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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 for problems arising in fluid dynamics 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.

Interests

  • Modeling - Thin liquid films
  • Scientific computation
  • 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

Spontaneous locomotion of phoretic particles in three dimensions

The motion of an autophoretic spherical particle in a simple fluid is analyzed. This motion is powered by a chemical species which is …

A shallow physics-informed neural network for solving partial differential equations on surfaces

In this paper, we introduce a mesh-free physics-informed neural network for solving partial differential equations on surfaces. Based …

Thin liquid films in a funnel

We explore flow of a completely wetting fluid in a funnel, with particular focus on contact line instabilities at the fluid front. …

A Shallow Ritz Method for elliptic problems with Singular Sources

In this paper, a shallow Ritz-type neural network for solving elliptic problems with delta function singular sources on an interface is …

A Discontinuity Capturing Shallow Neural Network for Elliptic Interface Problems

In this paper, a new Discontinuity Capturing Shallow Neural Network (DCSNN) for approximating $d$-dimensional piecewise continuous …

CV

Find my CV in PDF here.

Recent Posts

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 …

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 $\mu$, $U$ …

Multidimensional scaling

Multidimensional scaling, 簡稱 MDS, 是個資料分析或是資料降維的工具. 這裡我們要談一下從數學角度來說 MDS 的原理及做法, 更精確的說, 這裡講的是 classical MDS. 假設我們有 $n$ 筆 $p$ 維的資料,

主成分分析

主成分分析, Principal component analysis, 簡稱 PCA, 是個資料分析或是資料降維的工具. 資料降維簡單來說, 假設我們有一些資料, 這資料中的每一筆維度都很高, 導致我們很難 &ld

Sec.10.3 - 極座標曲線家族

Laboratory Project in Sec.10.3, Calculus by Stewart English version: Families of Polar Curves 在這個研究中,你將發現極座標曲線家族有趣又漂亮的形狀。同時,當常數改變時,你也會觀 …