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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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About Me
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Posts
These tools are all you need for your PhD!
Published:
As a PhD student, you are learning cutting-edge techniques. In the future, you will prepare to showcase your impressive work to audiences in your field. To excel in this role, a PhD student needs the best tools. This post will introduce the professional tools that current STEM PhD students use to complete their projects, write their papers, and demonstrate their results.
portfolio
Portfolio item number 1
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Portfolio item number 2
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publications
Stability analysis of nonlinear oscillator networks based on the mechanism of cascading failures
Published in Chaos, Solitons & Fractals, 2019
Complex networks; Power grid
Recommended citation: Huang Y, Dong H, Zhang W, et al. Stability analysis of nonlinear oscillator networks based on the mechanism of cascading failures[J]. Chaos, Solitons & Fractals, 2019, 128: 5-15. https://www.sciencedirect.com/science/article/pii/S0960077919302826
Comprehensive identification and isolation policies have effectively suppressed the spread of COVID-19
Published in Chaos, Solitons & Fractals, 2020
Virus spread; Complex networks
Recommended citation: Huang Y, Wu Y, Zhang W. Comprehensive identification and isolation policies have effectively suppressed the spread of COVID-19[J]. Chaos, Solitons & Fractals, 2020, 139: 110041. https://www.sciencedirect.com/science/article/pii/S0960077920304392
Soft policy optimization using dual-track advantage estimator
Published in IEEE International Conference on Data Mining (ICDM), 2020
Reinforcement learning
Recommended citation: Huang Y, Wang X, Zou L, et al. Soft policy optimization using dual-track advantage estimator[C]//2020 IEEE International Conference on Data Mining (ICDM). IEEE, 2020: 1064-1069. https://ieeexplore.ieee.org/abstract/document/9338396
Multi-agent reinforcement learning control of a hydrostatic wind turbine-based farm
Published in IEEE Transactions on Sustainable Energy, 2023
Reinforcement learning; Wind Farm Control
Recommended citation: Huang Y, Lin S, Zhao X. Multi-agent reinforcement learning control of a hydrostatic wind turbine-based farm[J]. IEEE Transactions on Sustainable Energy, 2023. https://ieeexplore.ieee.org/abstract/document/10109125
Reinforcement learning-based multi-objective control of grid-connected wind farms
Published in IEEE Transactions on Industrial Informatics, 2024
Reinforcement learning; Wind Farm Control
Recommended citation: Huang Y, Zhao X. Reinforcement Learning-Based Multiobjective Control of Grid-Connected Wind Farms[J]. IEEE Transactions on Industrial Informatics, 2024. https://ieeexplore.ieee.org/abstract/document/10436393
Wind Farm Control via Offline Reinforcement Learning with Adversarial Training
Published in IEEE Transactions on Automation Science and Engineering, 2025
Reinforcement learning; Wind Farm Control
Recommended citation: Huang Y, Zhao X. Wind Farm Control via Offline Reinforcement Learning with Adversarial Training[J]. IEEE Transactions on Automation Science and Engineering, 2025. https://ieeexplore.ieee.org/abstract/document/10912435
talks
DeepWake: Deep learning for wind farm wake modelling
Published:
In this meeting, I have introduced our lastest study in wind energy, DeepWake. DeepWake means that we use physics-informed deep learning to train a wind farm wake model. Additionally, we also expect to deeply reveal the wake generated by wind turbines using this model.
CuWind – CUDA (GPU)-Based High-Fidelity Wind Farm Simulator
Published:
In this workshop, I have introduced how to use CUDA to complete the Wind Farm Simulation to our collaborators with GE.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.