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Interface Design Web Design Sketch Bot Development Software Languages Java C/C++ Python Javascript (Node.js, React.js) Verilog Data Science Numpy Scipy Pandas Matplotlib T ensor Flow Plotly SQL Computer Aid Engineering Schematic Design: AutoCAD,, PSpice/HSpice Simulation Tools: Matlab/Simulink,Cadence,Multisim PCB Design: Eagle, Altium Embedded System Design Hardware Programming: Altera QuartuModelsim,FPGA , MPLAB/JTAG Experience Experience 01, FebPresent Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam porttitor dapibus ipsum ut efficitur. Aliquam feugiat nec sem dapibus blandit. Experience 02, JanFeb 2016 Lorem ipsum dolor
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4-6 years
University of Massachusetts
Electrical Engineering
Avatar of 王文祥.
Avatar of 王文祥.
經理 @鴻博資訊有限公司
2015 ~ Present
軟體工程師、電玩程式設計師、後端工程師、APP開發工程師、演算法開發工程師
Within one month
of the relevant technologies in the field of machine learning that I have researched and become familiar with over the past year: Numpy (Numerical Computing Library) : Numpy is one of the core libraries for numerical computing in Python. It provides powerful mathematical functions and array operations, capable of handling multidimensional arrays and matrix operations. In data processing and analysis, Numpy is an indispensable tool for efficiently handling large amounts of data. Pandas (Data Analysis Library) : Pandas is an important library in Python for data analysis and data processing. It offers powerful data structures such as DataFrame
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10-15 years
崑工科技大學
電子工程
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資訊工程師 @六點資訊科技有限公司
2023 ~ 2024
軟體工程師
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Sean Wang Hello, I'm Sean. With over 9 years of extensive experience in software development, I excel in employing divergent thinking to address abstract client requirements and tackle various implementation challenges within systems. I specialize in integrating diverse user contexts and crafting solutions based on available resources. I enjoy analyzing the essence of things through multidimensional observation. New Taipei City, [email protected] Academic qualifications 2008//06 Chihlee University of Technology Information management Bachelor's graduation 2005//06 Ger Jyh Senior High School Data Processing Department Vocational
C# .NET Core
T-SQL
JavaScript / ES6 / jQuery
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6-10 years
致理科技大學 Chihlee University of Technology
Information Management
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Data Science Competition Participant @Self-Employed
2020 ~ Present
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度對於建築耗能是否有顯著的成效 -進行數棟具綠建築標章辦公大樓的EnergyPlus能源性能模擬 National Taiwan University Bioenvironmental System Engineering •NTU Presidential AwardClass Representative 學術發表 - Fu, C. , Quintana, M., Nagy, Z., & Miller, CFilling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation. Applied Thermal Engineering, 236,Canaydin, A., Fu, C. , Balint, A., Khalil, M., Miller, C., & ...
Microsoft Office
python
machine learning
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4-6 years
National University of Singapore
Department of building
Avatar of 王永霖.
Avatar of 王永霖.
資深專案設計 @必應創造B'in live
2017 ~ 2023
Creative design、資深設計 Senior design、Visual design
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王永霖 Louis Senior project designer [email protected] Taipei City, Taiwan 我是一名影像內容製作的設計師,對動畫設計、3D製作、平面設計等領域有著豐富的經驗和深入的了解 。 擅長透過多面向整合思維,無論是使用攝影、編輯、動畫製作和互動設計等技能來創造出令人印象深刻的
Photoshop
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實踐大學(Shih Chien University)
資訊模擬與設計
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Catlle Breeding and Partnership Manager @PT. Pasir Tengah
2016 ~ 2023
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Universitas Gadjah Mada
Animal Science
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2015 ~ 2016
Product Manager
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closely with builders, creating tailored architecture diagrams and user journeys to streamline onboarding to our protocol. Blockchain Architect • The Blockchain Xdev (now EniblockLed the project management and development of a mobile application ( https://unbank.mobi ) enabling cryptocurrency transactions via QR codes, integrating various APIs and a multisignature wallet. Led the design of an experimental project with European banks, successfully facilitating secure bond issuance with a delivery vs payment module. This project managed interest, redemption, and a secondary market on the Tezos blockchain, gaining global recognition through articles such as (https://www.
Unemployed
Full-time / Remote Only
6-10 years
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Investor @Blank Street
2023 ~ Present
Real Estate Broker
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— Ryan Serhant In the realm of real estate, few names hold as much recognition and success as Ryan Serhant. As the visionary founder and CEO of SERHANT. , he has built an empire that transcends traditional brokerage, merging the worlds of media, entertainment, education, and technology. Ryan's diverse talents and entrepreneurial spirit extend far beyond the real estate realm. He is not only a top-performing broker but also an acclaimed innovator, producer, best-selling author, podcast host, public speaker, educator, content creator, and a captivating television personality. Audiences worldwide recognize him from his
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Hamilton College
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Head of Business Development @PT Kece Kreatif Indonesia
2023 ~ Present
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LSPR Communication and Business Institute
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Avatar of the user.
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Senior Front-End Software Engineer @KKSTREAM 香港商科科串流股份有限公司
2020 ~ 2022
前端工程師 Front-End Developer
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Front-End Development
Front-End Web Development
Javascript(ES6)
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6-10 years
國立中山大學 National Sun Yat-Sen University
Computer Science

