职务/职称
信息系统大数据实验室研究科学家
研究方向
凸优化算法，深度学习算法，通信与雷达信号处理算法
电子邮箱
zhaolicheng@sribd.cn
教育背景
香港科技大学博士
东南大学学士
个人介绍
赵立成于2014年获得东南大学信息工程学士学位，于2018年获得香港科技大学电子与计算机工程博士学位。在博士期间以第一作者发表五篇期刊文章，刊于IEEE Transactions on Signal Processing。自2018年至2021年，在京东担任算法工程师，负责推荐系统的构建与优化，有丰富的深度学习实践落地经验。目前赵立成博士被深圳市认定为海外高层次C类人才，其研究方向包括凸优化算法，深度学习算法，通信与雷达信号处理算法等。
职务/职称
信息系统大数据实验室研究科学家
研究方向
凸优化算法，深度学习算法，通信与雷达信号处理算法
电子邮箱
zhaolicheng@sribd.cn
教育背景
香港科技大学博士
东南大学学士
个人介绍
赵立成于2014年获得东南大学信息工程学士学位，于2018年获得香港科技大学电子与计算机工程博士学位。在博士期间以第一作者发表五篇期刊文章，刊于IEEE Transactions on Signal Processing。自2018年至2021年，在京东担任算法工程师，负责推荐系统的构建与优化，有丰富的深度学习实践落地经验。目前赵立成博士被深圳市认定为海外高层次C类人才，其研究方向包括凸优化算法，深度学习算法，通信与雷达信号处理算法等。
职务/职称
信息系统大数据实验室研究科学家
研究方向
凸优化算法，深度学习算法，通信与雷达信号处理算法
电子邮箱
zhaolicheng@sribd.cn
教育背景
香港科技大学博士
东南大学学士
个人介绍
赵立成于2014年获得东南大学信息工程学士学位，于2018年获得香港科技大学电子与计算机工程博士学位。在博士期间以第一作者发表五篇期刊文章，刊于IEEE Transactions on Signal Processing。自2018年至2021年，在京东担任算法工程师，负责推荐系统的构建与优化，有丰富的深度学习实践落地经验。目前赵立成博士被深圳市认定为海外高层次C类人才，其研究方向包括凸优化算法，深度学习算法，通信与雷达信号处理算法等。
职务/职称
研究科学家
研究方向
强化学习、智能楼宇，博弈论与网络优化
电子邮箱
zhangliangshuxue@gmail.com
教育背景
华中科技大学，学士， 2011
香港理工大学， 博士， 2016
主要成果/荣誉
国际会议Buildsys 2014的最佳论文奖
深圳市海外高层次人才(C类)
个人介绍
2017-2022年先后入职京东和腾讯，发表在KDD、SIGIR等多项强化学习决策研究成果在京东商业广告和腾讯王者荣耀上线应用，谷歌引用量1100+。后加入鹏城实验室，担任副研究员。主要研究方向: 强化学习，智能楼宇，博弈论与网络优化等。
代表性论文
博弈论与网络优化
1,Y. Zhao, H. Wang, H. Su, L. Zhang, R. Zhang, D. Wang, K. Xu,“Understand love of variety in wireless data market under sponsored data plans”,IEEE JSAC 2020 (CCF-A)
2,Y. Zhao, H, Su, L. Zhang, D. Wang, K. Xu, "Variety Matters: A New Model for the Wireless Data Market under Sponsored Data Plans", in Proc. of IEEE/ACM IWQoS 2019. (CCF-B)
3, Liang Zhang, Weijie Wu and Dan Wang, "TDS: Time-Dependent Sponsored Data Plan for Wireless Data Traffic Market", in Proc. of IEEE INFOCOM 2016. (CCF-A)
4, Liang Zhang, Weijie Wu and Dan Wang,"Sponsored Data Plan: A Two-Class Service Model in Wireless Data Networks", in Proc. of ACM SIGMETRICS 2015. (CCF-B, CORE* A)
5, Liang Zhang, Weijie Wu and Dan Wang, "Time Dependent Pricing in Wireless Data Networks: Flat-rates vs. Usage-based Schemes", in Proc. of IEEE INFOCOM, 2014 (CCF-A)
绿色智能楼宇
6, Z Zheng, F Wang, D Wang, L Zhang, "An Urban Mobility Model with Buildings Involved:
Bridging Theory to Practice", ACM TOSN 2020 (CCF-B)
7,Z. Zheng, F. Wang, D. Wang, and L. Zhang, "Buildings affect Mobile Pattens: Developing a new Urban Mobility Model", in Proc. of ACM Buildsys’18 (Best Paper Award)
8,L. Zhang, A. H. Lam and D. Wang, "Strategy proof Thermal Comfort Voting in Buildings,
in Proc. of ACM BuildSys’14
强化学习以及应用
9, D. Zhao, L. Zhang*, B. Zhang, L. Zheng, Y. Bao, W. Yan, "MaHRL: Multi-goals Abstraction based Deep Hierarchical Reinforcement Learning for Recommendations", in Proc. of ACM SIGIR 2020 (CCF-A)
10, Y. Su, L. Zhang*, Q. Dai, B. Zhang, J. Yan, S. Xu, D. Wang, Y. He, Y. Bao, and W. Yan, "An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration", in Proc. of IJCAI 2020 (CCF-A)
11, Y. Wang, L. Zhang(co-first author), Q. Dai, F. Sun, B. Zhang, Y. He, Y. Bao and W. Yan , "Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction", in Proc. of ACM CIKM 2019 (CCF-B)
12, X. Zhao, L. Xia, L. Zhang, Z. Ding, D. Yin, J. Tang, "Deep Reinforcement Learning for Page-wise Recommendations", in Proc. of ACM RecSys 2018 (CCF-B，高引论文270+)
13, X. Zhao, L. Zhang, Z. Ding, L. Xia, J. Tang, and D. Yin. "Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning". in Proc. of ACM SIGKDD 2018. (CCF-A，高引论文280+)
14,W. Lu, F. Chung, K. Lai, L. Zhang,"Recommender system based on scarce information mining", Neural Networks, 2017 (CCF-B)
15, Q Dai, X Shen, Z Zheng, L Zhang, Q Li, D Wang, "Adversarial training regularization for negative sampling based network embedding", Information Sciences 2021 (CCF-B)
16, Q. Dai, X. Shen, L. Zhang, Q. Li, D. Wang, "Adversarial Training Methods for Network Embedding", in Proc. of ACM WWW 2019 (CCF-A)
职务/职称
研究科学家
研究方向
强化学习、智能楼宇，博弈论与网络优化
电子邮箱
zhangliangshuxue@gmail.com
教育背景
华中科技大学，学士， 2011
香港理工大学， 博士， 2016
主要成果/荣誉
国际会议Buildsys 2014的最佳论文奖
深圳市海外高层次人才(C类)
个人介绍
2017-2022年先后入职京东和腾讯，发表在KDD、SIGIR等多项强化学习决策研究成果在京东商业广告和腾讯王者荣耀上线应用，谷歌引用量1100+。后加入鹏城实验室，担任副研究员。主要研究方向: 强化学习，智能楼宇，博弈论与网络优化等。
代表性论文
博弈论与网络优化
1,Y. Zhao, H. Wang, H. Su, L. Zhang, R. Zhang, D. Wang, K. Xu,“Understand love of variety in wireless data market under sponsored data plans”,IEEE JSAC 2020 (CCF-A)
