Daizong Ding

529 citations

18 papers · 341 · h-index 8

Impact in

Signal Processing top 5%
- Advanced Malware Detection Techniques
- Time Series Analysis and Forecasting
Software top 10%
- Software Testing and Debugging Techniques

Papers in

Artificial Intelligence 10
- Anomaly Detection Techniques and Applications 4
- Advanced Graph Neural Networks 4
- Adversarial Robustness in Machine Learning 3
Information Systems 7
- Recommender Systems and Techniques 6

Co-authors: Mi Zhang (13 shared papers)Min Yang (8 shared papers)Xudong Pan (10 shared papers)Xiangnan He (4 shared papers)Yinzhi Cao (1 shared paper)Yukun Zhang (1 shared paper)Yuan Zhang (1 shared paper)Xiaohan Zhang (1 shared paper)
Journals: IEEE Transactions on Knowledge and Data Engineering (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Infoscience (Ecole Polytechnique Fédérale de Lausanne) (1 paper)2022 IEEE 38th International Conference on Data Engineering (ICDE) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)
Partner nations: China Singapore Switzerland

In The Last Decade

Daizong Ding

18 papers receiving 336 citations

Peers

Countries citing papers authored by Daizong Ding

Since Specialization

Citations

This map shows the geographic impact of Daizong Ding'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 Daizong Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daizong Ding more than expected).

Fields of papers citing papers by Daizong Ding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daizong Ding. 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 Daizong Ding. The network helps show where Daizong Ding may publish in the future.

Co-authors

The 21 scholars most cited alongside Daizong Ding, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daizong Ding Line = papers co-authored together Daizong Ding links everyone, so they are left out of the graph.

All Works

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18 of 18 papers shown

#	Work
1	Enhancing State-of-the-art Classifiers with API Semantics to Detect Evolved Android Malware Xiaohan Zhang, Yuan Zhang, Ming Zhong, Daizong Ding, Yinzhi Cao, Yukun Zhang, Mi Zhang, Min Yang	2020	120
2	Modeling Extreme Events in Time Series Prediction Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He	2019	92
3	BayDNN Daizong Ding, Mi Zhang, Shao-Yuan Li, Jie Tang, Xiaotie Chen, Zhi‐Hua Zhou	2017	38
4	Enhancing Time Series Predictors with Generalized Extreme Value Loss IEEE Transactions on Knowledge and Data Engineering ·Mi Zhang, Daizong Ding, Xudong Pan, Min Yang	2021	17
5	Geographical Feature Extraction for Entities in Location-based Social Networks Infoscience (Ecole Polytechnique Fédérale de Lausanne) ·Daizong Ding, Mi Zhang, Xudong Pan, Duocai Wu, Pearl Pu	2018	14
6	Learning to Learn the Future Xiaoyu You, Mi Zhang, Daizong Ding, Fuli Feng, Yuanmin Huang	2021	13
7	A Geometrical Perspective on Image Style Transfer with Adversarial Learning IEEE Transactions on Pattern Analysis and Machine Intelligence ·Xudong Pan, Mi Zhang, Daizong Ding, Min Yang	2020	8
8	Towards Backdoor Attack on Deep Learning based Time Series Classification 2022 IEEE 38th International Conference on Data Engineering (ICDE) ·Daizong Ding, Mi Zhang, Yuanmin Huang, Xudong Pan, Fuli Feng, Erling Jiang, Min Yang	2022	8
9	Black-Box Adversarial Attack on Time Series Classification Proceedings of the AAAI Conference on Artificial Intelligence ·Daizong Ding, Mi Zhang, Fuli Feng, Yuanmin Huang, Erling Jiang, Min Yang	2023	6
10	A user intention modeling algorithm for friend recommendation Xuchen Zhang, Daizong Ding, Chudi Huang	2017	5
11	A Deep Learning Framework for Self-evolving Hierarchical Community Detection Daizong Ding, Mi Zhang, Hanrui Wang, Xudong Pan, Min Yang, Xiangnan He	2021	5
12	MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding Xiaoyu You, Beina Sheng, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Fuli Feng	2023	5
13	Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model Xiaoyu You, Chi Li, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan, Min Yang	2023	3
14	Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning Proceedings of the AAAI Conference on Artificial Intelligence ·Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He	2020	2
15	Modeling Personalized Out-of-Town Distances in Location Recommendation Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He	2020	2
16	Uplift Modeling for Target User Attacks on Recommender Systems arXiv (Cornell University) ·Wenjie Wang, (unknown), Fuli Feng, Wentao Shi, Daizong Ding, Tat‐Seng Chua	2024	1
17	CausalPC: Improving the Robustness of Point Cloud Classification by Causal Effect Identification Yuanmin Huang, Mi Zhang, Daizong Ding, Erling Jiang, Zhaoxiang Wang, Min Yang	2024	1
18	CAP: Robust Point Cloud Classification via Semantic and Structural Modeling Daizong Ding, Erling Jiang, Yuanmin Huang, Mi Zhang, Wenxuan Li, Min Yang	2023	1

About Daizong Ding

Daizong Ding is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Management Science and Operations Research and Statistical and Nonlinear Physics, having authored 18 papers that have together received 341 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (6 papers), Anomaly Detection Techniques and Applications (4 papers), Advanced Graph Neural Networks (4 papers), Adversarial Robustness in Machine Learning (3 papers), Human Mobility and Location-Based Analysis (3 papers), Complex Network Analysis Techniques (3 papers), Energy Load and Power Forecasting (2 papers) and Stock Market Forecasting Methods (2 papers). The work is most often cited by research in Signal Processing (167 citations), Software (34 citations), Computer Networks and Communications (112 citations), Information Systems (103 citations) and Artificial Intelligence (145 citations). Daizong Ding has collaborated with scholars based in China, Singapore and Switzerland. Frequent co-authors include Mi Zhang, Min Yang, Xudong Pan, Xiangnan He, Yinzhi Cao, Yukun Zhang, Yuan Zhang, Xiaohan Zhang, Mi Zhang and Jie Tang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Pattern Analysis and Machine Intelligence, Infoscience (Ecole Polytechnique Fédérale de Lausanne), 2022 IEEE 38th International Conference on Data Engineering (ICDE) and Proceedings of the AAAI Conference on Artificial Intelligence.

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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