Faculty

Institution

Unit

Venue

Jing Yang

Associate Professor of Electrical and Computer Engineering Associate Professor of Computer Science by courtesy

University of Virginia

Affiliations

School of Engineering and Applied Science

Department of Electrical and Computer Engineering

Jing Yang is currently serving as an Electrical And Computer Engineering Associate Professor of Electrical and Computer Engineering Associate Professor of Computer Science by courtesy at University of Virginia.

Honors

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Experiences

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Education

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Jing Yang

University of Virginia

Associate Professor of Electrical and Computer Engineering Associate Professor of Computer Science by courtesy

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wireless communications computer science communications systems telecommunication networks systems engineering wireless networks energy-efficient networking energy harvesting networked system design data science wireless sensor networks transmission power control signal processing distributed systems computer engineering energy management mathematical optimization sensor optimization power delivery machine learning research computational optimization dynamic resource allocation channel capacity estimation exploration v exploitation optimal policy stochastic process energy monitoring information theory stochastic optimization online algorithms control optimization information fusion network optimization stochastic dynamics wireless personal communication smart grid communication engineering collaborative sensor network distributed learning energy harvesting sensor localization wireless sensor systems data communications federated learning erasure channel mobile computing markov decision process multi-terminal information theory lower bounds scheduling problems channel characterization scheduling (computing) optimal packet scheduling optimal packet multiple access channel status updating system reliability engineering system safety stochastic games queueing theory stochastic networks communication algorithm fading channels joint source-channel coding power-efficient computing distributed ai system energy harvesting source information minimization energy cooperation rechargeable transmitter finite batteries optimal status convergence rate aoi minimization energy efficiency tradeoff

Notable Scholarly Works

Notable Federal Grants

Collaborators

Hybrid Rl. UAI 2025 (2025)

Jing Yang

Leveraging Transformers for In-Context Spectrum Estimation. ISIT 2025 (2025)

Jing Yang

spectrum estimationspeaker localizationdata sciencesignal processingspeech processingin-context spectrum estimation

Robust Rl. IEEE Trans. on Information Theory (2025)

Jing Yang

Theoretical Study of Transformers. ICML 2025 (2025)

Jing Yang

power electronicsengineeringpower deliveryengineering scienceelectromagnetic fieldselectromagnetic compatibilityelectrical transmissionelectromagnetismtheoretical studyelectric power systemselectrical engineering

Transformers for Wireless Communications. IEEE GLOBECOM 2025 (2025)

Jing Yang

wireless personal communicationwireless power transmissionwireless modelingpower deliverywireless communicationscommunications systemselectromagnetic compatibilityantennaswireless networkstelecommunication networkselectrical engineering

Advancing Ran Slicing With Offline Reinforcement Learning. arXiv (Cornell University) (2024)

Kun YangShu-Ping YehMenglei ZhangJerry SydirJing YangCong Shen

offline reinforcement learningcomputer sciencemachine learningwireless communicationsprogram slicingreinforcement learning

Data-Adaptive Differentially Private Prompt Synthesis for In-Context Learning. arXiv (Cornell University) (2024)

Gao, FengyuZhou, RuidaWang, TianhaoShen, CongYang, Jing

private prompt synthesisdata privacyin-context learningdata sciencedifferential privacy

Federated Representation Learning in the Under-Parameterized Regime. arXiv (Cornell University) (2024)

Liu, RenpuShen, CongYang, Jing

deep learningmachine learningnatural language processingfederated learningsupervised learningapplied mathematicsincremental learningunder-parameterized regime

Non-Asymptotic Convergence of Training Transformers for Next-Token Prediction. arXiv (Cornell University) (2024)

Huang, RuiquanLiang, YingbinYang, Jing

computer sciencenext-token predictionmachine learningtraining transformersnon-asymptotic convergence

Offline Reinforcement Learning for Wireless Network Optimization With Mixture Datasets. IEEE Transactions on Wireless Communications (2024)

Kun YangChengshuai ShiCong ShenJing YangShu-Ping YehJaroslaw J. Sydir

computer sciencemixture datasetsmachine learningreinforcement learningbenchmark datasetselectrical engineeringwireless network optimization

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Jing Yang

Associate Professor of Electrical and Computer Engineering Associate Professor of Computer Science by courtesy

University of Virginia

Affiliations

School of Engineering and Applied Science

Department of Electrical and Computer Engineering

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Jing Yang

University of Virginia

Associate Professor of Electrical and Computer Engineering Associate Professor of Computer Science by courtesy

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Hybrid Rl. UAI 2025 (2025)

Jing Yang

Leveraging Transformers for In-Context Spectrum Estimation. ISIT 2025 (2025)

Jing Yang

spectrum estimationspeaker localizationdata sciencesignal processingspeech processingin-context spectrum estimation

Robust Rl. IEEE Trans. on Information Theory (2025)

Jing Yang

Theoretical Study of Transformers. ICML 2025 (2025)

Jing Yang

Transformers for Wireless Communications. IEEE GLOBECOM 2025 (2025)

Jing Yang

Advancing Ran Slicing With Offline Reinforcement Learning. arXiv (Cornell University) (2024)

Kun YangShu-Ping YehMenglei ZhangJerry SydirJing YangCong Shen

offline reinforcement learningcomputer sciencemachine learningwireless communicationsprogram slicingreinforcement learning

Data-Adaptive Differentially Private Prompt Synthesis for In-Context Learning. arXiv (Cornell University) (2024)

Gao, FengyuZhou, RuidaWang, TianhaoShen, CongYang, Jing

private prompt synthesisdata privacyin-context learningdata sciencedifferential privacy

Federated Representation Learning in the Under-Parameterized Regime. arXiv (Cornell University) (2024)

Liu, RenpuShen, CongYang, Jing

deep learningmachine learningnatural language processingfederated learningsupervised learningapplied mathematicsincremental learningunder-parameterized regime

Non-Asymptotic Convergence of Training Transformers for Next-Token Prediction. arXiv (Cornell University) (2024)

Huang, RuiquanLiang, YingbinYang, Jing

computer sciencenext-token predictionmachine learningtraining transformersnon-asymptotic convergence

Offline Reinforcement Learning for Wireless Network Optimization With Mixture Datasets. IEEE Transactions on Wireless Communications (2024)

Kun YangChengshuai ShiCong ShenJing YangShu-Ping YehJaroslaw J. Sydir

computer sciencemixture datasetsmachine learningreinforcement learningbenchmark datasetselectrical engineeringwireless network optimization

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Cong Shen

Institution

University of Virginia

wireless networks

signal processing

Tianyi Chen

Institution

Rensselaer Polytechnic Institute

computer science

signal processing

Ali Tajer

Institution

Rensselaer Polytechnic Institute

signal processing

statistical pattern recognition

Gauri Joshi

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Atilla Eryilmaz

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wireless communications

electrical engineering

Jingxian Wu

Institution

University of Arkansas

big data analytics

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Sanjay Shakkottai

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University of Texas at Austin

intelligent network

wireless communication

Wendi Heinzelman

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University of Rochester

heterogeneous network

sensor suite

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Cornell University

strategy

electronic auction

Qilian Liang

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electrical engineering

computer science