发布时间:2019-12-01 浏览次数:33
朱群喜  青年研究员  博士生导师


复旦大学智能复杂体系基础理论与关键技术实验室 青年研究员

E-mail: qxzhu@fudan.edu.cn

个人主页:qunxizhu.cn


个人简介

朱群喜, 复旦大学智能复杂体系实验室青年研究员。2021年博士毕业于复旦大学数学科学学院。2021年至2024年在复旦大学从事博士后研究工作。致力于复杂系统和机器学习前沿的理论与方法研究, 在复杂系统建模、重构、预测和智能调控以及复杂系统驱动的机器学习领域做出了一系列工作, 相关成果以第一或通讯作者在综合性、控制、数学、物理、人工智能等顶级/一流学术刊物发表文章20余篇, 包括综合性领域期刊Nature Communications (人工智能与机器学习、应用物理与数学两个方向的Featured Article), 非线性期刊CHAOS (Editor’s Pick), 物理期刊Physical Review Research/E, 自动化控制理论期刊4篇(IEEE TAC 2篇, SIAM-CON 1篇, SCL 1篇), 人工智能会议7篇(ICML 3篇, ICLR 2篇, NeurIPS 1篇, AAAI 1篇)等。研究成果得到同行大家的关注和引用 (Edward Ott、Jürgen Kurths、曹进德、桂卫华等院士, Google Research、UC Berkeley、牛津大学、剑桥大学和麻省理工等知名教授专家团队), 以及国际知名学术/科技网站的报道(Phys.org, techxplore.com)。


曾获上海市启明星(扬帆专项)计划, 上海市“超级博士后”激励计划, 脑科学前沿中心“珠峰青年学者计划”, 上海市优秀毕业生荣誉称号,研究生国家奖学金3次,多次获得国家级和省部级大数据/程序设计/建模竞赛奖项(2019年IKCEST“一带一路”国际大数据竞赛特等奖,排名1st/2312)。

研究领域

复杂系统和人工智能交叉理论与方法; Math for AI (神经微分方程、储备池计算、知识嵌入机器学习等); AI for Science (物理、控制、计算生物等)

代表性成果

会议论文

  1. Qunxi Zhu* and Wei Lin [2024], Switched flow matching: Eliminating singularities via switching ODEs, 41st International Conference on Machine Learning (ICML 2024). (CCF A,人工智能三大顶会之一,每年举办一次)

  2. Jingdong Zhang, Luan Yang, Qunxi Zhu* and Wei Lin* [2024],  FESSNC: Fast exponentially stable and safe neural controller, 41st International Conference on Machine Learning (ICML 2024). (CCF A,人工智能三大顶会之一,每年举办一次)

  3. Xin Li, Jingdong Zhang, Qunxi Zhu*, Chengli Zhao*, Xue Zhang, Xiaojun Duan, and Wei Lin [2024], From Fourier to neural ODEs: Flow matching for modeling complex systems, 41st International Conference on Machine Learning (ICML 2024). (CCF A,人工智能三大顶会之一,每年举办一次)

  4. Shunyu Liu, Jie Zhou*, Qunxi Zhu, Qin Chen, Qingchun Bai, Jun Xiao, Liang He [2024], Let's Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion Models, International Conference on Computational Linguistics (COLING 2024). (自然语言处理和计算语言学领域的顶会,每两年举办一次)

  5. Limao Xiong, Jie Zhou*, Qunxi Zhu, Xiao Wang, Yuanbin Wu, Qi Zhang, Tao Gui, Xuanjing Huang, Jin Ma, Ying Shan [2023], A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition, Findings of the Association for Computational Linguistics (ACL 2023 Findings). (自然语言处理顶会, CCF A,每年举办一次)

  6. Jingdong Zhang, Qunxi Zhu*, Wei Yang*, and Wei Lin* [2023], SYNC: Safety-aware neural control for stablizing stochastic delay-differential equations, 11th International Conference on Learning Representations (ICLR 2023). (人工智能三大顶会之一,每年举办一次)

  7. Jingdong Zhang, Qunxi Zhu*, and Wei Lin* [2022], Hamiltonian neural Koopman operator, The Symbiosis of Deep Learning and Differential Equations - Workshop DLDE @ NeurIPS 2022.