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Print

陳得翊 William

Data analyst, Machine learning engineer

我是一個熱愛挖掘潛在問題的統計人,以客觀的角度分析問題及處理,重視團隊合作,開放的態度分享彼此不同的想法和意見,有效率的解決問題。就學期間致力研究於機器學習,降維(Dimension Reduction)以及模型分類問題。並與台北榮民總醫院合作結合人工智慧開發全方位疾病診斷,在臨床上預測病人在一年內是否發生中風,以及是否由肺靜脈引起心房顫動的3D影像分類。

  

Mobile: +886-988-313-160

Email: [email protected]

技能

Python


  • 視覺化:Matplotlib, Seaborn


  • 機器學習套件:
    Tensorflow, Keras, Scikit-learn, Fast.ai, OpenCV

Machine Learning


  • 模型:Random Forest, XGBoost, LightGBM, SVM, CNN, RNN, LSTM, ResNet
  • 特徵選擇:Genetic algorithm, Simulated Annealing

Dimension Reduction


Multidimensional Scaling (MDS), SCMDS, Principal component analysis (PCA), Factor analysis model, Lasso regression

學歷

2018 - 2020

國立交通大學

統計學研究所

論文題目:Using Machine Learning Model and Ensemble Learning to Predict Ischemic stroke

第三屆統計研究成果研討會海報論文競賽—特優獎


2014 - 2018

私立淡江大學

統計學係

相關課程:回歸分析, 類別資料分析, 實驗設計, 無母數統計, 多變量分析, 時間序列, 倖存分析

程式:R, SAS (SAS Certified Base Programmer)

社團:統計系籃球隊-隊長                                           大統盃,亞軍, 2016 大統盃季軍, 2017

專案經驗


國立交通大學與台北榮民總醫院心臟科

預測病人在一年內是否發生中風Ischemic Stroke

                                                                

透過機器學習 (Machine Learning) 預測病人在一年內是否發生腦缺血型中風 (Ischemic stroke) 並且提升模型在 auc 上的表現。研究過程我們遇到資料極度不平衡的問題,透過變數選擇 (Feature Selection) 幫助我們挑選重要的特徵,使用集成學習 (Ensemble Learning)及下採樣 (Under-sampling)結合多個模型及處理資料不平衡的問題。


國立交通大學

Modeling High-dimensional time series by Structural factor model

                      

研究威爾夏5000指數 (Wilshire 5000 index) 成分股,透過主成份分析 (Principle Component Analysis) by Bai and Ng, Ratio-based method by Lam and Yao, and Structural factor model by Gao and Tsai, 找出背後影響5000支股票的潛在變數。對應於潛在變數與5000支股票的權重,得到新的一組投資組合,比較投組與指數的報酬。 



國立交通大學與台北榮民總醫院心臟科

CT Images Classification of PV and Non-PV trigger by 3D Convolution Network

                                                                                                

一位病人通常會有多張CT影像,有些影像包含疾病而有些影像則未包含, 使用3D CNN 可以使模型以病人為單位而非影像。在3D影像前處理對於像素的長寬和影像之間的切片厚度做歸一化。由於每位病人的影像張數不同, 在張數較少的病人上下補上黑色影像。在模型的選擇上使用 3D Resnet 做 模型訓練,針對資料不平衡的問題,我們對病人的影像做旋轉使得少數類 病人與多數類病人以相同比例進入模型。                                                              



Kaggle

Predict Future Sales (Top 8%)

                                                                                                

資料集由俄羅斯1C公司提供,紀錄2013/01~2015/10的日資料,目的是預測下個月每個產品和商店的總銷售額。在EDA探討各變數與總銷售額的marginal effect,以及變數之間對總銷售額的Joint effect,我們在特徵工程將商店與商品名稱所額外提供的資訊,像是城市,產品類別形成了新的變數。最後透過LightGBM經由gridsearch調整超參數後得到在LB的 rmse : 0.89258。                                                  

工作經歷

四月 2020 - 六月 2020

時間序列助教  國立交通大學

批改學生作業以及協助課業問題。

七月 2019 - 八月 2019

因子選股實習生  元大投信

利用統計方法幫助大中華團隊研究A股,挑選出重要因子且建構模型挑選股票。檢定因子間是否存在共線性,影響下一期報酬率估計。最後透過因子表現分成五組,回測並且比較各組表現。實習期間與主管配合良好,經理人提供想法以及自己的選股邏輯,我再透過檢定和回歸等相關統計方法實現,彼此互助學習讓我獲益良多。

