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Biography: CV in PDF

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 promoted to Associate Professor with tenure in September 2016, and to Full Professor in September 2021.

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 Interest:

Numerical Analysis, Scientific Computing, Computational Partial Differential Equations

Dimension reduction, Data mining, 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.

Research supported by

National Science Foundation (DMS-1216928, DMS-1719698, DUE-2030552, DMS-2208277)
AFOSR (FA9550-18-1-0383), PI Gottlieb
UMass Dartmouth MUST program, established by Dr. Ramprasad Balasubramanian , sponsored by ONR (2020 - 2023), PI Heryudono
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

Major related links

Navigating this page

Helpful advices and tips.
List of publications (Please shoot me an email if a preprint you want is not online.)
Brief description of my main research areas

Helpful advices 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

Manuscripts submitted

Title	Author		arXiv/Preprint

Some journals in my field

Published articles

Title	Author	Journal	DOI / arXiv
Design of Experiments via Multi-Fidelity Surrogates and Statistical Sensitivity Measures	D. Gillcrist N. Alemazkoor Y. Chen M. Tootkaboni	Journal of Machine Learning for Modeling and Computing
A reduced basis warm-start iterative solver for the parameterized linear system	S. Hou Y. Chen Y. Xia	Beijing J. of Pure and Appl. Math.	arXiv: 2311.13862
MCMS-RBM: Multi-Component Multi-State Reduced Basis Method toward Efficient Transition Pathway Identification for Crystals and Quasicrystals	Y. Ji L. Ji Y. Chen Z. Xu	SIAM J. Sci. Comput.	arXiv: 2308.15195
TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs	Y. Chen Y. Ji A. Narayan Z. Xu	Comput. Methods Appl. Mech. Engrg.	arXiv: 2403.03459 doi.org/10.1016/j.cma.2024.117198
A micro-macro decomposed reduced basis method for the time-dependent radiative transfer equation	Z. Peng Y. Chen Y. Cheng F. Li	SIAM Multiscale Modeling & Simulation	arXiv: 2211.04677 doi.org/10.1137/22M1533487
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs	Y. Chen S. Koohy	Finite Elements in Analysis and Design	arXiv: 2303.14878 DOI 10.1016/j.finel.2023.104047
A fully conservative discontinuous Galerkin method via implicit penalization for the generalized KdV equation	Y. Chen B. Dong R. Pereira	SIAM J. Num. Anal.	arXiv: 2211.05893 DOI 10.1137/22M1470827
Fast L2 optimal mass transport via reduced basis methods for the Monge-Ampere equation	S. Hou Y. Chen Y. Xia	SIAM J. Sci. Comput.	arXiv: 2112.01878 DOI 10.1137/21M1463720
A hyper-reduced MAC scheme for the parametric Stokes and Navier-Stokes equations	Y. Chen L. Ji Z. Wang	J. Comput. Phys.	arXiv: 2110.11179 DOI 10.1016/j.jcp.2022.111412
A reduced basis method for radiative transfer equation	Z. Peng Y. Chen Y. Cheng F. Li	J. Sci. Comput.	arXiv: 2103.07574 DOI 10.1007/s10915-022-01782-2
An EIM-degradation free reduced basis method via over collocation and residual hyper reduction-based error estimation	Y. Chen S. Gottlieb L. Ji Y. Maday	J. Comput. Phys.	arXiv: 2101.05902 DOI 10.1016/j.jcp.2021.110545
L1-based reduced over collocation and hyper reduction for steady state and time-dependent nonlinear equations	Y. Chen L. Ji A. Narayan Z. Xu	J. Sci. Comput.	arXiv: 2009.04812 DOI 10.1007/s10915-021-01416-z
Model reduction for fractional elliptic problems using Kato's formula	H. Dinh H. Antil Y. Chen E. Cherkaev A. Narayan	Math. Control Relat. Fields, To Appear	arXiv: 1904.09332 DOI 10.3934/mcrf.2021004
Adaptive greedy algorithms based on parameter-domain decomposition and reconstruction for the reduced basis method	J. Jiang Y. Chen	Internat. J. Numer. Methods Engrg. To Appear	arXiv: 1911.02214 DOI 10.1002/nme.6544
Certified reduced basis methods for fractional Laplace equations via extension	H. Antil Y. Chen A. Narayan	SIAM J. Sci. Comput.	arXiv: 1808.00584 DOI 10.1137/18M1204802
Certified offline-free reduced basis (COFRB) methods for stochastic differential equations driven by arbitrary types of noise	Y. Liu T. Chen Y. Chen C.-W. Shu	J. Sci. Comput., To Appear	Preprint DOI 10.1007/s10915-019-00976-5
A reduced basis method for the nonlinear Poisson-Boltzmann equation	L. Ji Y. Chen Z. Xu	Advances in Applied Mathematics and Mechanics, To Appear.	arXiv: 1808.09392 DOI 10.4208/aamm.OA-2018-0188
A robust error estimator and a residual-free error indicator for reduced basis methods	Y. Chen J. Jiang A. Narayan	Computers and Mathematics with Applications, To Appear.	arXiv: 1710.08999 DOI 10.1016/j.camwa.2018.11.032
