Cake Talent Search

Advanced filters
On
4-6 years
6-10 years
10-15 years
More than 15 years
Avatar of the user.
Avatar of the user.
Past
Industrial Engineer @鴻海精密工業股份有限公司
2019 ~ 2023
Data Analyst 數據分析師 / Data Scientist 資料科學
Within one month
python
R
SAP
Unemployed
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立臺北大學 National Taipei University
經濟學
Avatar of 梁榮恩.
Avatar of 梁榮恩.
工程師 @中華航空公司 China Airlines
2015 ~ Present
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within one month
Ron Liang Software Engineer [email protected] City, Taiwan Software Engineer, China Airlines A dedicated Software Engineer with extensive experience in .NET development and AI. Skilled in web development using VB and C#, as well as in-depth knowledge of AI, data analytics, natural language processing, computer vision, and deep learning model training and operations using Python. Committed to delivering innovative solutions and contributing to the advancement of technology in the aviation industry. Work Experience Engineer | China Airlines April 2015 – Present .NET Software Development & Web Development: Developed and maintained robust web applications
Python
C#
Git
Employed
Ready to interview
Full-time / Interested in working remotely
6-10 years
國立台灣大學 National Taiwan University
電信工程學研究所
Avatar of Chun-Jung Huang.
Avatar of Chun-Jung Huang.
OPC Chief Engineer @TSMC
2020 ~ Present
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within one month
Chun-Jung Huang [email protected] Chiao-Tung University, Ph.D. - Photonics,2015 ~ 2020 Member of The Phi Tau Phi Scholastic Honor Society of the Republic of China. Work Experience TSMC, OPC Chief Engineer (MarPresent) ◆Introduced image anomaly detection techniques to identify and address defects in photomask manufacturing, significantly improving product quality and reducing turnaround time. ◆GPU acceleration, transferring existing code to GPU for high-performance computing using CUDA and CuLibs. ◆Implementing localized deployment of Large Language Models (LLMs) for customization and specific applications. ◆Utilizing Retriever-Augmented Generation (RAG) for
Deep learning with TensorFlow
Translational Research
Clinical Research
Employed
Ready to interview
Full-time / Interested in working remotely
4-6 years
National Chiao-Tung University
Ph.D. - Clinical Engineering
Avatar of the user.
Avatar of the user.
AI/ML Engineer @緯創資通
2020 ~ Present
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within one month
Computer Science
Computer Vision
Data Science
Employed
Ready to interview
Full-time / Interested in working remotely
4-6 years
National Cheng Kung University
Industrial and Information Management
Avatar of 李慕全(MuChuan Li).
Avatar of 李慕全(MuChuan Li).
軟體工程師 @TSMC 台積電
2024 ~ Present
AI工程師、機器學習工程師、電腦視覺工程師、資料科學家、Machine Learning Engineer、Computer Vision Engineer、Data Scientist
Within one month
預處理: • 開發爬蟲系統:使用者只需設定關鍵字即可自動爬取各大醫學論文網站當今的文章,爬取網站包含:PubMed、Google Patent、Internet Archive Scholar。 • 資料清理:將文章內容依照公司標準做整理,並新增數據至公司資料庫。 技術:Python、Beautiful Soup、Selenium、Prompt Engineering、MySQL 微算機系統實習 課程助教 • 國
Machine Learning
Computer Vision
Pytorch/Tensorflow
Employed
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立臺北科技大學
資訊工程
Avatar of 潘揚燊.
Avatar of 潘揚燊.
Smart Manufacturing AI Engineer @聯華電子股份有限公司
2022 ~ Present
AI工程師、機器學習工程師、深度學習工程師、影像演算法工程師、資料科學家、Ai Application Engineer,Machine Learning Engineer,Deep Learning Engineer,Data Scientist
Within one month
潘揚燊 ㄕㄣ Shen Pan Kaohsiung City,Taiwan •  [email protected] 希望職務:人工智慧應用開發工程師 現任 : 聯華電子 智慧製造 AI 工程師 您好,我是潘揚燊,目前任職於 聯華電子 , 擔任 智慧製造 AI 工程師 , 畢業於元智大學工業工程與管理學系研究所。 熟悉 Python、C#、R 語
Python
Qt
Git
Employed
Ready to interview
Full-time / Interested in working remotely
4-6 years
元智大學 Yuan Ze University
工業工程與管理學系所
Avatar of the user.
Avatar of the user.
Senior engineer @Chicony Electronics Co, Ltd.
2018 ~ Present
全端工程師、後端工程師、前端工程師、軟體專案主管、AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within one month
Python
C
C++
Employed
Ready to interview
Full-time / Interested in working remotely
6-10 years
National Taiwan Ocean University
Computer science and engineering
Avatar of 王維隆.
Avatar of 王維隆.
Past
後端部經理 @天堂遊戲有限公司
2022 ~ 2024
後端工程師
Within two months
工程師, May 2014 ~ Sep 2015 財富管理系統 借券子系統 交易 債務清理系統 個資法系統操作Log 壓力測試 二代投資系統 報表開發 交易庫存計算邏輯 至客戶端現場系統維護 學歷 國立臺北教育大學(National Taipei University of Education), 科學碩士(MS), 資料科學, 2015 ~ 2017 Lorem ipsum dolor sit am...
Golang
MySQL
Redis
Unemployed
Ready to interview
Full-time
10-15 years
國立臺北教育大學(National Taipei University of Education)
資料科學
Avatar of 傅群.
Offline
Avatar of 傅群.
Offline
Data Science Competition Participant @Self-Employed
2020 ~ Present
資料科學
Within two months
名 (團隊成員, 獲得1,500美元Aidea:中科智慧製造-光電製程品質預測, 第一名 (獨立參賽, 獲得1,500美元) - Kaggle平台的程式碼(notebooks)Master (180th/資料科學家 • 探識空間科技有限公司 八月一月 2020 | Taipei, Taiwan 與台積電合作研發: 應用人工智慧於建築設備群的運轉異常偵測及
Microsoft Office
python
machine learning
Studying
Ready to interview
Full-time / Interested in working remotely
4-6 years
National University of Singapore
Department of building
Avatar of 黃姵瑄.
Avatar of 黃姵瑄.
Data Engineer, Data Scientist, LLMOps @騰創數析股份有限公司 (創代科技)
2023 ~ Present
Data Analyst 數據分析師 / Data Scientist 資料科學
Within one month
及應用ETL數據自動化流程、建置Airflow排程管理、參與0到1架構分散式數據架構建置Druid + Superset、開發數據API flask/fastapi 與前端協作。 (資料工程師) - 電商行為數據探勘、商品分類模型建構、社群文章推薦模型訓練。建置商品推薦系統與文章推薦系統。 (資料科學
Python
Communication Skills
Analytical Thinking
Employed
Ready to interview
Full-time / Interested in working remotely
4-6 years
Temple University, Fox School of Business
Finance

