS Institutial research information system (University of Pisa). 23 indexed citations

9.

Bouadjenek, Mohamed Reda, et al.. (2022). Towards understanding and mitigating unintended biases in language model-driven conversational recommendation. Information Processing & Management. 60(1). 103139–103139. 22 indexed citations

10.

Mai, Zheda, et al.. (2022). Distributional Contrastive Embedding for Clarification-based Conversational Critiquing. Proceedings of the ACM Web Conference 2022. 2422–2432. 1 indexed citations

11.

Gao, Zhaolin, et al.. (2022). Mitigating the Filter Bubble While Maintaining Relevance. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2524–2531. 15 indexed citations

12.

Mai, Zheda, et al.. (2021). Online Class-Incremental Continual Learning with Adversarial Shapley Value. Proceedings of the AAAI Conference on Artificial Intelligence. 35(11). 9630–9638. 99 indexed citations

13.

Mai, Zheda, et al.. (2021). Online continual learning in image classification: An empirical survey. Neurocomputing. 469. 28–51. 229 indexed citations breakdown →

14.

Mai, Zheda, Ruiwen Li, Hyunwoo Kim, & Scott Sanner. (2021). Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning. 3584–3594. 96 indexed citations

15.

Mai, Zheda, Ga Wu, Kai Luo, & Scott Sanner. (2020). Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. 165–172.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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