Jifan Shi (史际帆）
Assistant Professor (tenure track), Research Institute of Intelligent Complex Systems, Fudan University. (2022.5- )
Researcher, Shanghai Artificial Intelligence Laboratory. (2023.4-)
Project Researcher, International Research Center for Neurointelligence (IRCN), The University of Tokyo Institutes for Advanced Study, The University of Tokyo.(2020.4-2022.3)
Project Researcher, Institute of Industrial Science (IIS), the University of Tokyo. (2018.4-2020.3)
PhD degree of Computational Mathematics, School of Mathematical Sciences, Peking University.
Bachelor degree of Information and Computing Science, School of Mathematical Sciences, Peking University.
Research Interests:
Stochastic modeling, algorithms and their applications; Mathematical theory in biology and life sciences.
Complex network inference: constructing undirected/directed networks, quantifying dynamical causality, inferring gene regulations etc.
Critical phenomena analysis: critical transition, tipping point, early-warning signal etc.
Biological data modeling and analysis: scRNA-seq, multi-omics data, EEG/fMRI data etc.
Publications
Detecting dynamical causality by intersection cardinal concavity. Peng Tao#, Qifan Wang#, Jifan Shi#, Xiaohu Hao, Xiaoping Liu, Bin Min, Yiheng Zhang, Chenyang Li, He Cui*, and Luonan Chen*. Fundamental Research, https://doi.org/10.1016/j.fmre.2023.01.007, (2023).
Energy landscape decomposition for cell differentiation with proliferation effect. Jifan Shi, Kazuyuki Aihara*, Tiejun Li*, and Luonan Chen*. National Science Review 9: nwac116, DOI: 10.1093/nsr/nwac116, (2022). (Preprint, SI, IICSnews, NSRnews).
Mean-field analysis of Stuart-Landau oscillator networks with symmetric coupling and dynamical noise. Yang Li*, Jifan Shi, and Kazuyuki Aihara. Chaos 32, 063114, (2022).
Embedding entropy: a nonlinear measure of dynamical causality. Jifan Shi*, Luonan Chen*, and Kazuyuki Aihara*. Journal of the Royal Society Interface. 19, 20210766(2022). (Preprint, SI, code)
Criticality in the healthy brain. Jifan Shi*, Kenji Kirihara, Mariko Tada, Mao Fujioka, Kaori Usui, Daisuke Koshiyama, Tsuyoshi Araki, Luonan Chen, Kiyoto Kasai*, and Kazuyuki Aihara*. Frontiers in Network Physiology, section Networks of Dynamical Systems. 1, 755685, (2022). (SI)
Dynamics-based data science in biology. Jifan Shi, Kazuyuki Aihara, and Luonan Chen*. Natl Sci Rev. 8(5), nwab029, (2021). (a brief news report).
On the Mathematics of RNA Velocity I: Theoretical Analysis. Tiejun Li*, Jifan Shi*, Yichong Wu*, and Peijie Zhou*. CSIAM Trans. Appl. Math. 2(1), 1-55, (2021). (pdf)
Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process. Jifan Shi, Tiejun Li*, Luonan Chen*, and Kazuyuki Aihara*. PLoS Comput. Biol. 15(11), e1007488, (2019). (SI, code)
Quantifying Waddington’s epigenetic landscape: a comparison of single-cell potency measures. Jifan Shi, Andrew E Teschendorff*, Weiyan Chen, Luonan Chen*, and Tiejun Li*. Brief. in Bioinformatics. 21(1), 248-261, (2020). (SI, code)
关于临界现象和强相关网络推断的多尺度建模与分析 (Multiscale modeling and analysis of critical transitions and network inference with strong connections). Jifan Shi. 北京大学博士学位论文(PhD thesis, in Chinese), (2018). (pdf)
Quantifying direct dependencies in biological networks by multiscale association analysis. Jifan Shi, Juan Zhao, Xiaoping Liu, Luonan Chen*, and Tiejun Li*. IEEE/ACM Trans. Comp. Biol. Bioinfo. 17(2), 449-458, (2020). (pdf, SI, code).
Detecting direct associations in a network by information theoretic approaches. Jifan Shi#, Juan Zhao#, Tiejun Li*, and Luonan Chen*. Sci. China Math. 62(5), 823-838, (2019).
Towards a critical transition theory under different temporal scales and noise strengths. Jifan Shi, Tiejun Li*, and Luonan Chen*. Phys. Rev. E 93(3), 032137, (2016).
Funds:
National Natural Science Foundation of China (NSFC), No. 12301620. 2024/01 --- 2026/12, PI.