The Most Lightweight and Effective Recruiting Plan

Search resumes and take the initiative to contact job applicants for higher recruiting efficiency. The Choice of Hundreds of Companies.

  • Browse all search results
  • Unlimited access to start new conversations
  • Resumes accessible for only paid companies
  • View users’ email address & phone numbers
Search Tips
1
Search a precise keyword combination
senior backend php
If the number of the search result is not enough, you can remove the less important keywords
2
Use quotes to search for an exact phrase
"business development"
3
Use the minus sign to eliminate results containing certain words
UI designer -UX
Only public resumes are available with the free plan.
Upgrade to an advanced plan to view all search results including tens of thousands of resumes exclusive on Cake.

Definition of Reputation Credits

Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
Problem-Solving
Ability to identify, analyze, and prepare solutions to problems.
Adaptability
Ability to navigate unexpected situations; and keep up with shifting priorities, projects, clients, and technology.
Communication
Ability to convey information effectively and is willing to give and receive feedback.
Time Management
Ability to prioritize tasks based on importance; and have them completed within the assigned timeline.
Teamwork
Ability to work cooperatively, communicate effectively, and anticipate each other's demands, resulting in coordinated collective action.
Leadership
Ability to coach, guide, and inspire a team to achieve a shared goal or outcome effectively.
Within three months
建築/能源/IoT 資料科學家
Self-Employed
2020 ~ Present
台灣台北市
Professional Background
Current status
Studying
Job Search Progress
Ready to interview
Professions
Big Data Engineer, Data Analyst, Data Scientist
Fields of Employment
Artificial Intelligence / Machine Learning, Internet of Things (IoT), Energy
Work experience
4-6 years
Management
I've had experience in managing 1-5 people
Skills
Microsoft Office
python
machine learning
AI
IoT
Data science
Languages
English
Professional
Chinese
Native or Bilingual
Job search preferences
Positions
資料科學家
Job types
Full-time
Locations
台灣台北
Remote
Interested in working remotely
Freelance
Yes, I freelance in my spare time
Educations
School
National University of Singapore
Major
Department of building
Print