七月 2016 - 八月 2016

顧問助理  VIT Advisors Limited(維億投資顧問有限公司)

陪同顧問到中國海口平安銀行做諮詢及授課,負責記錄諮詢重點。

Resume
Profile

陳得翊 William

Data analyst, Machine learning engineer

我是一個熱愛挖掘潛在問題的統計人,以客觀的角度分析問題及處理,重視團隊合作,開放的態度分享彼此不同的想法和意見,有效率的解決問題。就學期間致力研究於機器學習,降維(Dimension Reduction)以及模型分類問題。並與台北榮民總醫院合作結合人工智慧開發全方位疾病診斷,在臨床上預測病人在一年內是否發生中風,以及是否由肺靜脈引起心房顫動的3D影像分類。

  

Mobile: +886-988-313-160

Email: [email protected]

技能

Python


  • 視覺化:Matplotlib, Seaborn


  • 機器學習套件:
    Tensorflow, Keras, Scikit-learn, Fast.ai, OpenCV

Machine Learning


  • 模型:Random Forest, XGBoost, LightGBM, SVM, CNN, RNN, LSTM, ResNet
  • 特徵選擇:Genetic algorithm, Simulated Annealing

Dimension Reduction


Multidimensional Scaling (MDS), SCMDS, Principal component analysis (PCA), Factor analysis model, Lasso regression

學歷

2018 - 2020

國立交通大學

統計學研究所

論文題目:Using Machine Learning Model and Ensemble Learning to Predict Ischemic stroke

第三屆統計研究成果研討會海報論文競賽—特優獎


2014 - 2018

私立淡江大學

統計學係

相關課程:回歸分析, 類別資料分析, 實驗設計, 無母數統計, 多變量分析, 時間序列, 倖存分析

程式:R, SAS (SAS Certified Base Programmer)

社團:統計系籃球隊-隊長                                           大統盃,亞軍, 2016 大統盃季軍, 2017

專案經驗


國立交通大學與台北榮民總醫院心臟科

預測病人在一年內是否發生中風Ischemic Stroke

                                                                

透過機器學習 (Machine Learning) 預測病人在一年內是否發生腦缺血型中風 (Ischemic stroke) 並且提升模型在 auc 上的表現。研究過程我們遇到資料極度不平衡的問題,透過變數選擇 (Feature Selection) 幫助我們挑選重要的特徵,使用集成學習 (Ensemble Learning)及下採樣 (Under-sampling)結合多個模型及處理資料不平衡的問題。


國立交通大學

Modeling High-dimensional time series by Structural factor model

                      

研究威爾夏5000指數 (Wilshire 5000 index) 成分股,透過主成份分析 (Principle Component Analysis) by Bai and Ng, Ratio-based method by Lam and Yao, and Structural factor model by Gao and Tsai, 找出背後影響5000支股票的潛在變數。對應於潛在變數與5000支股票的權重,得到新的一組投資組合,比較投組與指數的報酬。 



國立交通大學與台北榮民總醫院心臟科

CT Images Classification of PV and Non-PV trigger by 3D Convolution Network

                                                                                                

一位病人通常會有多張CT影像,有些影像包含疾病而有些影像則未包含, 使用3D CNN 可以使模型以病人為單位而非影像。在3D影像前處理對於像素的長寬和影像之間的切片厚度做歸一化。由於每位病人的影像張數不同, 在張數較少的病人上下補上黑色影像。在模型的選擇上使用 3D Resnet 做 模型訓練,針對資料不平衡的問題,我們對病人的影像做旋轉使得少數類 病人與多數類病人以相同比例進入模型。                                                              



Kaggle

Predict Future Sales (Top 8%)

                                                                                                

資料集由俄羅斯1C公司提供,紀錄2013/01~2015/10的日資料,目的是預測下個月每個產品和商店的總銷售額。在EDA探討各變數與總銷售額的marginal effect,以及變數之間對總銷售額的Joint effect,我們在特徵工程將商店與商品名稱所額外提供的資訊,像是城市,產品類別形成了新的變數。最後透過LightGBM經由gridsearch調整超參數後得到在LB的 rmse : 0.89258。                                                  

工作經歷

四月 2020 - 六月 2020

時間序列助教  國立交通大學

批改學生作業以及協助課業問題。

七月 2019 - 八月 2019

因子選股實習生  元大投信

利用統計方法幫助大中華團隊研究A股,挑選出重要因子且建構模型挑選股票。檢定因子間是否存在共線性,影響下一期報酬率估計。最後透過因子表現分成五組,回測並且比較各組表現。實習期間與主管配合良好,經理人提供想法以及自己的選股邏輯,我再透過檢定和回歸等相關統計方法實現,彼此互助學習讓我獲益良多。

七月 2016 - 八月 2016

顧問助理  VIT Advisors Limited(維億投資顧問有限公司)

陪同顧問到中國海口平安銀行做諮詢及授課,負責記錄諮詢重點。