A Foreword to the Special Issue in Honor of Professor Bernardo Cockburn on His 60th Birthday: A Life Time of Discontinuous Schemings	Y. Chen B. Dong C.-W. Shu	Foreword to a special issue J. Sci. Comput.	DOI 10.1007/s10915-018-0845-0
A Hybridizable discontinuous Galerkin method for the Fifth-order Korteweg de-Vries equation	B. Dong J. Jiang Y. Chen	ESAIM: M2AN	arXiv: 1710.07734 DOI 10.1051/m2an/2018037
Offline-Enhanced Reduced Basis Method through adaptive construction of the Surrogate Training Set	J. Jiang Y. Chen A. Narayan	J. Sci. Comput. (to appear) (2017)	arXiv: 1703.05683 DOI 10.1007/s10915-017-0551-3
A goal-oriented RBM-Accelerated generalized polynomial chaos algorithm	J. Jiang Y. Chen A. Narayan	SIAM/ASA JUQ 4 (2016), no. 1, 1398 -- 1420.	arXiv Preprint JUQ Link
A new discontinuous Galerkin method, conserving the discrete H²-norm, for third-order linear equations in one space dimension	Y. Chen B. Cockburn B. Dong	IMA J Numer Anal (2016) 36 (4): 1570 - 1598.	doi: 10.1093/imanum/drv070
A Certified Natural-Norm Successive Constraint Method for Parametric Inf-Sup Lower Bounds	Y. Chen	Applied Numer. Math. 99 (2016) 98 - 108.	doi: 10.1016/j.apnum.2015.09.003 arXiv Preprint
Reduced Basis Decomposition: a Certified and Fast Lossy Data Compression Algorithm	Y. Chen	Computers and Mathematics with Applications 70 (2015) 2566 - 2574.	doi: 10.1016/j.camwa.2015.09.023 Corresponding downloadable software page. arXiv Preprint
[Refereed Proceedings] Using Visualization and Analysis with Efficient Dimension Reduction to Determine Underlying Factors in Hospital Inpatient Procedure Costs	M. Perkins Y. Chen	2015 IEEE Conference on Visual Analytics Science and Technology (VAST) vol. 00, pp. 205-206, 2015	doi:10.1109/VAST.2015.7347680 PDF at IEEExplore
Superconvergent HDG methods for linear, stationary, third-order equations in one-space dimension	Y. Chen B. Cockburn B. Dong	Math. Comp. 85 (2016), 2715 - 2742.	Link
A reduced radial basis function method for partial differential equations on irregular domains	Y. Chen S. Gottlieb A. Heryudono A. Narayan	J. Sci. Comput. (2016) 66(1):67 - 90.	Link arXiv Preprint
Parametric Analytical Preconditioning and its Applications to the Reduced Collocation Methods	Y. Chen S. Gottlieb Y. Maday	C. R. Acad. Sci. Paris, Ser. I 352 (2014) 661 - 666.	doi: 10.1016/j.crma.2014.06.001 arXiv Preprint
Analysis of variable-degree HDG methods for Convection-Diffusion equations. Part II: Semimatching nonconforming meshes	Y. Chen B. Cockburn	Math. Comp. (2014) 83 (285) 87 - 111.	Link
[Education Journal] Transformation of a Mathematics Department's Teaching and Research Through a Focus on Computational Science	Y. Chen G. Davis S. Gottlieb A. Hausknecht A. Heryudono S. Kim	Journal of Computational Science Education (2013) 4(1), pp. 24-29.	PDF
Reduced Collocation Methods: Reduced Basis Methods in the Collocation Framework	Y. Chen S. Gottlieb	Journal of Scientific Computing 55/3 (2013), pp. 718-737	Link arXiv Preprint
Certified Reduced Basis Method for Electromagnetic Scattering and Radar Cross Section Estimation	Y. Chen J.S. Hesthaven Y. Maday J. Rodriguez Xueyu Zhu	CMAME 233 (2012) 92 - 108.	doi: 10.1016/j.cma.2012.04.013
Analysis of variable-degree HDG methods for Convection-Diffusion equations. Part I: General nonconforming meshes	Y. Chen B. Cockburn	IMA J Numer Anal (2012) 32 (4): 1267 - 1293.	doi: 10.1093/imanum/drr058
A Seamless Reduced Basis Element Method for 2D Maxwell's Problem: An Introduction	Y. Chen J.S. Hesthaven Y. Maday	In Spectral and High Order Methods for Partial Differential Equations-Selected papers from the ICASOHOM'09 conference, J Hesthaven and EM Ronquist (eds). 2011, Volume 76, 141-152.	Link Updated Preprint
A Natural-Norm Successive Constraint Method for Inf-Sup Lower Bounds	D.B.P. Huynh D.J. Knezevic Y. Chen J.S. Hesthaven A.T. Patera	CMAME 199 (2010) 1963 - 1975	doi: 10.1016/j.cma.2010.02.011
Certified Reduced Basis Methods and Output Bounds for the Harmonic Maxwell's Equations	Y. Chen J.S. Hesthaven Y. Maday J. Rodriguez	SISC 32/2 (2010), pp. 970 - 996	doi: 10.1137/09075250X Updated Preprint
Improved Successive Constraint Method Based A Posteriori Error Estimate for Reduced Basis Approximation of 2D Maxwell's Problem	Y. Chen J.S. Hesthaven Y. Maday J. Rodriguez	ESAIM: M2AN 43 (2009) 1099 - 1116	doi: 10.1051/m2an/2009037
A Monotonic Evaluation of Lower Bounds for Inf-Sup Stability Constants in the Frame of Reduced Basis Approximations	Y. Chen J. S. Hesthaven Y. Maday J. Rodriguez	C. R. Acad. Sci. Paris, Ser. I 346 (2008) 1295 - 1300.	doi: 10.1016/j.crma.2008.10.012 Preprint
An adaptive high order discontinuous Galerkin method with error control for the Hamilton-Jacobi equations. Part I: the one dimensional steady state case	Y. Chen B. Cockburn	J. Comput. Phys. v 226/1(2007), pp. 1027-1058	doi: 10.1016/j.jcp.2007.05.003

