Yanlai Chen
Scholar

Yanlai Chen

Google Scholar ID: YRYmr8cAAAAJ
Professor of Mathematics, University of Massachusetts Dartmouth
Scientific ComputingNumerical AnalysisReduced Basis MethodDiscontinuous Galerkin Finite Element MethodAdaptivity
Citations & Impact
All-time
Citations
548
 
H-index
13
 
i10-index
20
 
Publications
20
 
Co-authors
28
list available
Resume (English only)
Academic Achievements
  • Grants from National Science Foundation (DMS-1216928, DMS-1719698, DUE-2030552, DMS-2208277)
  • Grant from AFOSR (FA9550-25-1-0181)
  • Co-PI/Team member of UMass Dartmouth MUST program established by Dr. Ramprasad Balasubramanian and sponsored by ONR
  • UMass Dartmouth Chancellor's Research Fund and Joseph P. Healey Endowment Grants (2011–2012)
  • Startup fund from College of Arts and Sciences (2010–2013)
  • UMassD multidisciplinary seed funding (Spring 2014)
  • UMass President's Office Science and Technology initiative funds (2013–2014)
  • Publications include: 'Reduced Basis Methods for Parametric Steady-State Radiative Transfer Equation', 'Derivative-informed Graph Convolutional Autoencoder with Phase Classification for the Lifshitz-Petrich Model', 'ReBaNO: Reduced Basis Neural...'
Research Experience
  • Postdoctoral Researcher at Brown University under the supervision of Prof. Jan Hesthaven and Prof. Yvon Maday
  • Joined University of Massachusetts Dartmouth, Department of Mathematics as Assistant Professor in August 2010
  • Subsequently promoted to Associate Professor with tenure and then to Full Professor
  • Served as (Co-)Graduate Program Director of the Engineering and Applied Science program from September 2020 to June 2024
  • Co-Director of the Center for Scientific Computing and Data Science Research from January to July 2022
  • Appointed Chief Research Officer of UMass Dartmouth in Spring 2024, effective July 1, 2024
Background
  • Research interests include: Numerical Analysis, Scientific Computing, Computational Partial Differential Equations
  • Dimension reduction, Data mining, Scientific Machine Learning, Data visualization
  • Neural networks, Meta learning
  • Conservation Laws, Hamilton-Jacobi-like equations and applications
  • Finite Element Discontinuous Galerkin Method, Adaptive numerical methods
  • Reduced Basis Methods, Reduced Basis Element Methods and Applications
  • Computational Electromagnetism
  • Mixed Finite Element Methods, Hybridizable Discontinuous Galerkin Methods
  • Uncertainty quantification, Fractional-order partial differential equations