傅群

0913889502 | [email protected]
https://www.linkedin.com/in/chun-fu/
https://www.kaggle.com/patrick0302

我是一名擁有豐富機器學習和數據分析經驗的專業人士,包含了學術界的博士學歷及豐富的業界經驗,尤其在能源和建築領域有著全面的專案經驗。以下是我職業生涯的亮點和重要成就:
- 在能源和建築領域有全面的機器學習專案經驗,包括預測、異常檢測、填補缺失數據和生成模型等方面
- 在建築和能源領域擁有超過三年的業界工作經驗,包括建築運營和節能策略,參與過數個建築大數據的專案
- 在數據競賽方面擁有豐富經驗,包括在Kaggle程式碼的Master級別,並在太陽能板生產、智慧農業數位分身和西門子永續黑客松等競賽中獲勝
- 多次應邀發表講座和演講,分享能源建模和數據分析方面的知識,包括在台灣電力公司、學術會議以及Python社群
- 在數據競賽、業界工作和學術研究的不同職位中,展示出強大的團隊合作和領導能力

工作經歷


Data Science Competition Expert

一月 2020 - Present  |  Taipei, Taiwan

- 2024 Kaggle獎金競賽:Enefit -預測prosumers能源行為, 銀牌, 71th/2731 on public leaderboard (團隊成員)
- 2023西門子永續技術黑客松:”Swarm Behaviour on the Grid”, 第一名 (團隊成員,獲得5,000歐元)
- 2022 台灣AIGO:透過身體組成與健身數據AI智能健身訓練課程推薦系統, 優勝隊伍 (團隊隊長, 獲得10,000美元)
- 2022年Kaggle社區競賽:大規模能源異常檢測, 第一名(獨立參賽)
- 2021智慧農業數位分身創新應用競賽,第三名 (團隊成員, 獲得1,500美元)
- 2020 Aidea:中科智慧製造-光電製程品質預測, 第一名 (獨立參賽, 獲得1,500美元)
- Kaggle平台的程式碼(notebooks)Master (180th/55809)

資料科學家  •  探識空間科技有限公司

八月 2016 - 一月 2020  |  Taipei, Taiwan

與台積電合作研發: 應用人工智慧於建築設備群的運轉異常偵測及診斷服務
- 實踐能夠大量導入和訓練的建模流程, 應用於超過千台設備、萬點以上的IoT點位
- 應用機器學習技術及早發覺異常徵兆, 提前告知維護人員設備異常及診斷預測
- 獲得內政部建研所2019年、第12屆巢向未來銀獎獎項(總排名第二名)

分析市政府的BA大數據, 並協助BIM-FM系統的建置
- 建置可視化的能源預測及最佳化服務(結合氣象預報)
- 從營運大數據中, 提出數種策略: 冰機預測性控制, 預冷策略, 負荷移轉
- 帶領工讀生完成1000+個空調設備的電子及系統化

建置智慧建築管理系統 (內政部建研所的Living 3.0智慧化展示空間)
- 整合500+的I/O點位, 包含既有系統及新增感測器 (BACnet/Modbus)
- 向參觀民眾展示智慧節能及最佳化控制 (每年約10,000+遊客), 視覺化呈現建築營運

學歷


National University of Singapore

Department of building  •  2020 - 2024

- 專攻建築能源和營運的機器學習技術。研究全面涵蓋了應用ML/DL的預測、異常檢測、缺失數據填補和數據生成
- Technical team in Kaggle competition: <ASHRAE - Great Energy Predictor III>近20年最大的建築能源數據競賽, 數據集涵蓋全球1500棟建築、收集期間長達三年, 協助分析比賽隊伍的機器學習模型及預測表現, 並比較不同的預測模型建構策略
- 博士論文<Automated Pipelines for Enhanced Energy Data Quality: Anomaly Detection, Data Imputation, and Generative Modeling>, 提出了一套結合異常偵測、缺失預測和數據條件生成的自動化流程, 規模化的將能源大數據進行清理和前處理。
- 2023台灣電力公司邀請演講: 數據與電業之旅系列講座 – 以數據探索能源與評估風險,
- 2022 PyCon APAC (python社群年會)公開演講: 從開放數據閱讀台灣能源 - 數據探索、模型預測和風險評估
- 2022 BuildSys2022 Workshop: "1st ACM BuildSys 2022 Tutorial on Electricity Demand Forecasting"