National Key R&D, 2022YFC2704600/2022YFC2704604. Ministry of science and technology (MOST). 2022/12 --- 2025/11, Sub-project Core Member.
Comprehensive Mathematical Understanding of the Complex Control System between Organs and Challenge for Ultra-Early Precision Medicine. Japan Science and Technology Agency (JST). Moonshot Research & Development Program, JPMJMS2021. 2020/12 --- 2025/11, direct costs 1,530,100,000 yen. Participants.
Research and Development on Next-generation AI and its Key Technology Based on Nonlinear Dynamics. Japan Agency for Medical Research and Development (AMED). Strategic Research Program for Brain Sciences, JP21dm0307009. 2018/06 --- 2024/03, direct costs 94,500,000 yen. Participants.
Establishing Theoretical Foundations for Mathematical Modeling of Pathological Biosystems and its Applications to Personalized Medicine. Japan Society for the Promotion of Science (JSPS). Grant-in-Aid for Scientific Research (S), JP15H05707. 2015/05 --- 2020/03, direct costs 148,000,000 yen. Participants.
Membership:
Chinese Mathematical Society (CMS)
China Society for Industrial and Applied Mathematics (CSIAM)
Operations Research Society of China (ORSC)
Shanghai Society of Nonlinear Sciences
Academic Activities:
The 3rd Mathematical Life Science Conference (MLS2023), Oct. 20-22, 2023, Wuxi, China.
The 21st Annual Meeting of China Society for Industrial and Applied Mathematics (CSIAM2023), Oct. 12-15, 2023, Kunming, China.
The 10th International Congress on Industrial and Applied Mathematics (ICIAM2023), Aug. 20-25, 2023, Waseda University, Tokyo, Japan.
† The 9th Shanghai International Symposium on Nonlinear Sciences and Applications (Shanghai NSA’23), July 23-28, 2023, Zhangye, Gansu Province, China.
The 342nd Shuangqing Forum of NSFC, July 9-11, 2023, Peking, China.
The 7th China System Science Conference (CSSC2023), May 19-21, 2023, Chongqing, China.
The 4th International Conference on Biomathematical Modelling and Stochastic Analysis, Apr. 28-30, 2023, Xuzhou, China.
The 1st Yangtze River Delta Academic Conference of Bioinformatics, Apr. 14-16, 2023, Huzhou, China.
† Symposium on Biological Mathematics and Computational Systems Biology 2022, held by IICS Fudan, Dec. 17-18, 2022, Online.
The 20th Annual Meeting of China Society for Industrial and Applied Mathematics (CSIAM2022), Nov. 17-20, 2022, Online.
NetSci2022, NetBioMed2022 Satellite, July 18-19, 2022, Online.
Workshop of Collective Dynamics and Networks, June 10-12, 2022, Online.
The 10th International Conference on Bioinformatics and Computational Biology (ICBCB2022), May 13-15, 2022, Online.
The 2nd CSIAM Conference of Mathematics and Life Science, Aug. 28-29, 2021, Online.
The 13th International Conference on Computational Systems Biology (ISB2020), Sep.18-21, 2020, Online.
The 12th International Conference on Computational Systems Biology (ISB2018), Aug.18-21, 2018, Guiyang, China.
The 11th International Conference on Computational Systems Biology (ISB2017), Aug.18-21, 2017, Shenzhen, China.
The 11th Annual Meeting of Chinese Computational Mathematical Society, July 21-23, 2017, Xi'an, China.
SIAM Conference on the Life Sciences (LS16), July 11-14, 2016, Boston, Massachusetts, USA.
The 9th International Conference on Systems Biology (ISB2015), Aug.21-24, 2015, Luoyang, China.
The 8th International Congress on Industrial and Applied Mathematics (ICIAM 2015), Aug. 10-14, 2015, Beijing, China.
The 12th annual meeting for CompMath in Chinese Universities, Oct. 19-23, 2013, Changsha.
† As an organizer.
Links:
Prof. Tiejun Li, Prof. Luonan Chen, Prof. Wei Li, Dr. Yang Li, Dr. Juan Zhao.
scRNA-seq:
Analysis of single cell RNA-seq data. A course by Hemberg-lab, with codes on github.
Datasets: Single Cell Expression Atlas, Single Cell Portal, Human Cell Atlas, SC2disease, CancerSEA, JingleBells, SpatialDB
EEG:
Database: OpenNeuro, EPR Core, European Epilepsy Database, Kaggle Seizure, TUH EEG, others(1, 2)
Others:
Deep learning tutorials: (i) Deep learning tutorial (Hung-yi Lee's ppt); (ii) MorvanZhou's programming; (iii) Tensorflow; (iv) Pytorch.
*Last Modified: Dec. 2023.