Other Preprints

Title	Author		arXiv/Preprint
L1-ROC and R2-ROC: L1- and R2-based Reduced Over-Collocation methods for parametrized nonlinear partial differential equations	Y. Chen S. Gottlieb L. Ji Y. Maday Z. Xu		arXiv: 1906.07349
Reduced-basis method for the iterative solution of parametrized symmetric positive-definite linear systems	N. C. Nguyen Y. Chen		arXiv: 1804.06363

Research supported by

National Science Foundation (DMS-1216928, DMS-1719698, DUE-2030552, DMS-2208277)
AFOSR (FA9550-18-1-0383), PI Gottlieb
UMass Dartmouth MUST program, established by Dr. Ramprasad Balasubramanian , sponsored by ONR (2020 - 2023), PI Heryudono
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:

The Python package GPT-PINN. See here for the paper on ResearchGate.

A NA G-ROMs talk given on 5/16/2023 on GPT-PINN:
The Python package 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):

A talk on RBM given at Banff on 6/26/2012.
A talk on RBM given at ICERM on 6/29/2018.
Introductory talks given at ICERM in Spring 2020: Part I, Part II.

Misc. Slides:

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

Office Location: LARTS 394A
Phone Number: x8438

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
Webpages for courses I am currently teaching
Sample video of my in-class lectures
Resources for Deep Learning

My schedule

Current Teaching

See UMassD myCourses for the class webpages.

Sample video of my in-class lectures (Fall 2019)

Resources for Deep Learning

Papers, courses and books
- A dedicated machine learning paper archive, Andrej Karpathy's ArXiv Sanity Preserver.
- Gabriel Peyre and Marco Cuturi's computational optimal transport book on arXiv.
- Yoshua Bengio, Aaron Courville, and Ian Goodfellow's Textbook.
- Course videos
  - Geoff Hinton's Course (78 short, 10-ish minute, YouTube clips, general introduction).
  - Fei Fei Li's Course (16 hour-long YouTube clips, neural nets for machine vision).
  - Chris Manning and Richard Socher's Course (19 hour-long YouTube clips, neural nets for natural language processing).
  - Andrew Ng's Course (112 short, 10-ish minute, YouTube clips, ML general introduction).
  - Andrew Ng's Stanford machine learning course (20 hour-long YouTube clips).
- A Machine Translation Reading List maintained by Tsinghua Natural Language Processing Group.
- Some of Weinan E's papers on deep learning-related topics.
- An easy-to-follow summary of the Wasserstein GAN.
- Vincent Herrmann's blog entry on Wasserstein GAN and the Kantorovich-Rubinstein Duality.
- Adam Oberman's ICERM presentation on PDE and DNN: Slides and video.
- Catherine F. Higham and Desmond J. Higham's Deep Learning: An Introduction for Applied Mathematicians paper.
- ReLU DNN and Linear FEM, PDE-Net , PDE-Net 2.0
Tools, libraries, and platforms
- Berkeley's Caffe.
- Python-based neural net libraries: Keras and PyTorch
- Theano (Python).
- Alex Krizhevsky's CudaConvNet (C++/CUDA) and CudaConvNet2.
- NYU's Torch.
- OpenAI's GitHub repos.
- Fast AI offering courses, libraries, and featuring many interesting AI articles and stories.
- Google's Dataset Search
- TensorFlow Word Vector Visualization
- Bayesian ML: Tensorflow or Python
- A collection of various deep learning architectures, models, and tips
Looking forward
- AI prediction for 2019 LeCun, Mason, Ng, and Chowdhury
Misc.
- Adam Harley's 3d MNIST Interactive Node-Link Visualization of CNNs.