National Taiwan University

Sustainable Environment and Green Architecture  •  2013 - 2015

綠建築標章制度下之節能成效調查與驗證研究

-執行國內首次對EEWH綠建築標章實質效益的全面檢核, 欲了解國內的綠建築制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  •  2009 - 2013

- NTU Presidential Award (2013)
- Class Representative

學術發表


- Fu, C., Quintana, M., Nagy, Z., & Miller, C. (2024). Filling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation. Applied Thermal Engineering, 236, 121545.

- Canaydin, A., Fu, C., Balint, A., Khalil, M., Miller, C., & Kazmi, H. (2024). Interpretable domain-informed and domain-agnostic features for supervised and unsupervised learning on building energy demand data. Applied Energy, 360, 122741.

- Fu, C., Kazmi, H., Quintana, M., & Miller, C. (2023, November). Enhancing Classification of Energy Meters with Limited Labels using a Semi-Supervised Generative Model. In Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 450-453).

- H. Kazmi, Fu, C., C. Miller, “Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale,” Building and Environment, vol. 239, pp. 110407, 2023.

- Fu, C., Arjunan, P., & Miller, C. (2022, November). Trimming outliers using trees: winning solution of the large-scale energy anomaly detection (LEAD) competition. In Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 456-461).

- Miller, C., Picchetti, B., Fu, C., & Pantelic, J. (2022). Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis. Science and Technology for the Built Environment, 1-18.

- Fu, C., & Miller, C. (2022). Using Google Trends as a proxy for occupant behavior to predict building energy consumption. Applied Energy, 310, 118343.

- Miller, C., Hao, L., Fu, C. (2022). Gradient boosting machines and careful pre-processing work best: ASHRAE Great Energy Predictor III lessons learned. arXiv preprint arXiv:2202.02898.

- Miller, C., Arjunan, P., Kathirgamanathan, A., Fu, C., Roth, J., Park, J. Y., ... & Haberl, J. (2020). The ASHRAE great energy predictor III competition: Overview and results. Science and Technology for the Built Environment, 26(10), 1427-1447.

語言


  • English — 專業
  • Chinese — 母語或雙語
Resume
Profile

傅群

0913889502 | [email protected]
https://www.linkedin.com/in/chun-fu/
https://www.kaggle.com/patrick0302

我是一名擁有豐富機器學習和數據分析經驗的專業人士,包含了學術界的博士學歷及豐富的業界經驗,尤其在能源和建築領域有著全面的專案經驗。以下是我職業生涯的亮點和重要成就:
- 在能源和建築領域有全面的機器學習專案經驗,包括預測、異常檢測、填補缺失數據和生成模型等方面
- 在建築和能源領域擁有超過三年的業界工作經驗,包括建築運營和節能策略,參與過數個建築大數據的專案
- 在數據競賽方面擁有豐富經驗,包括在Kaggle程式碼的Master級別,並在太陽能板生產、智慧農業數位分身和西門子永續黑客松等競賽中獲勝
- 多次應邀發表講座和演講,分享能源建模和數據分析方面的知識,包括在台灣電力公司、學術會議以及Python社群
- 在數據競賽、業界工作和學術研究的不同職位中,展示出強大的團隊合作和領導能力

工作經歷


Data Science Competition Expert

一月 2020 - Present  |  Taipei, Taiwan

- 2024 Kaggle獎金競賽:Enefit -預測prosumers能源行為, 銀牌, 71th/2731 on public leaderboard (團隊成員)
- 2023西門子永續技術黑客松:”Swarm Behaviour on the Grid”, 第一名 (團隊成員,獲得5,000歐元)
- 2022 台灣AIGO:透過身體組成與健身數據AI智能健身訓練課程推薦系統, 優勝隊伍 (團隊隊長, 獲得10,000美元)
- 2022年Kaggle社區競賽:大規模能源異常檢測, 第一名(獨立參賽)
- 2021智慧農業數位分身創新應用競賽,第三名 (團隊成員, 獲得1,500美元)
- 2020 Aidea:中科智慧製造-光電製程品質預測, 第一名 (獨立參賽, 獲得1,500美元)
- Kaggle平台的程式碼(notebooks)Master (180th/55809)

