Ting Dai

12 papers and 101 indexed citations i.

About

Ting Dai is a scholar working on Artificial Intelligence, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Ting Dai has authored 12 papers receiving a total of 101 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 2 papers in Signal Processing. Recurrent topics in Ting Dai’s work include Adversarial Robustness in Machine Learning (5 papers), Security in Wireless Sensor Networks (3 papers) and Machine Learning and Algorithms (2 papers). Ting Dai is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), Security in Wireless Sensor Networks (3 papers) and Machine Learning and Algorithms (2 papers). Ting Dai collaborates with scholars based in China, Singapore and United States. Ting Dai's co-authors include Jun Sun, Xinyu Wang, Jingyi Wang, Jin Song Dong, Peixin Zhang, Xingen Wang, Haiping Huang, Jianye Hao, Shuang Liu and Yang Zhang and has published in prestigious journals such as Environmental Science and Pollution Research, IEEE Transactions on Software Engineering and IEEE Transactions on Parallel and Distributed Systems.

In The Last Decade

Co-authorship network of co-authors of Ting Dai i

Fields of papers citing papers by Ting Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Ting Dai

Since Specialization
Citations

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

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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2025