2,Y. Zhao, H, Su, L. Zhang, D. Wang, K. Xu, "Variety Matters: A New Model for the Wireless Data Market under Sponsored Data Plans", in Proc. of IEEE/ACM IWQoS 2019. (CCF-B)
3, Liang Zhang, Weijie Wu and Dan Wang, "TDS: Time-Dependent Sponsored Data Plan for Wireless Data Traffic Market", in Proc. of IEEE INFOCOM 2016. (CCF-A)
4, Liang Zhang, Weijie Wu and Dan Wang,"Sponsored Data Plan: A Two-Class Service Model in Wireless Data Networks", in Proc. of ACM SIGMETRICS 2015. (CCF-B, CORE* A)
5, Liang Zhang, Weijie Wu and Dan Wang, "Time Dependent Pricing in Wireless Data Networks: Flat-rates vs. Usage-based Schemes", in Proc. of IEEE INFOCOM, 2014 (CCF-A)
绿色智能楼宇
6, Z Zheng, F Wang, D Wang, L Zhang, "An Urban Mobility Model with Buildings Involved:
Bridging Theory to Practice", ACM TOSN 2020 (CCF-B)
7,Z. Zheng, F. Wang, D. Wang, and L. Zhang, "Buildings affect Mobile Pattens: Developing a new Urban Mobility Model", in Proc. of ACM Buildsys’18 (Best Paper Award)
8,L. Zhang, A. H. Lam and D. Wang, "Strategy proof Thermal Comfort Voting in Buildings,
in Proc. of ACM BuildSys’14
强化学习以及应用
9, D. Zhao, L. Zhang*, B. Zhang, L. Zheng, Y. Bao, W. Yan, "MaHRL: Multi-goals Abstraction based Deep Hierarchical Reinforcement Learning for Recommendations", in Proc. of ACM SIGIR 2020 (CCF-A)
10, Y. Su, L. Zhang*, Q. Dai, B. Zhang, J. Yan, S. Xu, D. Wang, Y. He, Y. Bao, and W. Yan, "An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration", in Proc. of IJCAI 2020 (CCF-A)
11, Y. Wang, L. Zhang(co-first author), Q. Dai, F. Sun, B. Zhang, Y. He, Y. Bao and W. Yan , "Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction", in Proc. of ACM CIKM 2019 (CCF-B)
12, X. Zhao, L. Xia, L. Zhang, Z. Ding, D. Yin, J. Tang, "Deep Reinforcement Learning for Page-wise Recommendations", in Proc. of ACM RecSys 2018 (CCF-B，高引论文270+)
13, X. Zhao, L. Zhang, Z. Ding, L. Xia, J. Tang, and D. Yin. "Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning". in Proc. of ACM SIGKDD 2018. (CCF-A，高引论文280+)
14,W. Lu, F. Chung, K. Lai, L. Zhang,"Recommender system based on scarce information mining", Neural Networks, 2017 (CCF-B)
15, Q Dai, X Shen, Z Zheng, L Zhang, Q Li, D Wang, "Adversarial training regularization for negative sampling based network embedding", Information Sciences 2021 (CCF-B)
16, Q. Dai, X. Shen, L. Zhang, Q. Li, D. Wang, "Adversarial Training Methods for Network Embedding", in Proc. of ACM WWW 2019 (CCF-A)
职务/职称
研究科学家
研究方向
强化学习、智能楼宇，博弈论与网络优化
电子邮箱
zhangliangshuxue@gmail.com
教育背景
华中科技大学，学士， 2011
香港理工大学， 博士， 2016
主要成果/荣誉
国际会议Buildsys 2014的最佳论文奖
深圳市海外高层次人才(C类)
个人介绍
2017-2022年先后入职京东和腾讯，发表在KDD、SIGIR等多项强化学习决策研究成果在京东商业广告和腾讯王者荣耀上线应用，谷歌引用量1100+。后加入鹏城实验室，担任副研究员。主要研究方向: 强化学习，智能楼宇，博弈论与网络优化等。
代表性论文
博弈论与网络优化
1,Y. Zhao, H. Wang, H. Su, L. Zhang, R. Zhang, D. Wang, K. Xu,“Understand love of variety in wireless data market under sponsored data plans”,IEEE JSAC 2020 (CCF-A)
2,Y. Zhao, H, Su, L. Zhang, D. Wang, K. Xu, "Variety Matters: A New Model for the Wireless Data Market under Sponsored Data Plans", in Proc. of IEEE/ACM IWQoS 2019. (CCF-B)
3, Liang Zhang, Weijie Wu and Dan Wang, "TDS: Time-Dependent Sponsored Data Plan for Wireless Data Traffic Market", in Proc. of IEEE INFOCOM 2016. (CCF-A)
4, Liang Zhang, Weijie Wu and Dan Wang,"Sponsored Data Plan: A Two-Class Service Model in Wireless Data Networks", in Proc. of ACM SIGMETRICS 2015. (CCF-B, CORE* A)
5, Liang Zhang, Weijie Wu and Dan Wang, "Time Dependent Pricing in Wireless Data Networks: Flat-rates vs. Usage-based Schemes", in Proc. of IEEE INFOCOM, 2014 (CCF-A)
绿色智能楼宇
6, Z Zheng, F Wang, D Wang, L Zhang, "An Urban Mobility Model with Buildings Involved:
Bridging Theory to Practice", ACM TOSN 2020 (CCF-B)
7,Z. Zheng, F. Wang, D. Wang, and L. Zhang, "Buildings affect Mobile Pattens: Developing a new Urban Mobility Model", in Proc. of ACM Buildsys’18 (Best Paper Award)
8,L. Zhang, A. H. Lam and D. Wang, "Strategy proof Thermal Comfort Voting in Buildings,
in Proc. of ACM BuildSys’14
强化学习以及应用
9, D. Zhao, L. Zhang*, B. Zhang, L. Zheng, Y. Bao, W. Yan, "MaHRL: Multi-goals Abstraction based Deep Hierarchical Reinforcement Learning for Recommendations", in Proc. of ACM SIGIR 2020 (CCF-A)
10, Y. Su, L. Zhang*, Q. Dai, B. Zhang, J. Yan, S. Xu, D. Wang, Y. He, Y. Bao, and W. Yan, "An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration", in Proc. of IJCAI 2020 (CCF-A)