資料科學家  •  探識空間科技有限公司

八月 2016 - 一月 2020  |  Taipei, Taiwan

與台積電合作研發: 應用人工智慧於建築設備群的運轉異常偵測及診斷服務
- 實踐能夠大量導入和訓練的建模流程, 應用於超過千台設備、萬點以上的IoT點位
- 應用機器學習技術及早發覺異常徵兆, 提前告知維護人員設備異常及診斷預測
- 獲得內政部建研所2019年、第12屆巢向未來銀獎獎項(總排名第二名)

分析市政府的BA大數據, 並協助BIM-FM系統的建置
- 建置可視化的能源預測及最佳化服務(結合氣象預報)
- 從營運大數據中, 提出數種策略: 冰機預測性控制, 預冷策略, 負荷移轉
- 帶領工讀生完成1000+個空調設備的電子及系統化

建置智慧建築管理系統 (內政部建研所的Living 3.0智慧化展示空間)
- 整合500+的I/O點位, 包含既有系統及新增感測器 (BACnet/Modbus)
- 向參觀民眾展示智慧節能及最佳化控制 (每年約10,000+遊客), 視覺化呈現建築營運

學歷


National University of Singapore

Department of building  •  2020 - 2024

- 專攻建築能源和營運的機器學習技術。研究全面涵蓋了應用ML/DL的預測、異常檢測、缺失數據填補和數據生成
- Technical team in Kaggle competition: <ASHRAE - Great Energy Predictor III>近20年最大的建築能源數據競賽, 數據集涵蓋全球1500棟建築、收集期間長達三年, 協助分析比賽隊伍的機器學習模型及預測表現, 並比較不同的預測模型建構策略
- 博士論文<Automated Pipelines for Enhanced Energy Data Quality: Anomaly Detection, Data Imputation, and Generative Modeling>, 提出了一套結合異常偵測、缺失預測和數據條件生成的自動化流程, 規模化的將能源大數據進行清理和前處理。
- 2023台灣電力公司邀請演講: 數據與電業之旅系列講座 – 以數據探索能源與評估風險,
- 2022 PyCon APAC (python社群年會)公開演講: 從開放數據閱讀台灣能源 - 數據探索、模型預測和風險評估
- 2022 BuildSys2022 Workshop: "1st ACM BuildSys 2022 Tutorial on Electricity Demand Forecasting"

National Taiwan University

Sustainable Environment and Green Architecture  •  2013 - 2015

綠建築標章制度下之節能成效調查與驗證研究

-執行國內首次對EEWH綠建築標章實質效益的全面檢核, 欲了解國內的綠建築制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  •  2009 - 2013

- NTU Presidential Award (2013)
- Class Representative

學術發表


- Fu, C., Quintana, M., Nagy, Z., & Miller, C. (2024). Filling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation. Applied Thermal Engineering, 236, 121545.

- Canaydin, A., Fu, C., Balint, A., Khalil, M., Miller, C., & Kazmi, H. (2024). Interpretable domain-informed and domain-agnostic features for supervised and unsupervised learning on building energy demand data. Applied Energy, 360, 122741.

- Fu, C., Kazmi, H., Quintana, M., & Miller, C. (2023, November). Enhancing Classification of Energy Meters with Limited Labels using a Semi-Supervised Generative Model. In Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 450-453).

- H. Kazmi, Fu, C., C. Miller, “Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale,” Building and Environment, vol. 239, pp. 110407, 2023.

- Fu, C., Arjunan, P., & Miller, C. (2022, November). Trimming outliers using trees: winning solution of the large-scale energy anomaly detection (LEAD) competition. In Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 456-461).

- Miller, C., Picchetti, B., Fu, C., & Pantelic, J. (2022). Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis. Science and Technology for the Built Environment, 1-18.

- Fu, C., & Miller, C. (2022). Using Google Trends as a proxy for occupant behavior to predict building energy consumption. Applied Energy, 310, 118343.

- Miller, C., Hao, L., Fu, C. (2022). Gradient boosting machines and careful pre-processing work best: ASHRAE Great Energy Predictor III lessons learned. arXiv preprint arXiv:2202.02898.

- Miller, C., Arjunan, P., Kathirgamanathan, A., Fu, C., Roth, J., Park, J. Y., ... & Haberl, J. (2020). The ASHRAE great energy predictor III competition: Overview and results. Science and Technology for the Built Environment, 26(10), 1427-1447.

語言


  • English — 專業
  • Chinese — 母語或雙語