正職是政治大學應用數學系的博士候選人，朝向畢業前進中。

副職是不學無術者，一開始攻讀投資組合最佳化問題，在記憶體設計、奈米尺度材料力學及智慧理財新創公司輾轉走過，最近"被"投入到教學神經網路的講師狀態中。

+886-922214799

Taipei, Taiwan

I have two main research topics:

a) Computational algebra;

b) Applications of neural networks.

For first topic, I mainly deal with HodgeRank method and its generalization. The construction of computational algebra system is my side project which is constructed for the modeling of optimization problems.

Nowadays, neural network, especially Deep Neural Networks becomes a popular tools for developing Artificial Intelligence or Computer Aided Design. I an now focus on how to use neural network on medical image analysis. The tool I used in this field is Python and Keras.

**Thesis: Stochastic portfolio optimization models for the stable growth benchmark tracking**

I focused on the combination between portfolio optimization problem and scenario trees. Moment matching method was introduced to provide a user-defined scenario tree which fits the first few moments of past data.

Major in Judo (2nd Dan), double major in Karate (brown belt), minor in Slavic languages and **mathematics. **Besides, I was one of the co-founders of speciality coffee club in NCCU.

- Certification program:
- Mathematical Finance
- Slavic Languages And Literatures

- Studied on manifold interpolation/reconstruction based on composition of local orthogonal projections

- Integrated different framework of neural network model
- Developed visualization scheme about the quality of medical data.

- Assisted four students from NTU, NTHU, and NCTU to join work in the topic of computational algebraic geometry.
- Implemented a classical-to-tropical transformer for obejects in both classical algebraic geometry and tropical geometry. e.g., tropicalization of polynomial, tropical curve, and Newton polytope.
- Implemented an algorithm for the classfication of A-D-E singularities (du Val singularities).

- Assisted four students from different universities to join work in the field of real world data science issue.
- Implemented a smartphone application w/ Matlab and improve it into real-time application.
- Summarized some algorithms in medical image analysis from Kaggle Data Science Bowl 2017.

- Developed statistical analysis procedure of data from atomic force microscope (AFM).

- Studied papers on the topic of circuit dynamic and static optimization.
- Developed corresponding algorithms on VLSI circuit tuning via optimization method.

- Calculus
- Linear Algebra
- Advanced Calculus
- Real Analysis
- Differential Geometry
- Operations Research
- Investment Science/Futures and Options
- Financial Mathematics

HodgeRank is a pairwise comparison method for recommendation system.

The theory of HodgeRank is based on the theory of cohomology group and Hodge/Helmholtz Decomposition.

The figure is referred from [7].

I am recently focus on how to use neural network in medical image analysis. I am working with master students in NTU with Prof. Weichung Wang. We are now trying to duplicate some existence models and then improve it in any sense.

This figure is the MRI image of my left shoulder.

以下是一些自願/非自願(誤)的正式演講，包含學術及非學術演講。

The 9th International Conference on Optimization: Techniques and Applications (ICOTA 9)

- Index Tracking Models with Forecasting (with Ming Long Liu)
- Men and Women Matching Models and Its Applications (with Ming Long Liuand Po-Hsiang Chan)

- A brief introduction to HodgeRank

國立政治大學 教育發展中心

- 與學生互動的教學技巧

2017 TW-SIAM Contribution Session

- Feature Portfolio Construction with Deep Learning (join work with Yen-lung Tsai)

國立政治大學 應用數學系 數學軟體應用 / Applications of mathematics software

- Advanced Keras Modeling Techniques

全球智能「智能理財與深度學習」訓練營 專職講師

**Lin, T.Y.**& Y.L. Tsai, Graph Laplacian Problems on Graph Neural Networks. The 19th SIAM International Conference on Data Mining (SDM19) Workshop on Deep Learning for Graphs (SDM19).**Lin, T.Y.**& Y.L. Tsai, An Application of HodgeRank to the Online Peer Assessment, 4th International Workshop on Machine Learning Methods for Recommender Systems. In conjunction with 18th SIAM International Conference on Data Mining (SDM18).**Lin, T.Y.**& Y.L. Tsai, Invariant Generative Adversarial Network on Chinese characters. Doctoral consortium session at the 2017 conference on technologies and applications of artificial intelligence (TAAI 2017).**Lin, T.Y.**& Y.L. Tsai, Feature Portfolio Construction with Deep Learning, 2017 TWSIAM Annual Meeting.- Tsai, Y.L. &
**T.Y. Lin**, Toward Deep Learning for Application in Finance, 2016 Taiwan Mathematical Society Annual Meeting. **Lin, T.Y.**et al., Establishing Nanoscale Heterogeneity with Nanoscale Force Measurements, The Journal of Physical Chemistry C, 2015, 119 (32), pp 18267–18277.- Jiang, X., Lim, L. H., Yao, Y., & Ye, Y. (2011). Statistical ranking and combinatorial Hodge theory. Mathematical Programming, 127(1), 203-244.