11, Y. Wang, L. Zhang(co-first author), Q. Dai, F. Sun, B. Zhang, Y. He, Y. Bao and W. Yan , "Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction", in Proc. of ACM CIKM 2019 (CCF-B)
12, X. Zhao, L. Xia, L. Zhang, Z. Ding, D. Yin, J. Tang, "Deep Reinforcement Learning for Page-wise Recommendations", in Proc. of ACM RecSys 2018 (CCF-B，高引论文270+)
13, X. Zhao, L. Zhang, Z. Ding, L. Xia, J. Tang, and D. Yin. "Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning". in Proc. of ACM SIGKDD 2018. (CCF-A，高引论文280+)
14,W. Lu, F. Chung, K. Lai, L. Zhang,"Recommender system based on scarce information mining", Neural Networks, 2017 (CCF-B)
15, Q Dai, X Shen, Z Zheng, L Zhang, Q Li, D Wang, "Adversarial training regularization for negative sampling based network embedding", Information Sciences 2021 (CCF-B)
16, Q. Dai, X. Shen, L. Zhang, Q. Li, D. Wang, "Adversarial Training Methods for Network Embedding", in Proc. of ACM WWW 2019 (CCF-A)
职务/职称
研究科学家
研究方向
强化学习、智能楼宇，博弈论与网络优化
电子邮箱
zhangliangshuxue@gmail.com
教育背景
华中科技大学，学士， 2011
香港理工大学， 博士， 2016
主要成果/荣誉
国际会议Buildsys 2014的最佳论文奖
深圳市海外高层次人才(C类)
个人介绍
2017-2022年先后入职京东和腾讯，发表在KDD、SIGIR等多项强化学习决策研究成果在京东商业广告和腾讯王者荣耀上线应用，谷歌引用量1100+。后加入鹏城实验室，担任副研究员。主要研究方向: 强化学习，智能楼宇，博弈论与网络优化等。
代表性论文
博弈论与网络优化
1,Y. Zhao, H. Wang, H. Su, L. Zhang, R. Zhang, D. Wang, K. Xu,“Understand love of variety in wireless data market under sponsored data plans”,IEEE JSAC 2020 (CCF-A)
2,Y. Zhao, H, Su, L. Zhang, D. Wang, K. Xu, "Variety Matters: A New Model for the Wireless Data Market under Sponsored Data Plans", in Proc. of IEEE/ACM IWQoS 2019. (CCF-B)
3, Liang Zhang, Weijie Wu and Dan Wang, "TDS: Time-Dependent Sponsored Data Plan for Wireless Data Traffic Market", in Proc. of IEEE INFOCOM 2016. (CCF-A)
4, Liang Zhang, Weijie Wu and Dan Wang,"Sponsored Data Plan: A Two-Class Service Model in Wireless Data Networks", in Proc. of ACM SIGMETRICS 2015. (CCF-B, CORE* A)
5, Liang Zhang, Weijie Wu and Dan Wang, "Time Dependent Pricing in Wireless Data Networks: Flat-rates vs. Usage-based Schemes", in Proc. of IEEE INFOCOM, 2014 (CCF-A)
绿色智能楼宇
6, Z Zheng, F Wang, D Wang, L Zhang, "An Urban Mobility Model with Buildings Involved:
Bridging Theory to Practice", ACM TOSN 2020 (CCF-B)
7,Z. Zheng, F. Wang, D. Wang, and L. Zhang, "Buildings affect Mobile Pattens: Developing a new Urban Mobility Model", in Proc. of ACM Buildsys’18 (Best Paper Award)
8,L. Zhang, A. H. Lam and D. Wang, "Strategy proof Thermal Comfort Voting in Buildings,
in Proc. of ACM BuildSys’14
强化学习以及应用
9, D. Zhao, L. Zhang*, B. Zhang, L. Zheng, Y. Bao, W. Yan, "MaHRL: Multi-goals Abstraction based Deep Hierarchical Reinforcement Learning for Recommendations", in Proc. of ACM SIGIR 2020 (CCF-A)
10, Y. Su, L. Zhang*, Q. Dai, B. Zhang, J. Yan, S. Xu, D. Wang, Y. He, Y. Bao, and W. Yan, "An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration", in Proc. of IJCAI 2020 (CCF-A)
11, Y. Wang, L. Zhang(co-first author), Q. Dai, F. Sun, B. Zhang, Y. He, Y. Bao and W. Yan , "Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction", in Proc. of ACM CIKM 2019 (CCF-B)
12, X. Zhao, L. Xia, L. Zhang, Z. Ding, D. Yin, J. Tang, "Deep Reinforcement Learning for Page-wise Recommendations", in Proc. of ACM RecSys 2018 (CCF-B，高引论文270+)
13, X. Zhao, L. Zhang, Z. Ding, L. Xia, J. Tang, and D. Yin. "Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning". in Proc. of ACM SIGKDD 2018. (CCF-A，高引论文280+)
14,W. Lu, F. Chung, K. Lai, L. Zhang,"Recommender system based on scarce information mining", Neural Networks, 2017 (CCF-B)
15, Q Dai, X Shen, Z Zheng, L Zhang, Q Li, D Wang, "Adversarial training regularization for negative sampling based network embedding", Information Sciences 2021 (CCF-B)
16, Q. Dai, X. Shen, L. Zhang, Q. Li, D. Wang, "Adversarial Training Methods for Network Embedding", in Proc. of ACM WWW 2019 (CCF-A)
职务/职称
深圳市大数据研究院信息系统大数据实验室研究科学家
研究方向
电力系统优化、混合整数规划、最优化算法以及机器学习
电子邮箱
wujianghua@sribd.cn
教育背景
2014.08 – 2018.08 沈阳建筑大学，建筑电气智能化，学士
2018.08 – 2023.08 康涅狄格大学，电气与计算机工程，博士
个人介绍
吴江华博士于2023年在美国康涅狄格大学（University of Connecticut）的电气与计算机工程（Electrical and Computer Engineering）学院取得博士学位，同年9月加入深圳市大数据研究院，担任研究科学家。他现在的主要研究兴趣是分布式能源的并网及电力系统优化、考虑新能源及储能的新型电网优化，最优化算法以及传统优化算法与机器学习的融合。
代表性论文
1. J. Wu, P. Luh, Y. Chen, M. Bragin and B. Yan, “A Novel Optimization Approach for Subhourly Unit Commitment with Large Numbers of Units and Virtual Transactions,” IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3716–3725, Sep. 2022.
