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On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
Product Manager @Linker Vision2023 ~ 現在
・
PM/產品經理/專案管理
一個月內
relationship maintenance 24 Merchants, 6 IPs. NFT generation and 3D modeling Web 3.0, Metaverse, NFT-related consultant. OctFeb 2021 Project Engineer Acer Studying cutting-edge AI/DL skills to implement on a medical AI project. 92% accuracy on glaucoma CDR detection. Familiar with object detection, segmentation, and classification AI scenario. Good communication skills with doctors' demands and collaboration with colleagues. Patent Disclosure: Ultrasound detect and notify system. (serial number: I學歷 SepJun 2 National Taiwan University of Science and Technology Masters in Electrical Engineering Thesis "Online Data Stream Analytics
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
4 到 6 年
國立台灣科技大學 National Taiwan University of Science and Technology
・
電機工程
Team Lead @工業技術研究院2020 ~ 現在
・
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
一個月內
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
6 到 10 年
National Chung Cheng University
・
資訊工程學所
Engineering Manager @Viscovery 創意引晴股份有限公司2018 ~ 現在
・
一個月內
Research Experience Research Assistant, Seppresent Communication and Multimedia Lab (CMLab), NTU Proposed a Convolutional Neural Network (CNN) accurately performing fine-grained classification for surveillance car. The model recovered lost details from low resolution image with hints in crawled web images. Leveraged frame similarity to speed up CNN-based object detection and semantic segmentation models, e.g. FPN, PSPNet, YOLO, Faster-RCNN, and SegNet. Proposed a multimodal CNN achieving high fine-grained classification accuracy. The model was trained with both web images and its tags, and could predict solely with image in future testing phase
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
4 到 6 年
國立台灣大學
・
Electrical Engineering
技術長(CTO) @雅匠科技股份有限公司2019 ~ 2022
・
CTO、Sr.Software Manager、Sr.Software Engineer
一個月內
限公司 Java/ Kotlin/ python/ Flutter/ Docker/ Django/ FastAPI/ MySQL/ AWS/ GCP/ OpenCV - Direct management of about 5 to 8. - Mobile app development about AR, temperature/co2 monitoring, beacon parking-related app, etc. - Computer vision for object detection, hand tracking, hair segmentation, and virtual makeup with python language using OpenCV and other open-source. - The assessment of new technology to import and manage engineers' working flow. - Web API development for mobile or Web, and deploy with Docker container on a cloud server or local
就職中
全職 / 我只想遠端工作
4 到 6 年
ISU University
・
電機工程學系就職中
全職 / 對遠端工作有興趣
10 到 15 年
National Taiwan University of Science and Technology
・
Master's degree Computer Science and Information Engineering
Data engineer @H2 Inc.2021 ~ 現在
・
AI engineer, ML engineer, data scientist
三個月內
用 6 種不同 CNN model 搭配 5 種 data augmentation 並且 fine-tune model，達到 93 % Accuracy on validation dataset. Accuracy 達到 93%, 已與醫師合作發表醫學 paper 3. Pathology案件 -建立 two stage segmentation model, stage one segmentation model 達到86% IOU, stage two segmentation model 達到 94% custom dice coefficient 學歷 清華大學 動力機械工程學系技能 Software AWS Airflow Dagster Docker Git Flask Pytorch Tensorflow DVC Languages Python SQL Bash
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
4 到 6 年
清華大學
・
動力機械工程學系
Data science lecturer @Ittraining2020 ~ 現在
・
Data Scientist 資料科學家_數據分析師
一個月內
Detection: Detect Player Contacts from Sensor and Video Data, 2023/03/03 AIGC (生成式AI): - Bronze medal (solo): (Kaggle) Stable Diffusion - Image to Prompts: Deduce the prompts that generated our "highly detailed, sharp focus, illustration, 3d renders of majestic, epic" images, 2023/05/16 Object detection (目標檢測): - 4th place (solo): (Aidea AI CUP) 肺腺癌病理切片影像之腫瘤氣道擴散偵測競賽 I：運用物體偵測作法於找尋STAS, 2022/06/02
