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Te-Sheng Lin (林得勝)

Associate Professor

National Yang Ming Chiao Tung University, TW

About me

I am an associate professor at the Department of Applied Mathematics at National Yang Ming Chiao Tung University, Taiwan. My research focuses on developing analytical and computational tools and further communicating with scientists from other disciplines to solve practical engineering problems.

I received my Ph.D. degree in Applied Mathematics from the Department of Mathematical Sciences at New Jersey Institute of Technology, where I worked with Lou Kondic and Linda J. Cummings.

My list of publications in Google Scholar. Some preprints in arXiv.

I co-organize NYCU webinar on Scientific Machine Learning.

Interests

  • Mathematical modeling
  • Scientific computation
  • Scientific machine learning

Education

  • PhD in Applied Mathematics, 2012

    New Jersey Institute of Technology, USA

  • M.S. in Applied Mathematics, 2004

    National Chung Cheng University, Taiwan

  • B.S. in Mathematics, 2002

    National Chung Cheng University, Taiwan

Appointments

 
 
 
 
 

Associate Professor

National Yang Ming Chiao Tung University

Feb 2021 – Present Hsinchu, TW
 
 
 
 
 

Associate Professor

National Chiao Tung University

Aug 2020 – Jan 2021 Hsinchu, TW
 
 
 
 
 

Assistant Professor

National Chiao Tung University

Aug 2014 – Jul 2020 Hsinchu, TW
 
 
 
 
 

Research Associate

Loughborough University

Dec 2012 – Jul 2014 Loughborough, UK
 
 
 
 
 

Marie Curie Experienced Researcher

Loughborough University

Jun 2012 – Dec 2012 Loughborough, UK

Recent Publications

Y.-H. Tseng, T.-S. Lin, W.-F. Hu, M.-C. Lai (2023). A cusp-capturing PINN for elliptic interface problems. J. Comput. Phys..

DOI arXiv

J.-J. Tsai, C.-C. Chang, D.-Y. Huang, T.-S. Lin, Y.-C. Chen (2023). Analysis and classification of coffee beans using single coffee bean mass spectrometry with machine learning strategy. Jood Chem..

DOI

W.-F. Hu, T.-S. Lin, Y.-H. Tseng, M.-C. Lai (2023). An efficient neural-network and finite-difference hybrid method for elliptic interface problems with applications. Comm. Comput. Phys..

DOI arXiv

M. Blyth, T.-S. Lin, D. Tseluiko (2023). On the transition to dripping of an inverted liquid film. J. Fluid Mech..

DOI arXiv

W.-F. Hu, Y.-J. Shih, T.-S. Lin, M.-C. Lai (2023). A shallow physics-informed neural network for solving partial differential equations on surfaces.

arXiv

A. Farutin, M.S. Rizvi, W.-F. Hu, T.S. Lin, S. Rafaï, C. Misbah (2022). A Reduced Model for a Phoretic Swimmer. J. Fluid Mech..

DOI arXiv

W.-F. Hu, T.-S. Lin, M.-C. Lai (2022). A Discontinuity Capturing Shallow Neural Network for Elliptic Interface Problems. J. Comput. Phys..

DOI arXiv

M.-C. Lai, C.-C. Chang, W.-S. Lin, W.-F. Hu, T.-S. Lin (2022). A Shallow Ritz Method for elliptic problems with Singular Sources. J. Comput. Phys..

DOI arXiv

W.-F. Hu, T.-S. Lin, S. Rafai, C. Misbah (2022). Spontaneous locomotion of phoretic particles in three dimensions. Phys. Rev. Fluids.

PDF DOI

T.-S. Lin, J.A. Dijksman, L. Kondic (2021). Thin liquid films in a funnel. J. Fluid Mech..

PDF DOI arXiv

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Recent Posts

Trace, determinant 與 eigenvalue 的關係

方陣 A 的行列式等於其特徵值相乘 Determinant of A equals to the product of its eigenvalues 給定一個 $n\times n$ 的方陣 $A$, 我們定義一個變數為 $\lambda$ …
Last updated on Nov 16, 2023 2 min read linear algebra, notes

Euler equations

Euler equations Here, we consider Euler equations: $$ \tag{1} x^2 y’’ + a xy’ + by = 0, \quad x\ne 0, $$ where $a$, …
Last updated on Nov 16, 2023 3 min read ODE

Euler equations

Euler equations 這裡我們想要解 Euler equations, 長相如下: $$ \tag{1} x^2 y’’ + a xy’ + by = 0, $$ 其中 $a$, $b$ 為常數. …
Last updated on Nov 16, 2023 2 min read ODE

Power method with Rayleigh Quotient

Power 迭代法目錄: 基本概念 Power iteration; inverse power method; shifted inver power method 找第二大的 eigenvalue deflation Rayleigh Quotient 迭代及其收斂 …
Last updated on Apr 29, 2023 1 min read notes, Linear algebra, Computational Mathematics

Power method - deflation

Power 迭代法目錄: 基本概念 Power iteration; inverse power method; shifted inver power method 找第二大的 eigenvalue deflation Rayleigh Quotient 迭代及其收斂 …
Last updated on May 24, 2023 3 min read notes, Linear algebra, Computational Mathematics

Conjugate gradient method - iterative method

共軛梯度法 (CG method, conjugate gradient method) 目錄: CG method - Direct mehtod 直接法 CG method - iterate mehtod 迭代法 For solving $Ax=b$, where …
Last updated on Apr 29, 2023 4 min read notes, Linear algebra, Computational Mathematics

Power method

Power 迭代法目錄: 基本概念 Power iteration; inverse power method; shifted inver power method 找第二大的 eigenvalue deflation Rayleigh Quotient 迭代及其收斂 …
Last updated on May 24, 2023 3 min read notes, Linear algebra, Computational Mathematics

Conjugate gradient method - direct method

共軛梯度法 (CG method, conjugate gradient method) 目錄: CG method - Direct mehtod 直接法 CG method - iterate mehtod 迭代法 For solving $Ax=b$, where …
Last updated on Apr 29, 2023 1 min read notes, Linear algebra, Computational Mathematics

Diffusion maps

擴散映射, Diffusion maps (以下簡稱 DM), 是個資料分析, 流型學習或是資料降維的工具. 這裡我們要介紹以 julia 來做 diffusion maps 降維. Algorithm - diffusion maps embeding 先簡單介紹一下 …
Last updated on Aug 14, 2021 3 min read notes, Linear algebra, Machine_learning, notes_julia

主成分分析 - 2

這裡我們補充一下主成分分析裡的證明部分. 假設我們有 $n$ 筆 $p$ 維的資料, 記成 $$ \{x_1, x_2, \cdots, x_n\} \in R^p. $$ 假設想要投影到 $k$ 維, $k\le p$, 數學上來說就是想要找到 $\mu$, $U$ …
Last updated on Dec 22, 2020 2 min read Calculus, Computational Mathematics, Linear algebra, Machine_learning
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