2. J. Wu, P. Luh, Y. Chen, B. Yan and M. Bragin, “Synergistic Integration of Machine Learning and Mathematical Optimization for Unit Commitment,” IEEE Transactions on Power Systems, Jan. 2023. (Accepted)
3. J. Wu, Z. Wang, Y. Chen, B. Yan and M. A. Bragin, P. B. Luh, “A Hybrid Machine Learning and Optimization Approach with Feasibility Layer Assistance for Sub-hourly Unit Commitment,” (Under Review)
4. W. Lin, J. Hua, H. Jian, J. Xue, J. Wu, C. Wang and Z. Lin, “High-dimension tie-line security regions for renewable accommodations,” Energy, vol 270, May 2023, 126887.
5. J. Wu, P. B. Luh, Y. Chen, B. Yan, and M. A. Bragin, “A Decomposition and Coordination Approach for Large Sub-hourly Unit Commitment,” 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Aug. 2020.
职务/职称
深圳市大数据研究院信息系统大数据实验室研究科学家
研究方向
电力系统优化、混合整数规划、最优化算法以及机器学习
电子邮箱
wujianghua@sribd.cn
教育背景
2014.08 – 2018.08 沈阳建筑大学，建筑电气智能化，学士
2018.08 – 2023.08 康涅狄格大学，电气与计算机工程，博士
个人介绍
吴江华博士于2023年在美国康涅狄格大学（University of Connecticut）的电气与计算机工程（Electrical and Computer Engineering）学院取得博士学位，同年9月加入深圳市大数据研究院，担任研究科学家。他现在的主要研究兴趣是分布式能源的并网及电力系统优化、考虑新能源及储能的新型电网优化，最优化算法以及传统优化算法与机器学习的融合。
代表性论文
1. J. Wu, P. Luh, Y. Chen, M. Bragin and B. Yan, “A Novel Optimization Approach for Subhourly Unit Commitment with Large Numbers of Units and Virtual Transactions,” IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3716–3725, Sep. 2022.
2. J. Wu, P. Luh, Y. Chen, B. Yan and M. Bragin, “Synergistic Integration of Machine Learning and Mathematical Optimization for Unit Commitment,” IEEE Transactions on Power Systems, Jan. 2023. (Accepted)
3. J. Wu, Z. Wang, Y. Chen, B. Yan and M. A. Bragin, P. B. Luh, “A Hybrid Machine Learning and Optimization Approach with Feasibility Layer Assistance for Sub-hourly Unit Commitment,” (Under Review)
4. W. Lin, J. Hua, H. Jian, J. Xue, J. Wu, C. Wang and Z. Lin, “High-dimension tie-line security regions for renewable accommodations,” Energy, vol 270, May 2023, 126887.
5. J. Wu, P. B. Luh, Y. Chen, B. Yan, and M. A. Bragin, “A Decomposition and Coordination Approach for Large Sub-hourly Unit Commitment,” 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Aug. 2020.
职务/职称
深圳市大数据研究院信息系统大数据实验室研究科学家
研究方向
电力系统优化、混合整数规划、最优化算法以及机器学习
电子邮箱
wujianghua@sribd.cn
教育背景
2014.08 – 2018.08 沈阳建筑大学，建筑电气智能化，学士
2018.08 – 2023.08 康涅狄格大学，电气与计算机工程，博士
个人介绍
吴江华博士于2023年在美国康涅狄格大学（University of Connecticut）的电气与计算机工程（Electrical and Computer Engineering）学院取得博士学位，同年9月加入深圳市大数据研究院，担任研究科学家。他现在的主要研究兴趣是分布式能源的并网及电力系统优化、考虑新能源及储能的新型电网优化，最优化算法以及传统优化算法与机器学习的融合。
代表性论文
1. J. Wu, P. Luh, Y. Chen, M. Bragin and B. Yan, “A Novel Optimization Approach for Subhourly Unit Commitment with Large Numbers of Units and Virtual Transactions,” IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3716–3725, Sep. 2022.
2. J. Wu, P. Luh, Y. Chen, B. Yan and M. Bragin, “Synergistic Integration of Machine Learning and Mathematical Optimization for Unit Commitment,” IEEE Transactions on Power Systems, Jan. 2023. (Accepted)
3. J. Wu, Z. Wang, Y. Chen, B. Yan and M. A. Bragin, P. B. Luh, “A Hybrid Machine Learning and Optimization Approach with Feasibility Layer Assistance for Sub-hourly Unit Commitment,” (Under Review)
4. W. Lin, J. Hua, H. Jian, J. Xue, J. Wu, C. Wang and Z. Lin, “High-dimension tie-line security regions for renewable accommodations,” Energy, vol 270, May 2023, 126887.
