Publication

Conference Papers

1. Stochastic Battery Operations using Deep Neural Networks

Yize Chen, Md Umar Hashmi and Deepjyoti Deka, submitted

2. IntelligentCrowd: Mobile Crowdsensing via Multi-agent Reinforcement Learning

Yize Chen and Hao Wang, accepted to International Conference on Computing, Networking and Communications (ICNC 2019)

3. Is Machine Learning in Power Systems Vulnerable?

Yize Chen, Yushi Tan and Deepjyoti Deka, accepted to IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) 2018, Workshop on AI in Energy Systems [Preprint][Code]

4.Optimal Control Via Neural Networks: A Convex Approach

Yize Chen*, Yuanyuan Shi* and Baosen Zhang, Submitted [Preprint]

5.Bayesian Renewables Scenario Generation via Deep Generative Networks

Yize Chen, Pan Li and Baosen Zhang, accepted to Conference on Information Sciences and Systems (CISS)  2018 [PDF]

6.An Unsupervised Deep Learning Approach for Scenario Forecasts

Yize Chen, Xiyu Wang and Baosen Zhang, accepted to Power Systems Computation Conference  (PSCC 2018) [PDF]

7. Towards Trusted Social Networks with Blockchain Technology

Yize Chen, Quanlai Li and Hao Wang, accepted to Symposium on Foundations and Applications of Blockchain (FAB 2018) [PDF]

8.Modeling and Optimization of Complex Building Energy Systems with Deep Neural Networks

Yize Chen, Yuanyuan Shi and Baosen Zhang, Accpeted to Asilomar Conference on Signals, Systems and Computers (Asilomar 2017) [PDF]

9.Blocking Transferability of Adversarial Examples in Black-Box Learning
Systems

Hossein Hosseini, Yize Chen, Sreeram Kannan, Baosen Zhang and Radha Poovendran, Submitted to IEEE Winter Conf. on Applications of Computer Vision (WACV 2018) [PDF]

Jounal Papers

1.Non-Wire Alternatives: a Robust Approach

Jesus E. Contreras-Ocana, Yize Chen, Uzma Siddiqi and Baosen Zhang, Submitted to IEEE Transactions on Power Systems

2.Link Prediction through Deep Learning

Xu-wen Wang, Yize Chen, and Yang-Yu Liu, Submitted [Preprint]

3.Model-Free Renewables Scenario Generation Using Generative Adversarial
Networks

Yize Chen, Yishen Wang, Daniel Kirschen and Baosen Zhang, Accepted to IEEE Transactions on Power Systems [PDF] [Code] [Poster]

4.Revealing Complex Ecological Dynamics via Symbolic Regression

Yize Chen, Marco Tulio Angulo and Yang-Yu Liu, Submitted to Nature Communications [Preprint]

Presentations

1.Modeling and Optimization of Complex Building Energy Systems with Recurrent Neural Networks, invited talk, INFORMS Annual Meeting, October 2017, Houston, TX [Slides]

2. Optimal Control via Neural Networks, invited talk, Center for Nonlinear Studies of Los Alamos National Laboratory, August 2018, Los Alamos, NM

3. Renewable Scenario Generation Using Adversarial Networks, invited talk, INFORMS Annual Meeting, November 2018, Phoenix, AZ