Gang Wang

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Research activity per year

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

SDG 7 Affordable and Clean Energy

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Dive into the research topics where Gang Wang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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AdaDQ-KD: An Adaptive Dithering Quantization with Knowledge Distillation in Privacy-Preserving Federated Learning
Wang, G., Qi, Q., Yu, H., Han, R., Bai, L. & Choi, J., 2026, (Accepted/In press) In: IEEE Transactions on Vehicular Technology.
Research output: Contribution to journal › Article › peer-review
Toward Trusted 6G Mobile Edge Computing: A Secure Batch Large Language Models Deployment Framework
Sun, Y., Liu, J., Xiong, G., Song, Q., Liu, J., Wang, G. & Wang, R., 2026, In: IEEE Transactions on Mobile Computing. 25, 3, p. 3328-3346 19 p.
Research output: Contribution to journal › Article › peer-review
2 Link opens in a new tab Scopus citations
Multiple Aircraft Trajectory Prediction Based on Bayesian Social LSTM
Zhong, X., Cai, K., Wang, G. & Zhao, P., 2025, AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025. American Institute of Aeronautics and Astronautics Inc, AIAA, (AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
3 Link opens in a new tab Scopus citations
Efficient Federated Learning via Joint Communication and Computation Optimization
Wang, G., Zhao, C., Qi, Q., Han, R., Bai, L. & Choi, J., 2024, In: IEEE Transactions on Vehicular Technology. 73, 8, p. 11580-11592 13 p.
Research output: Contribution to journal › Article › peer-review

Open Access
9 Link opens in a new tab Scopus citations
P2CEFL: Privacy-Preserving and Communication Efficient Federated Learning With Sparse Gradient and Dithering Quantization
Wang, G., Qi, Q., Han, R., Bai, L. & Choi, J., 2024, In: IEEE Transactions on Mobile Computing. 23, 12, p. 14722-14736 15 p.
Research output: Contribution to journal › Article › peer-review
4 Link opens in a new tab Scopus citations

Gang Wang

Personal profile

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

AdaDQ-KD: An Adaptive Dithering Quantization with Knowledge Distillation in Privacy-Preserving Federated Learning

Toward Trusted 6G Mobile Edge Computing: A Secure Batch Large Language Models Deployment Framework

Multiple Aircraft Trajectory Prediction Based on Bayesian Social LSTM

Efficient Federated Learning via Joint Communication and Computation Optimization

P2CEFL: Privacy-Preserving and Communication Efficient Federated Learning With Sparse Gradient and Dithering Quantization

Gang Wang

Personal profile

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Research output

AdaDQ-KD: An Adaptive Dithering Quantization with Knowledge Distillation in Privacy-Preserving Federated Learning

Toward Trusted 6G Mobile Edge Computing: A Secure Batch Large Language Models Deployment Framework

Multiple Aircraft Trajectory Prediction Based on Bayesian Social LSTM

Efficient Federated Learning via Joint Communication and Computation Optimization

P2CEFL: Privacy-Preserving and Communication Efficient Federated Learning With Sparse Gradient and Dithering Quantization