5. J. Wu, P. B. Luh, Y. Chen, B. Yan, and M. A. Bragin, “A Decomposition and Coordination Approach for Large Sub-hourly Unit Commitment,” 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Aug. 2020.
职务/职称
深圳市大数据研究院信息系统大数据实验室研究科学家
研究方向
电力系统优化、混合整数规划、最优化算法以及机器学习
电子邮箱
wujianghua@sribd.cn
教育背景
2014.08 – 2018.08 沈阳建筑大学，建筑电气智能化，学士
2018.08 – 2023.08 康涅狄格大学，电气与计算机工程，博士
个人介绍
吴江华博士于2023年在美国康涅狄格大学（University of Connecticut）的电气与计算机工程（Electrical and Computer Engineering）学院取得博士学位，同年9月加入深圳市大数据研究院，担任研究科学家。他现在的主要研究兴趣是分布式能源的并网及电力系统优化、考虑新能源及储能的新型电网优化，最优化算法以及传统优化算法与机器学习的融合。
代表性论文
1. J. Wu, P. Luh, Y. Chen, M. Bragin and B. Yan, “A Novel Optimization Approach for Subhourly Unit Commitment with Large Numbers of Units and Virtual Transactions,” IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3716–3725, Sep. 2022.
2. J. Wu, P. Luh, Y. Chen, B. Yan and M. Bragin, “Synergistic Integration of Machine Learning and Mathematical Optimization for Unit Commitment,” IEEE Transactions on Power Systems, Jan. 2023. (Accepted)
3. J. Wu, Z. Wang, Y. Chen, B. Yan and M. A. Bragin, P. B. Luh, “A Hybrid Machine Learning and Optimization Approach with Feasibility Layer Assistance for Sub-hourly Unit Commitment,” (Under Review)
4. W. Lin, J. Hua, H. Jian, J. Xue, J. Wu, C. Wang and Z. Lin, “High-dimension tie-line security regions for renewable accommodations,” Energy, vol 270, May 2023, 126887.
5. J. Wu, P. B. Luh, Y. Chen, B. Yan, and M. A. Bragin, “A Decomposition and Coordination Approach for Large Sub-hourly Unit Commitment,” 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Aug. 2020.
职务/职称
信息系统大数据实验室研究科学家
教育背景
博士（香港大学）
学士（华中科技大学）
研究领域
电力与能源系统；灵活智联高能效建筑；基础设施弹性；优化；机器/强化学习
学术领域
计算机工程，电子工程，新能源科学与工程
个人网站
http://leishunbo.info/
电子邮件
leishunbo@cuhk.edu.cn
个人简介
雷顺波，香港中文大学（深圳）助理教授、博士生导师。他于2013年获华中科技大学工学学士学位，于2017年获香港大学博士学位；先后在美国阿贡国家实验室任访问学者（2015-2017），在香港大学从事博士后研究（2017-2019），在美国密歇根大学任研究员（2019-2021）和访问研究员（2021）。他的研究兴趣包括韧性综合能源系统、建筑-电网交互灵活性、优化和学习算法；发表论文50余篇，以第一作者出版Wiley-IEEE专著Power Grid Resilience Against Natural Disasters: Preparedness, Response, and Recovery，3篇第一作者论文入选ESI Top 1%高被引论文。
雷博士现担任IEEE Transactions on Smart Grid、《现代电力系统保护与控制》（英文）、《中国电力》等期刊的编委或青年编委；同时担任IEEE PES Loads Subcommittee技术分委会副主席、IEEE PES TF on Flexible Grid-Interactive Efficient Buildings to Enhance Electric Service Resilience工作组主席；获评IEEE Transactions on Smart Grid最佳论文奖（2019-2021）、IEEE PES General Meeting最佳会议论文奖（2022）、IEEE Transactions on Power Systems/Smart Grid/Sustainable Energy等期刊的最佳审稿人奖（2018，2019，2021，2022）、荷兰4TU理工大学联盟韧性工程中心“Young Resilience Fellow”（2021）。
学术著作
查看完整论文列表，请访问其Google Scholar主页：https://scholar.google.be/citations?user=ltUvPPkAAAAJ&hl=en
部分论文（截至2022年5月）:
- Shunbo Lei, David Pozo, Ming-Hao Wang, Qifeng Li, Yupeng Li, and Chaoyi Peng, "Power Economic Dispatch against Extreme Weather Conditions: The Price of Resilience," Renewable and Sustainable Energy Reviews, 157: 111994, Apr. 2022.
- Aditya Keskar*, Shunbo Lei*, Taylor Webb, Sarah Nagy, Ian A. Hiskens, Johanna L. Mathieu, and Jeremiah X. Johnson, "Assessing the Performance of Global Thermostat Adjustment in Commercial Buildings for Load Shifting Demand Response," Environmental Research: Infrastructure and Sustainability, 2: 015003, Mar. 2022. (*Co-first and co-corresponding authors)
- Shunbo Lei, Johanna L. Mathieu, and Rishee K. Jain, "Performance of Existing Models in Baselining Demand Response from Commercial Building HVAC Fans," ASME Journal of Engineering for Sustainable Buildings and Cities, 2(2): 021002, May 2021.
- Rong-Peng Liu, Shunbo Lei*, Chaoyi Peng, Wei Sun, and Yunhe Hou, "Data-based Resilience Enhancement Strategies for Electric-Gas Systems against Sequential Extreme Weather Events," IEEE Transactions on Smart Grid, 11(6): 5383-5395, Nov 2020. (*Corresponding author)
- Shunbo Lei, Chen Chen, Yue Song, and Yunhe Hou, "Radiality Constraints for Resilient Reconfiguration of Distribution Systems: Formulation and Application to Microgrid Formation," IEEE Transactions on Smart Grid, 11(5): 3944-3956, Sep 2020.
- Shunbo Lei, David Hong, Johanna L. Mathieu, and Ian A. Hiskens, "Baseline Estimation of Commercial Building HVAC Fan Power Using Tensor Completion," in Proceedings of the Power Systems Computation Conference (PSCC), Porto, Portugal, Jun 2020.
