Dr. Yanlai Chen

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Biography

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Yanlai Chen received his B.S. degree in Mathematics from University of Science and Technology of China (USTC), in 2002, M.S. in Computer Science and Engineering from Department of Computer Science and Engineering , and Ph.D. in Mathematics from School of Mathematics, University of Minnesota, in 2007. Prof. Cockburn, Bernardo was his thesis advisor. He then worked as a Postdoctoral Researcher supervised by Prof. Hesthaven Jan and Prof. Maday, Yvon at Brown University. Dr. Chen joined Department of Mathematics, University of Massachusetts Dartmouth in August 2010, as an Assistant Professor in Mathematics. He was subsequently promoted to Associate Professor with tenure and then to Full Professor.

Dr. Chen's administrative experience includes serving as a (Co-)Graduate Program Director of the Engineering and Applied Science program from September 2020 to June 2024, and as a Co-Director of the Center for Scientific Computing and Data Science Research from January to July of 2022. In Spring 2024, Chen was appointed Chief Research Officer of UMass Dartmouth, effective 07/01/2024.

Outside of work and spending time with his family, Dr. Chen enjoys running and serving his communities including via roles of school council and board of trustees members. He finished Boston Marathon in 2023 with a time 3:04:41.

Research Interests

  • 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
The views and opinions expressed in this page are strictly those of the page author. The contents of this page have not been reviewed or approved by the University of Massachusetts, Dartmouth.
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Research Supported By

  • National Science Foundation (DMS-1216928, DMS-1719698, DUE-2030552, DMS-2208277)
  • AFOSR (FA9550-25-1-0181)
  • UMass Dartmouth MUST program, established by Dr. Ramprasad Balasubramanian , sponsored by ONR, Co-PI / Team member
  • UMass Dartmouth Chancellor's Research Fund and Joseph P. Healey Endowment Grants (2011 - 2012)
  • A startup fund from college of arts and science (2010 - 2013)
  • UMassD multidisciplinary seed funding program (Spring 2014)
  • UMass President's office Science and Technology initiative funds (2013 - 2014)

Related Profiles

MathSciNet Google Scholar ResearchGate ORCID

Major Related Links

Helpful Advice and Tips

  • Advice for and Expectations from New and Current Students: Modest Advice from Dorsa Amir (HTML PDF);   Advice from Dr. Jan Hesthaven (HTML PDF)
  • A detailed checklist for paper writing (prepared by Dr. Zheng Zhang from UCSB). HTML   PDF

Published and Submitted Articles

View Full List on Google Scholar
Research Topics (Based on Titles)

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Some Journals in My Field

m2an
JSC
JUQ
imajna
ANum
CAMWA
mcom
CRAS
CMAME
SISC
JCP
ICOSAHOM
cicp
sinum
bit
FoCM
MMS
SIREV
Group Gallery

Postdoctoral Researchers

Mrad
Dr. Preskella Mrad

Preskella is a Postdoctoral Researcher who joined in Spring 2026.

Current Graduate Students

Gillcrist
David Gillcrist

David is a PhD student who started in Fall 2020, jointly advised with Mazdak Tootkaboni from Civil Engineering

Zheng
Haolan Zheng

Haolan a PhD student who started in Fall 2023.

Tariq
Muhammad Shan Tariq

Shan is a PhD student who started in Fall 2024, jointly advised with Bo Dong from Mathematics

Shu
Hai-Shuo Shu

Hai-Shuo is a PhD student who started in Fall 2024, jointly advised with Zheng Chen from Mathematics

Graduate Student Alumni

Ji
Yajie Ji

Yajie is a Doctoral student at the Shanghai Jiaotong University jointly advised with Zhenli Xu.

Upon graduation in Summer 2025, Yajie started working as a Postdoc at Yale.

Hou
Shijin Hou

Shijin is a Doctoral student at the University of Science and Technology of China jointly advised with Yinhua Xia.

Upon graduation in Summer 2024, Shijin started working as an Assistant Professor at Henan University.

Pereira
Rebecca Pereira

Rebecca is a PhD student starting in Fall 2017. In Summer 2017, she worked on fast algorithms for geometric engineering design under uncertainty, jointly with Mazdak Tootkaboni from Civil Engineering. In Summer 2018, she started a project on (Hybridizable) discontinuous Galerkin method, jointly with Bo Dong from Mathematics.

Upon graduation in Spring 2023, Rebecca started working at a federal agency

Bellizzi
Richard Bellizzi

With Alfa Heryudono being the main advisor, Richard is a part-time PhD student and an employee at Nye Lubricants.

Richard is currently working on building mathematical models and implementing machine learning algorithms for lubricant manufacturing.

Upon graduation in Spring 2023, Richard has been continuing his career in the lubricant industry.

Lijie
Lijie Ji

Lijie was a Doctoral student at the Shanghai Jiaotong University jointly advised with Zhenli Xu . She has been working on reduced basis method and reduced over collocation method since early 2018, and visited the CHEN lab from September 2019 to September 2020.

Upon graduation in 2021, Lijie worked as a Wu Wen-Tsun Assistant Professor at the Shanghai Jiaotong University

Jiang
Jiahua Jiang

Co-advised with Akil Narayan and working also under the guidance of Bo Dong , Jiahua focused on uncertainty quantification, and model order reduction. She started her doctoral study in Fall 2013, and graduated in Summer 2018.