  8. Jingdong Zhang, Qunxi Zhu*, and Wei Lin* [2022], Neural stochastic control, 36th Conference on Neural Information Processing Systems (NeurIPS 2022). (CCF A,人工智能三大顶会之一,每年举办一次)

  9. Qunxi Zhu*, Yifei Shen, Dongsheng Li, and Wei Lin* [2022], Neural piecewise-constant delay differential equations, 36th AAAI Conference on Artificial Intelligence (AAAI 2022). (CCF A,每年举办一次)

  10. Qunxi Zhu*, Yao Guo*, and Wei Lin* [2021], Neural delay differential equations, 9th International Conference on Learning Representations (ICLR 2021). (人工智能三大顶会之一,每年举办一次)


期刊论文

  1. Jingdong Zhang, Luan Yang, Qunxi Zhu*, Celso Grebogi, and Wei Lin* [2024], Machine-learning-coined noise induces energy-saving synchrony, Physical Review E, Letter, vol. 110, no. 1, Art. no. L012203. (国际知名学术Phys.org报道)

  2. Xin Li, Qunxi Zhu*, Chengli Zhao*, Xiaojun Duan, Bolin Zhao, Xue Zhang, Huanfei Ma, Jie Sun, and Wei Lin* [2024], Higher-order Granger reservoir computing: Simultaneously achieving scalable complex structures inference and accurate dynamics prediction, Nature Communications, vol. 15, Art. no. 2506. (Editorially selected as a Featured Article both in NC's focus contents: AI & machine learning & Applied physics and mathematics) (国际知名科技techxplore.com报道)

  3. Jingdong Zhang, Qunxi Zhu*, and Wei Lin* [2024],  Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws, Physical Review Research, Letter, vol. 6, no. 1, Art. no. L012031. (国际知名学术Phys.org报道)

  4. Boyun Ji, Qunxi Zhu*, and Wei Lin [2023], Dimension reduction of collective attention networks, International Journal of Bifurcation and Chaos, August 14, vol. 33, no. 11, Art. no. 2350135.

  5. Xin Li, Qunxi Zhu*, Chengli Zhao*, Xuzhe Qian, Xue Zhang, Xiaojun Duan, and Wei Lin [2023], Tipping-point detection using reservoir computing, RESEARCH, vol. 6, Art. no. 0174.

  6. Qunxi Zhu*, Xin Li, Wei Lin* [2023], Leveraging neural differential equations and adaptive delayed feedback to detect unstable periodic orbits based on irregularly-sampled time series, CHAOS, Fast track, 33(3), 031101. (Editor's Pick)

  7. Qunxi Zhu, Zuguang Gao, Yang Liu*, and Weihua Gui [2020], Categorization problem on controllability of Boolean control networks, IEEE Transactions on Automatic Control, 66(5), 2297-2303. (控制理论顶刊)

  8. Qunxi Zhu, Huanfei Ma, and Wei Lin* [2019], Detecting unstable periodic orbits based only on time series: When adaptive delayed feedback control meets reservoir computing, CHAOS, 29(9), 093125.

  9. Chiyu Pan, Yuanren Jiang, Qunxi Zhu, and Wei Lin* [2019], Emergent dynamics of coordinated cells with time delays in a tissue, CHAOS, Fast Track, 29(3), 031101.

  10. Qunxi Zhu, and Wei Lin* [2019], Stabilizing Boolean networks by optimal event-triggered feedback control. Systems & Control Letters, 126, 40-47.  (控制理论顶刊)

  11. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2018], Controllability and observability of Boolean control networks via sampled-data control. IEEE Transactions on Control of Network Systems, 6(4), 1291-1301.

