YIN,Feng

Labs

YIN,Feng
Title:

Assistant Professor

Education Background:
Ph.D. in Electrical Engineering (summa cum laude)
Signal Processing Group, Technische Universität Darmstadt, Germany. 2011-2014

M.Sc. in Electrical Engineering
Technische Universität Darmstadt, Germany. 2008-2011

B.Sc. in Electrical Engineering
Shanghai Jiao Tong University, Shanghai, China. 2004-2008
Office Address

Room 205, Dao Yuan Bldg.

Lab info

Labs info

1.Post-doc

(1).KONG, Qinglei.

    2019.11-Present

     Research Interests: Privacy preservation, Blockchain, VANET security.

    Description: I focused on the privacy-preserving vehicular networks, and I designed a few secure data processing mechanisms in vehicular blockchain and vehicular federated learning. My research works have achieved the secure data aggregation and acquisition in vehicular cloud with dynamic topology and stringent delay requirement, and they have improved the computation and communication efficiency of vehicular data processing. 

     Email: kongqinglei@cuhk.edu.cn

2.Ph.D Students

(1).ZHANG, Tianjian.

     Fall 2018-Present

     Research Interests: Explainable Machine Learning, Causal Discovery, Causal Inference and their Applications.

     Email: tianjianzhang@link.cuhk.edu.cn

(2).DAI, Yijue

     Fall 2018-Present

    Research Interests: Gaussian process, Kernel inference, Machine learning.

     Description: Mainly focus on kernel function learning with respect to data efficiency, interpretability, scalability and optimality. 

     Representative Publication: Dai, Yijue, et al. "An Interpretable and Sample Efficient Deep Kernel for Gaussian Process." Conference on Uncertainty in Artificial Intelligence.PMLR, 2020.

     Email: 218019041@link.cuhk.edu.cn

(3).ZHANG, Ceyao

    Spring 2019-Present

     Research Interests: Meta-learning, Reinforcement learning, Gaussian Process.

     Description: I have joined the work of Exact O(N2) Hyper-Parameter Optimization for Gaussian Process Regression, which helped me open the door to Gaussian Process and Bayesian Learning. Now I am interersted in reinforcement learning and meta-learning, and I am trying to leverage meta-learning to improve the sample efficiency of reinforcement learning. 

     Email: 218019058@link.cuhk.edu.cn

(4).GAO, Jun

     Fall 2019-Present

     Research Interests: Meta-learning, Wireless localization.

     Description: Machine learning technology can model the uncertain behaviors of wireless signals in the environment. However, existing methods are much sensitive and time-consuming to changes in the environments. My research focuses on a fast adaptive and cost-effective fingerprint-based localization system based on few-shot meta-learning. 

     Email: 219019052@link.cuhk.edu.cn

(5).LIN, Zhidi

     Fall 2019-Present

     Research Interests: Nonlinear state space model, Bayesian learning and inference, Distributed algorithms.

     Email: zhidilin@link.cuhk.edu.cn

(6).YAN, Wenzhong

    Spring 2020-Present

     Research Interests: Graph neural networks, Signal processing

     Description: My research topic is dynamic graphneural networks for large scale spatio-temporal data modeling. I mainly focus on two related applications: 1) multi-agents localization and tracking and 2) wireless traffic prediction in temporal networks.

     Email: 219019024@link.cuhk.edu.cn

3.Mphil Students

(1).ZHANG, Xinyi

     Fall 2020-Present

     Research Interests:

     Email:220019018@link.cuhk.edu.cn

(2).ZHANG, Yuanhang

     Fall 2020-Present

     Research Interests: State-space model based on deep neural networks

     Description: Research on non-linear state-space model whose transition and emission function are modeled by deep learning algorithm, variational learning and LSTM for instance. 

    Email:220019088@link.cuhk.edu.cn

(3).QU, Xiaodong

     Fall 2020-Present

     Research Interests: Privacy preservation, Vehicle-to-grid integrates electric grid with transportation systems.

     Description: Vehicle-to-grid integrates electric grid with transportations systems, which incur security and privacy challenges which affect the practical use. Therefore, privacy-preserving mechanisms based on the vehicle-to-grid system are needed.

     Email: 220019089@link.cuhk.edu.cn