- Shunbo Lei, Chen Chen, Yupeng Li, and Yunhe Hou, "Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration with Repair Crew and Mobile Power Source Dispatch," IEEE Transactions on Smart Grid, 10(6): 6187-6202, Nov 2019. (2019-2021 IEEE Transactions on Smart Grid Top 5 Outstanding Papers Award)
- Shunbo Lei, Chen Chen, Hui Zhou, and Yunhe Hou, "Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement," IEEE Transactions on Smart Grid, 10(5): 5650-5662, Sep 2019.
- Yang Liu, Shunbo Lei*, and Yunhe Hou, "Restoration of Power Distribution Systems with Multiple Data Centers as Critical Loads," IEEE Transactions on Smart Grid, 10(5): 5294-5307, Sep 2019. (*Corresponding author)
- Shunbo Lei, Jianhui Wang, Chen Chen, and Yunhe Hou, "Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters," IEEE Transactions on Smart Grid, 9(3): 2030-2041, May 2018. (ESI Top 1% Highly Cited Paper)
- Shunbo Lei, Jianhui Wang, and Yunhe Hou, "Remote-Controlled Switch Allocation Enabling Prompt Restoration of Distribution Systems," IEEE Transactions on Power Systems, 33(3): 3129-3142, May 2018.
- Shunbo Lei, Yunhe Hou, Feng Qiu, and Jie Yan, "Identification of Critical Switches for Integrating Renewable Distributed Generation by Dynamic Network Reconfiguration," IEEE Transactions on Sustainable Energy, 9(1): 420-432, Jan 2018.
- Shunbo Lei, Yunhe Hou, Xi Wang, and Kai Liu, "Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion," IEEE Transactions on Industrial Informatics, 13(3): 995-1005, Jun 2017.
职务/职称
信息系统大数据实验室研究科学家
教育背景
博士（香港大学）
学士（华中科技大学）
研究领域
电力与能源系统；灵活智联高能效建筑；基础设施弹性；优化；机器/强化学习
学术领域
计算机工程，电子工程，新能源科学与工程
个人网站
http://leishunbo.info/
电子邮件
leishunbo@cuhk.edu.cn
个人简介
雷顺波，香港中文大学（深圳）助理教授、博士生导师。他于2013年获华中科技大学工学学士学位，于2017年获香港大学博士学位；先后在美国阿贡国家实验室任访问学者（2015-2017），在香港大学从事博士后研究（2017-2019），在美国密歇根大学任研究员（2019-2021）和访问研究员（2021）。他的研究兴趣包括韧性综合能源系统、建筑-电网交互灵活性、优化和学习算法；发表论文50余篇，以第一作者出版Wiley-IEEE专著Power Grid Resilience Against Natural Disasters: Preparedness, Response, and Recovery，3篇第一作者论文入选ESI Top 1%高被引论文。
雷博士现担任IEEE Transactions on Smart Grid、《现代电力系统保护与控制》（英文）、《中国电力》等期刊的编委或青年编委；同时担任IEEE PES Loads Subcommittee技术分委会副主席、IEEE PES TF on Flexible Grid-Interactive Efficient Buildings to Enhance Electric Service Resilience工作组主席；获评IEEE Transactions on Smart Grid最佳论文奖（2019-2021）、IEEE PES General Meeting最佳会议论文奖（2022）、IEEE Transactions on Power Systems/Smart Grid/Sustainable Energy等期刊的最佳审稿人奖（2018，2019，2021，2022）、荷兰4TU理工大学联盟韧性工程中心“Young Resilience Fellow”（2021）。
学术著作
查看完整论文列表，请访问其Google Scholar主页：https://scholar.google.be/citations?user=ltUvPPkAAAAJ&hl=en
部分论文（截至2022年5月）:
- Shunbo Lei, David Pozo, Ming-Hao Wang, Qifeng Li, Yupeng Li, and Chaoyi Peng, "Power Economic Dispatch against Extreme Weather Conditions: The Price of Resilience," Renewable and Sustainable Energy Reviews, 157: 111994, Apr. 2022.
- Aditya Keskar*, Shunbo Lei*, Taylor Webb, Sarah Nagy, Ian A. Hiskens, Johanna L. Mathieu, and Jeremiah X. Johnson, "Assessing the Performance of Global Thermostat Adjustment in Commercial Buildings for Load Shifting Demand Response," Environmental Research: Infrastructure and Sustainability, 2: 015003, Mar. 2022. (*Co-first and co-corresponding authors)
- Shunbo Lei, Johanna L. Mathieu, and Rishee K. Jain, "Performance of Existing Models in Baselining Demand Response from Commercial Building HVAC Fans," ASME Journal of Engineering for Sustainable Buildings and Cities, 2(2): 021002, May 2021.
- Rong-Peng Liu, Shunbo Lei*, Chaoyi Peng, Wei Sun, and Yunhe Hou, "Data-based Resilience Enhancement Strategies for Electric-Gas Systems against Sequential Extreme Weather Events," IEEE Transactions on Smart Grid, 11(6): 5383-5395, Nov 2020. (*Corresponding author)
- Shunbo Lei, Chen Chen, Yue Song, and Yunhe Hou, "Radiality Constraints for Resilient Reconfiguration of Distribution Systems: Formulation and Application to Microgrid Formation," IEEE Transactions on Smart Grid, 11(5): 3944-3956, Sep 2020.
- Shunbo Lei, David Hong, Johanna L. Mathieu, and Ian A. Hiskens, "Baseline Estimation of Commercial Building HVAC Fan Power Using Tensor Completion," in Proceedings of the Power Systems Computation Conference (PSCC), Porto, Portugal, Jun 2020.
- Shunbo Lei, Chen Chen, Yupeng Li, and Yunhe Hou, "Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration with Repair Crew and Mobile Power Source Dispatch," IEEE Transactions on Smart Grid, 10(6): 6187-6202, Nov 2019. (2019-2021 IEEE Transactions on Smart Grid Top 5 Outstanding Papers Award)
- Shunbo Lei, Chen Chen, Hui Zhou, and Yunhe Hou, "Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement," IEEE Transactions on Smart Grid, 10(5): 5650-5662, Sep 2019.