  12. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2019], Further results on the controllability of Boolean control networks. IEEE Transactions on Automatic Control, 64(1), 440-442.  (控制理论顶刊)

  13. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2018], On the optimal control of Boolean control networks. SIAM Journal on Control and Optimization, 56(2), 1321–1341.  (控制理论顶刊)

  14. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2018], Observability of Boolean control networks. Science China Information Sciences, 61(9), 092201. (CCF A, CAA A+)


发布时间:2019-12-01 浏览次数:33
朱群喜  青年研究员  博士生导师


复旦大学智能复杂体系基础理论与关键技术实验室 青年研究员

E-mail: qxzhu@fudan.edu.cn

个人主页:qunxizhu.cn


个人简介

朱群喜, 复旦大学智能复杂体系实验室青年研究员。2021年博士毕业于复旦大学数学科学学院。2021年至2024年在复旦大学从事博士后研究工作。致力于复杂系统和机器学习前沿的理论与方法研究, 在复杂系统建模、重构、预测和智能调控以及复杂系统驱动的机器学习领域做出了一系列工作, 相关成果以第一或通讯作者在综合性、控制、数学、物理、人工智能等顶级/一流学术刊物发表文章20余篇, 包括综合性领域期刊Nature Communications (人工智能与机器学习、应用物理与数学两个方向的Featured Article), 非线性期刊CHAOS (Editor’s Pick), 物理期刊Physical Review Research/E, 自动化控制理论期刊4篇(IEEE TAC 2篇, SIAM-CON 1篇, SCL 1篇), 人工智能会议7篇(ICML 3篇, ICLR 2篇, NeurIPS 1篇, AAAI 1篇)等。研究成果得到同行大家的关注和引用 (Edward Ott、Jürgen Kurths、曹进德、桂卫华等院士, Google Research、UC Berkeley、牛津大学、剑桥大学和麻省理工等知名教授专家团队), 以及国际知名学术/科技网站的报道(Phys.org, techxplore.com)。


曾获上海市启明星(扬帆专项)计划, 上海市“超级博士后”激励计划, 脑科学前沿中心“珠峰青年学者计划”, 上海市优秀毕业生荣誉称号,研究生国家奖学金3次,多次获得国家级和省部级大数据/程序设计/建模竞赛奖项(2019年IKCEST“一带一路”国际大数据竞赛特等奖,排名1st/2312)。

研究领域

复杂系统和人工智能交叉理论与方法; Math for AI (神经微分方程、储备池计算、知识嵌入机器学习等); AI for Science (物理、控制、计算生物等)

代表性成果

会议论文

  1. Qunxi Zhu* and Wei Lin [2024], Switched flow matching: Eliminating singularities via switching ODEs, 41st International Conference on Machine Learning (ICML 2024). (CCF A,人工智能三大顶会之一,每年举办一次)

  2. Jingdong Zhang, Luan Yang, Qunxi Zhu* and Wei Lin* [2024],  FESSNC: Fast exponentially stable and safe neural controller, 41st International Conference on Machine Learning (ICML 2024). (CCF A,人工智能三大顶会之一,每年举办一次)

  3. Xin Li, Jingdong Zhang, Qunxi Zhu*, Chengli Zhao*, Xue Zhang, Xiaojun Duan, and Wei Lin [2024], From Fourier to neural ODEs: Flow matching for modeling complex systems, 41st International Conference on Machine Learning (ICML 2024). (CCF A,人工智能三大顶会之一,每年举办一次)

  4. Shunyu Liu, Jie Zhou*, Qunxi Zhu, Qin Chen, Qingchun Bai, Jun Xiao, Liang He [2024], Let's Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion Models, International Conference on Computational Linguistics (COLING 2024). (自然语言处理和计算语言学领域的顶会,每两年举办一次)

  5. Limao Xiong, Jie Zhou*, Qunxi Zhu, Xiao Wang, Yuanbin Wu, Qi Zhang, Tao Gui, Xuanjing Huang, Jin Ma, Ying Shan [2023], A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition, Findings of the Association for Computational Linguistics (ACL 2023 Findings). (自然语言处理顶会, CCF A,每年举办一次)

  6. Jingdong Zhang, Qunxi Zhu*, Wei Yang*, and Wei Lin* [2023], SYNC: Safety-aware neural control for stablizing stochastic delay-differential equations, 11th International Conference on Learning Representations (ICLR 2023). (人工智能三大顶会之一,每年举办一次)

  7. Jingdong Zhang, Qunxi Zhu*, and Wei Lin* [2022], Hamiltonian neural Koopman operator, The Symbiosis of Deep Learning and Differential Equations - Workshop DLDE @ NeurIPS 2022.