Jiahua's research has been supported by a fellowship from the Center for Scientific Computing and Visualization Research at UMassD, an NSF grant, and a UMassD Multi-disciplinary seed fund (MSF).

Jiahua worked as a PostDoc at Virginia Tech University upon graduation in 2018, and is now an assistant professor at the University of Birmingham.

Bresten
Christopher Bresten

Co-advised with Sigal Gottlieb and graduated in 2017, Chris was a PhD student working on model order reduction for nonlinear and nonaffine problems. He started this project in Fall 2012.

Chris's research has been supported in part by an NSF grant.

Chris is currently a PostDoc in Korea.

Undergraduate Student Alumni

Koohy
Shawn Koohy

Supported by an NSF grant, Shawn was a sophomore when he started exploring neural networks in Spring 2022. He graduated in 2024 and started pursuing his doctoral degree at UPenn.

Parenteau
Chase Parenteau

Chase is a honors student admitted to the university in 2018. He worked on mathematical models and machine learning algorithms for sports analytics in Spring 2019 and beyond.

Jonathan
Jonathan Curtis

Jonathan is analyzing and implementing GPU-accelerated Reduced Basis Method. He started in Summer 2017.

Jonathan's research has been supported by the department of mathematics, UMassD.

Ian
Ian Camerlin

Ian is implementing GPU algorithms. He started in Summer 2014.

Ian's research has been supported by an NSF grant. Ian graduated in 2016 and took a job in industry.

Peter
Peter Takahashi

Peter started in Summer 2014 working on reduced basis type of model reduction techniques for data science.

Peter's research was partially supported by the President's S&T grant. Peter chose to pursue his interests in computer science starting from Fall 2015. He graduated in 2017 and is a graduate student at Yale University.

Jacob
Jacob Sousa

Advised by and working with Alfa Heryudono before Spring 2014, Jacob worked with me on modeling and its reduction for a computational biology project in Spring 2014.He is now an EAS PhD student at the University of Massachusetts Dartmouth.

Jacob's research was supported by the UMassD Multi-disciplinary seed funding (MSF) program.

Davey
Andrew Davey

Andrew mainly focused on implementing successive constraint methods in the collocation framework and devising appropriate variants. He started in Summer 2012 and left in Summer 2014 being awarded a Ben L. Fryrear Fellowship in Computational Science to pursue his PhD degree at the Colorado School of Mines.

Andrew's research was mainly supported by an NSF grant and also by UMassD's Multidisciplinary Seed Funding (MSF) program.

See below for a brief OUR (Office of Undergraduate Research) interview of Andrew talking about his experience at UMassD.

Kumar
Rushendra Kumar

Rushendra was a summer intern in 2012 coming from Indian Institute of Technology, Bhubaneswar. He is now at Springforth Capital Advisors in the Bhubaneshwar Area of India.

Office Location: Foster 008
Phone Number: x8827

Dedication to Teaching and Advising

  • Thanks to National Science Foundation, via grant DUE-2030552, we have established the ACCOMPLISH whose mission is to provide a multi-faceted financial and social support and contextualized computing-centered educational framework for eligible STEM students to propel them into the nation's high-quality STEM workforce.

Navigating this page

My Schedule

Current Teaching

  • See UMassD myCourses for the class webpages.

Sample Video of In-Class Lectures (Fall 2019)

Resources for Deep Learning (To be Updated)

Research supported by

  • National Science Foundation (DMS-1216928, DMS-1719698, DUE-2030552, DMS-2208277)
  • AFOSR (FA9550-25-1-0181)
  • UMass Dartmouth MUST program, established by Dr. Ramprasad Balasubramanian , sponsored by ONR (2020 - 2023), Co-PI / Team member.
  • UMass Dartmouth Chancellor's Research Fund and Joseph P. Healey Endowment Grants (2011 - 2012)
  • A startup fund from college of arts and science (2010 - 2013)
  • UMassD multidisciplinary seed funding program (Spring 2014)
  • UMass President's office Science and Technology initiative funds (2013 - 2014)

Software Packages

GPT-PINN

See here for the paper on ResearchGate.

A NA G-ROMs talk given on 5/16/2023 on GPT-PINN:

TGPT-PINN

See here for the paper on ResearchGate.

The DDPS Webinar given at the Livermore Lab on 4/5/2024 on GPT-PINN and TGPT-PINN

A user-friendly page containing the Matlab test code using Reduced Basis Decomposition (RBD) for data compression (see paper   Reduced Basis Decomposition: a Certified and Fast Lossy Data Compression Algorithm.): Reduced Basis Decomposition page.

  • Sample applications of RBD
    • Lossy image compression and greedy face recognition FR_RBD page.

The suite of Matlab code for the reduced collocation method (see paper   Reduced Collocation Methods: Reduced Basis Methods in the Collocation Framework.) is available for download at RCM Software Page

Research Talks (Video)

Misc. Slides

  • Spring 2012 open house lecture at UMass Dartmouth is available here.
  • Spring 2014 open house lecture at UMass Dartmouth is available here.

Contact Information

Yanlai Chen
Office: Foster 008
Office of Research and Innovation
University of Massachusetts, Dartmouth
285 Old Westport Road
North Dartmouth, MA 02747

Phone: 1-508-999-8827
Fax: 1-508-999-8868
E-mail: first.last@umassd.edu