Guang Lin  CV

Associate Professor

Department of Mathematics & School of Mechanical Engineering

Purdue University

150 N. University Street,

West Lafayette, IN 47907-2067

Office: Math 410

Office phone: +1 765 49-41965
Email: guanglin at purdue dot edu


Professional activities

   Workshop on the Current Trends and Challenges in Data Science and Uncertainty Quantification, Purdue, Mar. 31, 2018

Current Teaching:

Past Teaching:



Ph.D, 2007, Applied Mathematics, Brown University

M.S., 2004, Applied Mathematics, Brown University

M.S., 2000, Mechanics and Engineering Science, Peking University, P.R. China

B.S., 1997, Mechanics, Zhejiang University, P.R. China


Research Interest


1.     Big data analysis and statistical machine learning

2.    Predictive modeling and uncertainty quantification

3.    Scientific computing and computational fluid dynamics

4.    Stochastic multiscale modeling


My research interests include diverse topics in computational and predictive science and statistical learning both on algorithms and applications. A main current thrust is stochastic simulation (in the context of uncertainty quantification, statistical learning and beyond), and multiscale modeling of physical and biological systems (e.g., blood flow). My research goal is to develop high-order numerical algorithms to promote innovation with significant potential impact and design highly-scalable numerical solvers on petascale supercomputers to investigate new knowledge discovery and predictive modeling for critical decision making in complex physical and biological complex systems.




1.     NSF CAREER Award, 2016

2.    Mentor for Purdue undergraduate team, awarded the Prize of Finalist in the MCM math modeling contest2016

3.    Mathematical Biosciences Institute Early Career Award, 2015

4.    Ronald L. Brodzinski Award for Early Career Exception Achievement, Department of Energy Pacific Northwest National Laboratory, 2012.

5.    Early Career Award, Department of Energy Pacific Northwest National Laboratory2012.

6.    Advanced Scientific Computing Research Leadership Computing Challenge (ALCC) award, Department of Energy 2010.

7.     Outstanding Performance Award, Department of Energy Pacific Northwest National Laboratory, 2010.

8.    Ostrach Fellowship, Brown University, 2005.


Current Research Grants


1   Career: Uncertainty Quantification and Big Data Analysis in Interconnected Systems: Algorithms, Computations, and Applications, 2016 National Science Foundation (NSF) Faculty Early Career Development (CAREER) award, 2016-2021

2   2015 Mathematical Biosciences Institute Early Career Award, PI: Guang Lin, Sep.-Dec., 2015

3   Subcontract from Department of Energy Pacific Northwest National Laboratory on following two DOE Math Center grants, 2014-2017.

·       DOE Math Center grant on Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4) project.

·       DOE Math Center grant on Multifaceted Mathematics for Complex Energy Systems (M2ACS) project 


4   Startup Fund from Purdue University 2014-2019

To Applicants

Graduate students and postdoc positions are available in my group. If you are interested in machine learning, big data analysis, uncertainty quantification & predictive modeling, welcome to contact me via email.