Greetings! I'm Sean, also known as Chun-Hsien (陳俊憲). I am currently a graduate student at the Institute of Applied Mathematics in National Taiwan University, specializing in machine learning, data science, and financial engineering.

My diverse academic background and interests have equipped me with a strong understanding of mathematical models and algorithms, allowing me to develop effective solutions to real-world problems in data analysis. Through my studies, I have developed a particular passion for utilizing these skills to make a positive impact on various industries.

I am excited to connect with others in the math, machine learning, deep learning and finance community. I look forward to new opportunities to learn, grow, and contribute.

Education

National Taiwan University

M.S. in Applied Mathematics

Nov. 2021 - Jun. 2023

Advisor: Prof. Chuan-Hsiang Han

National Chengchi University

B.S. in Applied Mathematics, Minor in Statistics

Nov. 2017 - Jun. 2021

Experience

NCTS

Undergraduate Student Researcher

Topic: Variational models and numerical methods on image processing

Jul. 2020 - Aug. 2020

Advisor: Prof. Suh-Yuh Yang

Shanghai Far Eastern It Co., Ltd.

Data Analyst Intern

Jun. 2019 - Aug. 2019

Teaching Assitant

Teaching assitant of Python Computer Programming at NTU

Nov. 2021 - Jun. 2023

Awards

  • AI CUP 2023 Spring Competition Golden Medal Award, May 2023
  • AI CUP 2022 Fall Competition Top 3%, Dec 2022
  • The Memorial Scholarship Foundation to Lin Hsiung Chen, Dec. 2020
  • Academic Excellent Award at NCCU Applied Mathematics 6 times

Projects

Multimodal Pathological Voice Classification

AI CUP 2023 Spring Competition

Audio Classification

May. 2023 - June. 2023

Projects in Natural Language Processing

Adaptive deep learning 2022

Intent Classification、Slot Tagging、Chinese Question Answering、Natural Language Generation

Sep. 2022 - Dec. 2022

Hahow User Course&Topic Prediction

Adaptive deep learning 2022 Final Competition

Dec. 2022 - Jan. 2023

Prediction of Suspected Money Laundering Transactions

T-Brain Machine Learning Competition

The competion provides Suspicious Activity Report (SAR) data, for participants to design algorithms and build models that more accurately filter out suspicious transactions that require reporting, thereby reducing the false positive rate of suspicious activities. We build the prediction model using tree-based models to deal with rare events, and finally achieve private raking of 14th.

Oct. 2019 - Dec. 2022