就職中
・
目前會考慮了解新的機會
兼職 / 對遠端工作有興趣
15 年以上
Purdue University
・
School of civil engineering (Stochastic & statistical hydrology)Senior Backend Engineer/Machine Learning Engineer @Calyx Inc.2022 ~ 現在
・
後端工程師/系統架構師/機器學習工程師
一個月內
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
6 到 10 年
國立臺灣師範大學
・
地球科學/大氣組Marketing Specialist @TradeUP Securities2021 ~ 現在
・
Marketing Specialist
一個月內
ensuring the timely recording and distribution of clients' rewards. •Drafted, proofread, designed, and distributed both internal and external communications. This included visually compelling Google Display Ads, press releases, engaging blog posts, and posts across multiple social media platforms. •Maximized the use of the CRM system for customer segmentation and targeted marketing. •Coordinated promotional items for prospects and customers, leveraging digital platforms to achieve a wider reach and impact. •Engaged with internal teams to optimize procedures and campaigns that fueled growth marketing initiatives. •Collaborated closely with product and engineering teams to implement strategies aimed at
就職中
・
目前會考慮了解新的機會
全職 / 我只想遠端工作
6 到 10 年
William Paterson University of New Jersey
・
Marketing/Marketing Management, General
BI/DATA Engineer
一個月內
learning input/output and BI features. Foxconn, Senior Data Engineer, OctDec 2018 Collect customer data from various channels and extract valuable information to build ad recommendation models Experience with ETL flow design and develop: ETL between Hadoop and RDB Cleaning TV logs to analyze customer behavior and building key metrics to analyze Construct data flow to manage big data ingestion from upstream application to Hadoop Distributed File System Building data warehouse from scratch and using Hadoop, Hive, Impala, Python to solving data process issue Taiwan Star, Senior BI Developer , AugSep 2017 Implemented customer segmentation an...
全職 / 對遠端工作有興趣
6 到 10 年
最輕量、快速的招募方案，數百家企業的選擇
搜尋履歷，主動聯繫求職者，提升招募效率。
- 瀏覽所有搜尋結果
- 每日可無限次數開啟陌生對話
- 搜尋僅開放付費企業檢視的履歷
- 檢視使用者信箱 & 電話
搜尋技巧
1
嘗試搜尋最精準的關鍵字組合
資深 後端 php laravel
2
將須完全符合的字詞放在雙引號中
"社群行銷"
3
在不想搜尋到的字詞前面加上減號，如果想濾掉中文字，需搭配雙引號使用 (-"人資")
UI designer -UX
職場能力評價定義
專業技能
該領域中具備哪些專業能力（例如熟悉 SEO 操作，且會使用相關工具）。
問題解決能力
能洞察、分析問題，並擬定方案有效解決問題。
變通能力
遇到突發事件能冷靜應對，並隨時調整專案、客戶、技術的相對優先序。
溝通能力
有效傳達個人想法，且願意傾聽他人意見並給予反饋。
時間管理能力
了解工作項目的優先順序，有效運用時間，準時完成工作內容。
團隊合作能力
具有向心力與團隊責任感，願意傾聽他人意見並主動溝通協調。
領導力
專注於團隊發展，有效引領團隊採取行動，達成共同目標。
專業背景
目前狀態
就職中
求職階段
目前沒有興趣尋找新的機會
專業
數據科學家
產業
軟體
工作年資
4 到 6 年
管理經歷
我有管理 1～5 人的經驗
技能
語言能力
求職偏好
希望獲得的職位
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
預期工作模式
全職
期望的工作地點
Taipei, 台灣, Singapore, Japan
遠端工作意願
對遠端工作有興趣
接案服務
否
學歷
學校
National Cheng Kung University
主修科系
Electrical Engineering
Bing-Min(Ben) Wang
Currently, I work as a software engineer on the AdInsight team at Microsoft where I handle petabyte-scale data, maintain stable services, and utilize both deterministic and machine learning techniques to recommend keywords. In addition, I have experience in applying machine learning in other areas, such as healthcare.
I am an open-minded and fast learner, with the ability to quickly adapt to new processes, systems, and technologies. I excel in time management, multitasking, and thrive under pressure. I am passionate about tackling tough technical challenges and collaborating with team members to solve difficult problems. I take pride in bringing my ideas to life through real-world applications.