Past Teaching

Students

Current Graduate Students

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

Matthew Cormier	Jointly advised with Sigal Gottlieb , Matt is a PhD student who started in Fall 2019. In Summer 2019, he started studying the mathematics for Neural Networks, in particular its utilities in time marching schemes.

Haolan Zheng	Haolan a PhD student who started in Fall 2023.

Current Visiting/Oversea Doctoral Students

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

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

Current Undergraduate Students

Alumni

Graduate Student alumni

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

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 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

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.

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

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.

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 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 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 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 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.

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.

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.

Quick Links

This page is organized and occasionally maintained by Yanlai Chen. Some of the sources are gotton from the Internet. I thank very much the authors sharing them on the Web. If some of them are copyrighted, please notify me and I will remove them as soon as possible

Mathematical Links

MISC

MATHEMATICS ORGANIZATIONS:

Society for Industrial and Applied Mathematics - (HiPerSoft)
- Society for Industrial and Applied Mathematics - Rice Student Chapter
Mathematical Programming Society
American Mathematical Society
- Combined Membership List (CML) - contact information for mathematicians

MISC. MATHEMATICS ORGANIZATIONS:

The International Center for Scientific Research - (CIRS)
The Mathematics Genealogy Project
Mathematical Programming Glossary (by Harvey J. Greenberg)
Mathematical Quotation Server
Mathtools.net
Stanford ICME
USC CAMS

Worldwide Mathematical Links

Mathematics Department Web Servers
Mathematics web sites around the world
Mathematical Resources on the Web
American Mathematical Society (e-MATH)
AMS Directory of Preprint Servers
The Geometry Center (University of Minnesota)
MSRI (Mathematical Sciences Research Institute)
SIAM (Society for Industrial and Applied Mathematics)
NCSA (National Center for Supercomputing Applications)
Institut de Mathmatiques Appliques
MAA (Mathematical Association of America)
Isaac Newton Institute for Mathematical Sciences
NSF (National Science Foundation)
IMA (Institute for Mathematics and its Applications)
AIM (The American Institute of Mathematics)
History of Mathematics
AMS e-Math Server

On technical stuff

F2PY - Fortran to Python interface generator

Wrapping C codes using f2py

OpenMP

MPI

MatlabMPI

Mesh Generation on the web(Courtesy of Lin)

C Programming(courtesy of Dave.)

Last Updated On: 6/4/10

Contact Information

Yanlai Chen Office: LARTS Room 394A
Department of Mathematics Phone: 1-508-999-8438
University of Massachusetts, Dartmouth Fax: 1-508-910-6917
285 Old Westport Road E-mail: first.last@umassd.edu
North Dartmouth, MA 02747

Yanlai Chen's Homepage

Research supported by

Related Profiles

Major related links

Navigating this page

Helpful advices and tips

Manuscripts submitted

Some journals in my field

Published articles

Other Preprints

Research supported by

Software Packages:

Research talks (Video):

Misc. Slides:

Dedication to teaching and advising

Navigating this page

Students

Current Graduate Students

David Gillcrist

Matthew Cormier

Haolan Zheng

Current Visiting/Oversea Doctoral Students

Shijin Hou

Yajie Ji

Current Undergraduate Students

Alumni

Graduate Student alumni

Rebecca Pereira

Richard Bellizzi

Lijie Ji

Jiahua Jiang

Christopher Bresten

Undergraduate Student alumni

Shawn Koohy

Chase Parenteau

Jonathan Curtis

Ian Camerlin

Peter Takahashi

Jacob Sousa

Andrew Davey

Rushendra Kumar

Quick Links

Mathematical Links

Contact Information