- Yang Liu, Shunbo Lei*, and Yunhe Hou, "Restoration of Power Distribution Systems with Multiple Data Centers as Critical Loads," IEEE Transactions on Smart Grid, 10(5): 5294-5307, Sep 2019. (*Corresponding author)
- Shunbo Lei, Jianhui Wang, Chen Chen, and Yunhe Hou, "Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters," IEEE Transactions on Smart Grid, 9(3): 2030-2041, May 2018. (ESI Top 1% Highly Cited Paper)
- Shunbo Lei, Jianhui Wang, and Yunhe Hou, "Remote-Controlled Switch Allocation Enabling Prompt Restoration of Distribution Systems," IEEE Transactions on Power Systems, 33(3): 3129-3142, May 2018.
- Shunbo Lei, Yunhe Hou, Feng Qiu, and Jie Yan, "Identification of Critical Switches for Integrating Renewable Distributed Generation by Dynamic Network Reconfiguration," IEEE Transactions on Sustainable Energy, 9(1): 420-432, Jan 2018.
- Shunbo Lei, Yunhe Hou, Xi Wang, and Kai Liu, "Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion," IEEE Transactions on Industrial Informatics, 13(3): 995-1005, Jun 2017.
职务/职称
信息系统大数据实验室研究科学家
教育背景
博士（香港大学）
学士（华中科技大学）
研究领域
电力与能源系统；灵活智联高能效建筑；基础设施弹性；优化；机器/强化学习
学术领域
计算机工程，电子工程，新能源科学与工程
个人网站
http://leishunbo.info/
电子邮件
leishunbo@cuhk.edu.cn
个人简介
雷顺波，香港中文大学（深圳）助理教授、博士生导师。他于2013年获华中科技大学工学学士学位，于2017年获香港大学博士学位；先后在美国阿贡国家实验室任访问学者（2015-2017），在香港大学从事博士后研究（2017-2019），在美国密歇根大学任研究员（2019-2021）和访问研究员（2021）。他的研究兴趣包括韧性综合能源系统、建筑-电网交互灵活性、优化和学习算法；发表论文50余篇，以第一作者出版Wiley-IEEE专著Power Grid Resilience Against Natural Disasters: Preparedness, Response, and Recovery，3篇第一作者论文入选ESI Top 1%高被引论文。
雷博士现担任IEEE Transactions on Smart Grid、《现代电力系统保护与控制》（英文）、《中国电力》等期刊的编委或青年编委；同时担任IEEE PES Loads Subcommittee技术分委会副主席、IEEE PES TF on Flexible Grid-Interactive Efficient Buildings to Enhance Electric Service Resilience工作组主席；获评IEEE Transactions on Smart Grid最佳论文奖（2019-2021）、IEEE PES General Meeting最佳会议论文奖（2022）、IEEE Transactions on Power Systems/Smart Grid/Sustainable Energy等期刊的最佳审稿人奖（2018，2019，2021，2022）、荷兰4TU理工大学联盟韧性工程中心“Young Resilience Fellow”（2021）。
学术著作
查看完整论文列表，请访问其Google Scholar主页：https://scholar.google.be/citations?user=ltUvPPkAAAAJ&hl=en
部分论文（截至2022年5月）:
- Shunbo Lei, David Pozo, Ming-Hao Wang, Qifeng Li, Yupeng Li, and Chaoyi Peng, "Power Economic Dispatch against Extreme Weather Conditions: The Price of Resilience," Renewable and Sustainable Energy Reviews, 157: 111994, Apr. 2022.
- Aditya Keskar*, Shunbo Lei*, Taylor Webb, Sarah Nagy, Ian A. Hiskens, Johanna L. Mathieu, and Jeremiah X. Johnson, "Assessing the Performance of Global Thermostat Adjustment in Commercial Buildings for Load Shifting Demand Response," Environmental Research: Infrastructure and Sustainability, 2: 015003, Mar. 2022. (*Co-first and co-corresponding authors)
- Shunbo Lei, Johanna L. Mathieu, and Rishee K. Jain, "Performance of Existing Models in Baselining Demand Response from Commercial Building HVAC Fans," ASME Journal of Engineering for Sustainable Buildings and Cities, 2(2): 021002, May 2021.
- Rong-Peng Liu, Shunbo Lei*, Chaoyi Peng, Wei Sun, and Yunhe Hou, "Data-based Resilience Enhancement Strategies for Electric-Gas Systems against Sequential Extreme Weather Events," IEEE Transactions on Smart Grid, 11(6): 5383-5395, Nov 2020. (*Corresponding author)
- Shunbo Lei, Chen Chen, Yue Song, and Yunhe Hou, "Radiality Constraints for Resilient Reconfiguration of Distribution Systems: Formulation and Application to Microgrid Formation," IEEE Transactions on Smart Grid, 11(5): 3944-3956, Sep 2020.
- Shunbo Lei, David Hong, Johanna L. Mathieu, and Ian A. Hiskens, "Baseline Estimation of Commercial Building HVAC Fan Power Using Tensor Completion," in Proceedings of the Power Systems Computation Conference (PSCC), Porto, Portugal, Jun 2020.
- Shunbo Lei, Chen Chen, Yupeng Li, and Yunhe Hou, "Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration with Repair Crew and Mobile Power Source Dispatch," IEEE Transactions on Smart Grid, 10(6): 6187-6202, Nov 2019. (2019-2021 IEEE Transactions on Smart Grid Top 5 Outstanding Papers Award)
- Shunbo Lei, Chen Chen, Hui Zhou, and Yunhe Hou, "Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement," IEEE Transactions on Smart Grid, 10(5): 5650-5662, Sep 2019.
- Yang Liu, Shunbo Lei*, and Yunhe Hou, "Restoration of Power Distribution Systems with Multiple Data Centers as Critical Loads," IEEE Transactions on Smart Grid, 10(5): 5294-5307, Sep 2019. (*Corresponding author)
- Shunbo Lei, Jianhui Wang, Chen Chen, and Yunhe Hou, "Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters," IEEE Transactions on Smart Grid, 9(3): 2030-2041, May 2018. (ESI Top 1% Highly Cited Paper)
- Shunbo Lei, Jianhui Wang, and Yunhe Hou, "Remote-Controlled Switch Allocation Enabling Prompt Restoration of Distribution Systems," IEEE Transactions on Power Systems, 33(3): 3129-3142, May 2018.