  8. Jingdong Zhang, Qunxi Zhu*, and Wei Lin* [2022], Neural stochastic control, 36th Conference on Neural Information Processing Systems (NeurIPS 2022). (CCF A,人工智能三大顶会之一,每年举办一次)

  9. Qunxi Zhu*, Yifei Shen, Dongsheng Li, and Wei Lin* [2022], Neural piecewise-constant delay differential equations, 36th AAAI Conference on Artificial Intelligence (AAAI 2022). (CCF A,每年举办一次)

  10. Qunxi Zhu*, Yao Guo*, and Wei Lin* [2021], Neural delay differential equations, 9th International Conference on Learning Representations (ICLR 2021). (人工智能三大顶会之一,每年举办一次)


期刊论文

  1. Jingdong Zhang, Luan Yang, Qunxi Zhu*, Celso Grebogi, and Wei Lin* [2024], Machine-learning-coined noise induces energy-saving synchrony, Physical Review E, Letter, vol. 110, no. 1, Art. no. L012203. (国际知名学术Phys.org报道)

  2. Xin Li, Qunxi Zhu*, Chengli Zhao*, Xiaojun Duan, Bolin Zhao, Xue Zhang, Huanfei Ma, Jie Sun, and Wei Lin* [2024], Higher-order Granger reservoir computing: Simultaneously achieving scalable complex structures inference and accurate dynamics prediction, Nature Communications, vol. 15, Art. no. 2506. (Editorially selected as a Featured Article both in NC's focus contents: AI & machine learning & Applied physics and mathematics) (国际知名科技techxplore.com报道)

  3. Jingdong Zhang, Qunxi Zhu*, and Wei Lin* [2024],  Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws, Physical Review Research, Letter, vol. 6, no. 1, Art. no. L012031. (国际知名学术Phys.org报道)

  4. Boyun Ji, Qunxi Zhu*, and Wei Lin [2023], Dimension reduction of collective attention networks, International Journal of Bifurcation and Chaos, August 14, vol. 33, no. 11, Art. no. 2350135.

  5. Xin Li, Qunxi Zhu*, Chengli Zhao*, Xuzhe Qian, Xue Zhang, Xiaojun Duan, and Wei Lin [2023], Tipping-point detection using reservoir computing, RESEARCH, vol. 6, Art. no. 0174.

  6. Qunxi Zhu*, Xin Li, Wei Lin* [2023], Leveraging neural differential equations and adaptive delayed feedback to detect unstable periodic orbits based on irregularly-sampled time series, CHAOS, Fast track, 33(3), 031101. (Editor's Pick)

  7. Qunxi Zhu, Zuguang Gao, Yang Liu*, and Weihua Gui [2020], Categorization problem on controllability of Boolean control networks, IEEE Transactions on Automatic Control, 66(5), 2297-2303. (控制理论顶刊)

  8. Qunxi Zhu, Huanfei Ma, and Wei Lin* [2019], Detecting unstable periodic orbits based only on time series: When adaptive delayed feedback control meets reservoir computing, CHAOS, 29(9), 093125.

  9. Chiyu Pan, Yuanren Jiang, Qunxi Zhu, and Wei Lin* [2019], Emergent dynamics of coordinated cells with time delays in a tissue, CHAOS, Fast Track, 29(3), 031101.

  10. Qunxi Zhu, and Wei Lin* [2019], Stabilizing Boolean networks by optimal event-triggered feedback control. Systems & Control Letters, 126, 40-47.  (控制理论顶刊)

  11. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2018], Controllability and observability of Boolean control networks via sampled-data control. IEEE Transactions on Control of Network Systems, 6(4), 1291-1301.

  12. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2019], Further results on the controllability of Boolean control networks. IEEE Transactions on Automatic Control, 64(1), 440-442.  (控制理论顶刊)

  13. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2018], On the optimal control of Boolean control networks. SIAM Journal on Control and Optimization, 56(2), 1321–1341.  (控制理论顶刊)

  14. Qunxi Zhu, Yang Liu*, Jianquan Lu, and Jinde Cao [2018], Observability of Boolean control networks. Science China Information Sciences, 61(9), 092201. (CCF A, CAA A+)