E-mail: [email protected]
Skills
- Have practical experience in developing and managing distributed systems, as well as handling large-scale data.
- Combine deterministic and ML-based techniques to generate keyword recommendations that meet latency requirements while maintaining high quality.
- Design state-of-the-art deep neural networks to solve imaging problems (2D/3D), sequential/time series and tabular data
- object detection such as Faster R-CNN, SSD and YOLO, image segmentation such as U-Net
- attention model such as Transformer
- Demonstrate a solid understanding of generative models, such as GPT and diffusion models, showcasing proficiency in leveraging their capabilities for various applications
- Test and evaluate algorithms to prove robustness
- Have great communication, planning skills and profound experience in cooperating with experts in other fields
Work Experience
Microsoft，Sep 2021 - Present
Software Engineer, AdInsight (STCA)
- Conduct Ads Globalization:
- Enable ES/IT/NL recommendations in daily services pipeline(new keyword recommendation). About 2~3% increase in the revenue.
- Support markets expansion in real-time services. The real-time product(K2K, keyword to keyword) can support extra 64 markets by leveraging table generated by partner team.
- Improve the quality(coverage and depth) of the suggestions by introducing the INTL(international) TwinBERT trained from partner team.
- Resolve language mismatch issue in daily services pipeline to decrease the dismiss and rate ultimately drive the revenue growth.
- Set up a daily pipeline to monitor the quality of ES/IT/NL suggestions to prevent hurting user experience owing to globalization.
- Resolve MAD(monitor, alerting, diagnosis) service doesn't send alerting emails in time for specific jobs to prevent team from getting ICM tickets
- Leaverage LLM (large language model) to replace human-labeling and reduce ~30% of labeling budget.
HTC Healthcare (DeepQ)，Sep 2018 - Aug 2021 · 3 yrs
Senior Deep Learning Engineer, Deep Learning Apps
- Nodule Detection: Developed the 3D detection model (Faster R-CNN, U-Net like backbone) from scratch and use Focal loss and adding hard negative example gradually to deal with the large class imbalance
- Intracranial Hemorrhage Classification: Developed the ICH classification model (Efficient-Net) combined with transformer encoder to consider sequential information and deployed to hospital PACS system with heatmap visualization
- Ischemic stroke segmentation: Develop the segmentation model to segment core/penumbra zone which can be used in deciding treatment in stroke patient.
- Facial Landmark Detection: Developed the real-time face detection model(SSD: Single Shot MultiBox Detector) from scratch and deployed to mobile web browser(onnxjs, tfjs)
- Fingertip Detection: Improved performance(~5 AP) of the real-time YOLO-like model running on mobile device(tflite) by a novel data augmentation
Competitions
RSNA Intracranial Hemorrhage Detection (Kaggle), ranked top 3% (silver)
- Developed an algorithm to detect acute intracranial hemorrhage and its subtypes
- Multi-label Classification
APTOS 2019 Blindness Detection (Kaggle), ranked top 4% (silver)
- Developed a classifier that output the severity of diabetic retinopathy given the retina images
- Ordinal Classification
KDD CUP 2017 - Task2, ranked top 2.3%
- For every 20-minute time window, predict the entry and exit traffic volumes at tollgates
Projects
Stand ML Group - CheXpert
- Developed a convolutional neural networks that output the probability of 14 observations given the available frontal and lateral radiographs
Credit Scoring (Sinopac), Jul. 2017 to Jul. 2018
- Developed a classifier to predict a company will default or not, and extract the readable rules which are verified by the experts
Education
National Cheng Kung University (NCKU), Sep. 2016 - Jun. 2018
Master of Electrical Engineering
- Thesis: Exploring neural network hyper-parameters on small datasets and hand-crafted features: take credit scoring as an example
- GPA 4.15
National Cheng Kung University (NCKU), Sep. 2012 - Jun. 2016
Bachelor of Electrical Engineering
- Independent Study: Transmitter Front-End Circuit Architecture
Bing-Min(Ben) Wang
Currently, I work as a software engineer on the AdInsight team at Microsoft where I handle petabyte-scale data, maintain stable services, and utilize both deterministic and machine learning techniques to recommend keywords. In addition, I have experience in applying machine learning in other areas, such as healthcare.
