教育经历       

2000年9月-2004年7月 中国 中国科学技术大学 科技英语 学士

2006年8月-2012年8月 美国  普度大学（Purdue University）计算与应用数学 博士

工作经历

2013年3月-2015年8月 美国麻省理工大学(Massachusetts Institute of Technology) 博士后研究员Postdoctoral researcher

2015年9月-2020年7月 美国布朗大学（Brown university）博士后研究员 Postdoctoral researcher

2020年7月-至今        暨南大学信息技术学院数学系   教授

计算与应用数学

我们的研究方向是计算和应用数学，欢迎感兴趣的同学加入我们。

1.计算流体力学：发展高精度数值模拟方法，应用于复杂流动系统分析； 2.计算生物力学：开发血管流、血栓、肿瘤等数学建模计算框架； 3.人工智能驱动建模：创新深度学习与传统数值计算的融合算法； 4. AI算法：情感计算、目标检测、目标导航、故障诊断、 AI金融等；5.疾病计算建模及医学图像处理：如构建传染病传播预测与药物递送优化模型，与多家企业和医院合作，致力于将计算数学应用于工业及医疗实际问题。

SELECTED PUBLICATIONS

(*: These authors contributed equally to this work, #:corresponding author)

Google scholar website:https://scholar.google.com/citations?user=rXW31d8AAAAJ&hl=zh-CN

Scholarmate website: https://www.scholarmate.com/dynweb/main?locale=zh_CN

ORCID website: https://orcid.org/0009-0009-8786-3063

1.        Y.Qian, G.Zhu, Z.Zhang, S.Modepalli, Y.Zheng, X.Zheng, G. Frydman , H. Li*, Coagulo-Net: Enhancing the

mathematical modeling of blood coagulation using physics-informed neural networks, Neural Networks (IF:9.6), 180(106732), 2024.

https://doi.org/10.1016/j.neunet.2024.106732 (doi: 10.1016/j.neunet.2024.106732)

2. Q. Chen, H.Li, X. Zheng#, A Deep Neural Network for Operator Learning Enhanced by Attention and Gating

Mechanisms for Long-time Forecasting of Tumor Growth, Engineering with Computers (IF: 8.0), 1-111, 2024.

3. Q. Chen, Q.Ye, W.Zhang, H.Li, X. Zheng#, TGM-Nets: A Deep Learning framework for enhanced forecasting

of tumor growth by integrating imaging and Modeling, Engineering Applications of Artificial Intelligence (IF: 7.8), 126, 106867, 2023.

4.  K.Boster,S.Cai,A.Guevara,J.Sun,X.Zheng,M.Nedergaard,D.Kelley, G.E.Karniadakis, Artificial Intelligence velocimetry reveals invivo pressure gradients in brain cerebrospinal fluid,120(14),e2217744120,  ProceedingsoftheNational Academyof Sciences (IF:11.2), 2022.

5.  E.Kharazmi.,M.Cai,X.Zheng,Z.Zhang,G.Lin,G.E.Karniadakis,Identifiability and predictability of integer-and fractional-order epidemiological models using physics-informed neural networks, Nature Computational Science (IF:12.0),1(11), 744-753, 2021.

6.  X.Zheng,Z.Wang,M.S.Triantafyllou,G.E.Karniadakis,Fluid-elastic instability of a horizontal flexible pipe conveying two-phaseflow, International Journal of Multiphase Flow (IF:3.6), 141, 103667, 2021.

7.  Z.Wang,X.Zheng,C.Chryssostomidis,G.E.Karniadakis,Aphase-field

method for boilingheat transfer,Journal of Computational Physics (IF:3.8), 435, 110239, 2021.

8.  M.Yin,X.Zheng,J.D.Humphrey,G.E.Karniadakis,Non-invasive inference of thrombus material properties with physics-informed neural networks,Computer Methods in Applied Engineering and Mechanics (IF:6.5), 375, 113603, 2021.

9.  M. Carlson*, X. Zheng*,H. Sundar, M. Kirby, G.E. Karniadakis, An open-source parallel code for computingthe fractional Laplacian on 3D complex-geometry domains,261, 107695, Computer Physics Communications (IF:7.2), 2021.

10. H.Li*,K.Sampani*,X.Zheng*,D.P.Papageorgiou,A.Yazdani,M.O.Bernabeu,G.E.Karniadakis,J.K.Sun,Predictive modeling of thrombus formation in diabetic retinal microaneurysms,Journal of the Royal Society

Interface (IF:4.3), 7(8), 201102, 2020.

11. Konstantina Sampani, He Li, Xiaoning Zheng, Dimitrios Papageorgiou, Miguel Oscar Bernabeu, Ward Fickweiler, Lloyd Paul Aiello, George Karniadakis, Jennifer K Sun,Computational fluid dynamics (CFD) estimation of thrombus formation in diabetic retinal microaneurysms (MAs),Investigative Ophthalmology & Visual Science, 61(7), 5023-5023，2020.

12. X. Zheng,A. Yazdani, H.Li,J.D. Humphrey, G.E. Karniadakis, A 3D phase-field

model for multiscale simulation ofthe interaction between blood and thrombus in arterial vessels, PLoS Computational Biology (IF:3.8), 16,e1007709,2020.

13.  A.Lischke,G. Pang, M.Gulian, F.Song, C. Glusa,X. Zheng,Z.Mao, W. Cai,

M. Ainsworth, G. E. Karniadakis. What isthe fractionalLaplacian?A comparativereviewwith newresults. Journal of Computational Physics (IF:3.8), 404, 109009, 2020.

14.  F.Xie,X.Zheng,M.S.Triantafyllou,Y.Constantinides,Y.Zheng,G.E. Karniadakis.DNSoftwo-phaseflowinaninclinedpipe.Journal of Fluid Mechanics (IF:3.6), 825,189-207, 2017.

15.  X. Zheng, G. E.Karniadakis. A phase-field/ALEmethod for simulatingfluid-

structureinteractions intwo-phaseflow. Computer Methods in Applied Engineering

and Mechanics (IF:6.5), 309, 19-40,2016.

16.  F.Xie, X.Zheng, M. S.Triantafyllou, Y. Constantinides, G.E. Karniadakis, The

flowdynamics of thegarden-hoseinstability. Journal of Fluid Mechanics (IF:3.6),800, 595-612, 2016.

17.  X. Zheng, H. Babaee, S. Dong,C. Chryssostomidis, G. E. Karniadakis. A Phase-

Field Methodfor3DSimulation ofTwo-PhaseHeatTransfer.International Journal

of Heat and Mass Transfer (IF:5.2), 82,282-298, 2015.

18.  Dong, S., & X. Zheng. Direct numerical simulation of spiral turbulence.

Journal of fluid mechanics (IF:3.6), 668, 150-173,2011.

19.  X. Zheng., & Dong, S. An eigen-based high-order expansion basis for

structured spectral elements. Journal of Computational Physics (IF:3.8), 230(23), 8573-8602,2011.

20.  Xin, Y. P., Liu, J., & X. Zheng. A cross‐cultural lesson comparison on teaching the

connection between multiplication and division. School Science and Mathematics, 111(7), 354-367,2011.

Google scholar website:https://scholar.google.com/citations?user=rXW31d8AAAAJ&hl=zh-CN

Scholarmate website: https://www.scholarmate.com/dynweb/main?locale=zh_CN

ORCID website: https://orcid.org/0009-0009-8786-3063

Instructor