Caiwen Ding

3.2k total citations
117 papers, 1.8k citations indexed

About

Caiwen Ding is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Caiwen Ding has authored 117 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 55 papers in Computer Vision and Pattern Recognition and 51 papers in Electrical and Electronic Engineering. Recurrent topics in Caiwen Ding's work include Advanced Neural Network Applications (42 papers), Advanced Memory and Neural Computing (33 papers) and Adversarial Robustness in Machine Learning (14 papers). Caiwen Ding is often cited by papers focused on Advanced Neural Network Applications (42 papers), Advanced Memory and Neural Computing (33 papers) and Adversarial Robustness in Machine Learning (14 papers). Caiwen Ding collaborates with scholars based in United States, Mexico and China. Caiwen Ding's co-authors include Yanzhi Wang, Qinru Qiu, Bo Yuan, Zhe Li, Ao Ren, Xuehai Qian, Ji Li, Yun Liang, Ning Liu and Weiwen Jiang and has published in prestigious journals such as Scientific Reports, Nutrients and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Caiwen Ding

110 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Caiwen Ding United States 22 833 782 617 347 219 117 1.8k
Kaisheng Ma China 25 639 0.8× 1.2k 1.6× 796 1.3× 322 0.9× 354 1.6× 83 2.5k
Li Jiang China 21 366 0.4× 1.3k 1.6× 296 0.5× 277 0.8× 374 1.7× 162 1.8k
Ang Li United States 26 823 1.0× 467 0.6× 528 0.9× 508 1.5× 675 3.1× 155 2.0k
Janardhan Rao Doppa United States 23 472 0.6× 600 0.8× 343 0.6× 402 1.2× 237 1.1× 132 1.4k
Theocharis Theocharides Cyprus 24 349 0.4× 934 1.2× 881 1.4× 905 2.6× 454 2.1× 128 2.3k
Ninghui Sun China 15 485 0.6× 711 0.9× 804 1.3× 528 1.5× 665 3.0× 63 1.7k
Bingjun Xiao United States 12 505 0.6× 1.2k 1.5× 1.0k 1.6× 269 0.8× 497 2.3× 18 1.9k
Seyed-Mohsen Moosavi-Dezfooli Switzerland 12 2.9k 3.4× 399 0.5× 896 1.5× 224 0.6× 204 0.9× 19 3.3k
Cong Xu China 19 724 0.9× 2.2k 2.8× 658 1.1× 558 1.6× 457 2.1× 47 3.0k

Countries citing papers authored by Caiwen Ding

Since Specialization
Citations

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

Fields of papers citing papers by Caiwen Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Caiwen Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Caiwen Ding. A scholar is included among the top collaborators of Caiwen Ding 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 Caiwen Ding. Caiwen Ding is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Chen, Zhutian, et al.. (2025). HiVeGen – Hierarchical LLM-based Verilog Generation for Scalable Chip Design. 30–36. 2 indexed citations
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Xie, Mimi, et al.. (2024). Developing an eco-driving strategy in a hybrid traffic network using reinforcement learning. Science Progress. 107(3). 342233902–342233902. 5 indexed citations
6.
Li, Zhengang, Alec Lu, Zhenglun Kong, et al.. (2024). Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. 324–337. 3 indexed citations
7.
Ding, Caiwen, et al.. (2024). Performance Improvement of Degrading Memristor-Bridge-Based Multilayer Neural Network with Refresh Pulses. International Journal of High Speed Electronics and Systems. 33(02n03).
8.
Chen, Wei‐Ying, Brian Hutchinson, Qian Yang, et al.. (2023). Deep Learning for Automated Quantification of Irradiation Defects in TEM Data: Relating Pixel-level Errors to Defect Properties. Microscopy and Microanalysis. 29(Supplement_1). 1559–1560. 1 indexed citations
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Li, Yingjie, Minhan Lou, Weilu Gao, et al.. (2023). Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. 85. 1–6. 1 indexed citations
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Wang, Yijue, Nuo Xu, Kaleel Mahmood, et al.. (2022). Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. 2022 IEEE International Conference on Big Data (Big Data). 1 indexed citations
11.
Wang, Yijue, Chenghong Wang, Hang Liu, et al.. (2022). Variance of the Gradient Also Matters: Privacy Leakage from Gradients. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8. 2 indexed citations
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Chen, Wei‐Ying, et al.. (2022). DefectTrack: a deep learning-based multi-object tracking algorithm for quantitative defect analysis of in-situ TEM videos in real-time. Scientific Reports. 12(1). 15705–15705. 19 indexed citations
13.
Peng, Hongwu, Tong Geng, Ang Li, et al.. (2021). Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. 142–148. 77 indexed citations
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Xie, Mimi, et al.. (2021). An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving. 122–128. 16 indexed citations
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Chen, Shiyang, Hongwu Peng, Zhenglun Kong, et al.. (2021). HMC-T RAN. 169–174. 4 indexed citations
16.
Xu, Kaidi, Sijia Liu, Pin‐Yu Chen, et al.. (2020). Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 8479–8483. 4 indexed citations
17.
Li, Bingbing, Zhenglun Kong, Tianyun Zhang, et al.. (2020). Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. 3187–3199. 26 indexed citations
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Li, Bingbing, et al.. (2020). An Efficient Deep Reinforcement Learning Framework for UAVs. 323–328. 13 indexed citations
19.
Li, Zhe, Ji Li, Ao Ren, et al.. (2018). HEIF: Highly Efficient Stochastic Computing-Based Inference Framework for Deep Neural Networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 38(8). 1543–1556. 67 indexed citations
20.
Kim, Jaemin, Donkyu Baek, Caiwen Ding, et al.. (2018). Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 26(7). 1241–1253. 12 indexed citations

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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