- Shunbo Lei, Yunhe Hou, Feng Qiu, and Jie Yan, "Identification of Critical Switches for Integrating Renewable Distributed Generation by Dynamic Network Reconfiguration," IEEE Transactions on Sustainable Energy, 9(1): 420-432, Jan 2018.
- Shunbo Lei, Yunhe Hou, Xi Wang, and Kai Liu, "Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion," IEEE Transactions on Industrial Informatics, 13(3): 995-1005, Jun 2017.
职务/职称
信息系统大数据实验室研究科学家
教育背景
博士（香港大学）
学士（华中科技大学）
研究领域
电力与能源系统；灵活智联高能效建筑；基础设施弹性；优化；机器/强化学习
学术领域
计算机工程，电子工程，新能源科学与工程
个人网站
http://leishunbo.info/
电子邮件
leishunbo@cuhk.edu.cn
个人简介
雷顺波，香港中文大学（深圳）助理教授、博士生导师。他于2013年获华中科技大学工学学士学位，于2017年获香港大学博士学位；先后在美国阿贡国家实验室任访问学者（2015-2017），在香港大学从事博士后研究（2017-2019），在美国密歇根大学任研究员（2019-2021）和访问研究员（2021）。他的研究兴趣包括韧性综合能源系统、建筑-电网交互灵活性、优化和学习算法；发表论文50余篇，以第一作者出版Wiley-IEEE专著Power Grid Resilience Against Natural Disasters: Preparedness, Response, and Recovery，3篇第一作者论文入选ESI Top 1%高被引论文。
雷博士现担任IEEE Transactions on Smart Grid、《现代电力系统保护与控制》（英文）、《中国电力》等期刊的编委或青年编委；同时担任IEEE PES Loads Subcommittee技术分委会副主席、IEEE PES TF on Flexible Grid-Interactive Efficient Buildings to Enhance Electric Service Resilience工作组主席；获评IEEE Transactions on Smart Grid最佳论文奖（2019-2021）、IEEE PES General Meeting最佳会议论文奖（2022）、IEEE Transactions on Power Systems/Smart Grid/Sustainable Energy等期刊的最佳审稿人奖（2018，2019，2021，2022）、荷兰4TU理工大学联盟韧性工程中心“Young Resilience Fellow”（2021）。
学术著作
查看完整论文列表，请访问其Google Scholar主页：https://scholar.google.be/citations?user=ltUvPPkAAAAJ&hl=en
部分论文（截至2022年5月）:
- Shunbo Lei, David Pozo, Ming-Hao Wang, Qifeng Li, Yupeng Li, and Chaoyi Peng, "Power Economic Dispatch against Extreme Weather Conditions: The Price of Resilience," Renewable and Sustainable Energy Reviews, 157: 111994, Apr. 2022.
- Aditya Keskar*, Shunbo Lei*, Taylor Webb, Sarah Nagy, Ian A. Hiskens, Johanna L. Mathieu, and Jeremiah X. Johnson, "Assessing the Performance of Global Thermostat Adjustment in Commercial Buildings for Load Shifting Demand Response," Environmental Research: Infrastructure and Sustainability, 2: 015003, Mar. 2022. (*Co-first and co-corresponding authors)
- Shunbo Lei, Johanna L. Mathieu, and Rishee K. Jain, "Performance of Existing Models in Baselining Demand Response from Commercial Building HVAC Fans," ASME Journal of Engineering for Sustainable Buildings and Cities, 2(2): 021002, May 2021.
- Rong-Peng Liu, Shunbo Lei*, Chaoyi Peng, Wei Sun, and Yunhe Hou, "Data-based Resilience Enhancement Strategies for Electric-Gas Systems against Sequential Extreme Weather Events," IEEE Transactions on Smart Grid, 11(6): 5383-5395, Nov 2020. (*Corresponding author)
- Shunbo Lei, Chen Chen, Yue Song, and Yunhe Hou, "Radiality Constraints for Resilient Reconfiguration of Distribution Systems: Formulation and Application to Microgrid Formation," IEEE Transactions on Smart Grid, 11(5): 3944-3956, Sep 2020.
- Shunbo Lei, David Hong, Johanna L. Mathieu, and Ian A. Hiskens, "Baseline Estimation of Commercial Building HVAC Fan Power Using Tensor Completion," in Proceedings of the Power Systems Computation Conference (PSCC), Porto, Portugal, Jun 2020.
- Shunbo Lei, Chen Chen, Yupeng Li, and Yunhe Hou, "Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration with Repair Crew and Mobile Power Source Dispatch," IEEE Transactions on Smart Grid, 10(6): 6187-6202, Nov 2019. (2019-2021 IEEE Transactions on Smart Grid Top 5 Outstanding Papers Award)
- Shunbo Lei, Chen Chen, Hui Zhou, and Yunhe Hou, "Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement," IEEE Transactions on Smart Grid, 10(5): 5650-5662, Sep 2019.
- Yang Liu, Shunbo Lei*, and Yunhe Hou, "Restoration of Power Distribution Systems with Multiple Data Centers as Critical Loads," IEEE Transactions on Smart Grid, 10(5): 5294-5307, Sep 2019. (*Corresponding author)
- Shunbo Lei, Jianhui Wang, Chen Chen, and Yunhe Hou, "Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters," IEEE Transactions on Smart Grid, 9(3): 2030-2041, May 2018. (ESI Top 1% Highly Cited Paper)
- Shunbo Lei, Jianhui Wang, and Yunhe Hou, "Remote-Controlled Switch Allocation Enabling Prompt Restoration of Distribution Systems," IEEE Transactions on Power Systems, 33(3): 3129-3142, May 2018.
- Shunbo Lei, Yunhe Hou, Feng Qiu, and Jie Yan, "Identification of Critical Switches for Integrating Renewable Distributed Generation by Dynamic Network Reconfiguration," IEEE Transactions on Sustainable Energy, 9(1): 420-432, Jan 2018.
- Shunbo Lei, Yunhe Hou, Xi Wang, and Kai Liu, "Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion," IEEE Transactions on Industrial Informatics, 13(3): 995-1005, Jun 2017.