I am an open-minded and fast learner, with the ability to quickly adapt to new processes, systems, and technologies. I excel in time management, multitasking, and thrive under pressure. I am passionate about tackling tough technical challenges and collaborating with team members to solve difficult problems. I take pride in bringing my ideas to life through real-world applications.
E-mail: [email protected]
Skills
- Have practical experience in developing and managing distributed systems, as well as handling large-scale data.
- Combine deterministic and ML-based techniques to generate keyword recommendations that meet latency requirements while maintaining high quality.
- Design state-of-the-art deep neural networks to solve imaging problems (2D/3D), sequential/time series and tabular data
- object detection such as Faster R-CNN, SSD and YOLO, image segmentation such as U-Net
- attention model such as Transformer
- Demonstrate a solid understanding of generative models, such as GPT and diffusion models, showcasing proficiency in leveraging their capabilities for various applications
- Test and evaluate algorithms to prove robustness
- Have great communication, planning skills and profound experience in cooperating with experts in other fields
Work Experience
Microsoft，Sep 2021 - Present
Software Engineer, AdInsight (STCA)
- Conduct Ads Globalization:
- Enable ES/IT/NL recommendations in daily services pipeline(new keyword recommendation). About 2~3% increase in the revenue.
- Support markets expansion in real-time services. The real-time product(K2K, keyword to keyword) can support extra 64 markets by leveraging table generated by partner team.
- Improve the quality(coverage and depth) of the suggestions by introducing the INTL(international) TwinBERT trained from partner team.
- Resolve language mismatch issue in daily services pipeline to decrease the dismiss and rate ultimately drive the revenue growth.
- Set up a daily pipeline to monitor the quality of ES/IT/NL suggestions to prevent hurting user experience owing to globalization.
- Resolve MAD(monitor, alerting, diagnosis) service doesn't send alerting emails in time for specific jobs to prevent team from getting ICM tickets
- Leaverage LLM (large language model) to replace human-labeling and reduce ~30% of labeling budget.
HTC Healthcare (DeepQ)，Sep 2018 - Aug 2021 · 3 yrs
Senior Deep Learning Engineer, Deep Learning Apps
- Nodule Detection: Developed the 3D detection model (Faster R-CNN, U-Net like backbone) from scratch and use Focal loss and adding hard negative example gradually to deal with the large class imbalance
- Intracranial Hemorrhage Classification: Developed the ICH classification model (Efficient-Net) combined with transformer encoder to consider sequential information and deployed to hospital PACS system with heatmap visualization
- Ischemic stroke segmentation: Develop the segmentation model to segment core/penumbra zone which can be used in deciding treatment in stroke patient.
- Facial Landmark Detection: Developed the real-time face detection model(SSD: Single Shot MultiBox Detector) from scratch and deployed to mobile web browser(onnxjs, tfjs)
- Fingertip Detection: Improved performance(~5 AP) of the real-time YOLO-like model running on mobile device(tflite) by a novel data augmentation
Competitions
RSNA Intracranial Hemorrhage Detection (Kaggle), ranked top 3% (silver)
- Developed an algorithm to detect acute intracranial hemorrhage and its subtypes
- Multi-label Classification
APTOS 2019 Blindness Detection (Kaggle), ranked top 4% (silver)
- Developed a classifier that output the severity of diabetic retinopathy given the retina images
- Ordinal Classification
KDD CUP 2017 - Task2, ranked top 2.3%
- For every 20-minute time window, predict the entry and exit traffic volumes at tollgates
Projects
Stand ML Group - CheXpert
- Developed a convolutional neural networks that output the probability of 14 observations given the available frontal and lateral radiographs
Credit Scoring (Sinopac), Jul. 2017 to Jul. 2018
- Developed a classifier to predict a company will default or not, and extract the readable rules which are verified by the experts
Education
National Cheng Kung University (NCKU), Sep. 2016 - Jun. 2018
Master of Electrical Engineering
- Thesis: Exploring neural network hyper-parameters on small datasets and hand-crafted features: take credit scoring as an example
- GPA 4.15
National Cheng Kung University (NCKU), Sep. 2012 - Jun. 2016
Bachelor of Electrical Engineering
- Independent Study: Transmitter Front-End Circuit Architecture