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Avatar of Alex Yu.
Avatar of Alex Yu.
Product Manager @Linker Vision
2023 ~ Present
PM/產品經理/專案管理
Within one month
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
Business Development
Deep Learning
PYTHON
Employed
Open to opportunities
Full-time / Interested in working remotely
4-6 years
國立台灣科技大學 National Taiwan University of Science and Technology
電機工程
Avatar of the user.
Avatar of the user.
Team Lead @工業技術研究院
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
C++
Python
Deep Learning
Employed
Open to opportunities
Full-time / Interested in working remotely
6-10 years
National Chung Cheng University
資訊工程學所
Avatar of 金爾康.
Avatar of 金爾康.
Engineering Manager @Viscovery 創意引晴股份有限公司
2018 ~ Present
Within one month
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
Deep Learning
Computer Vision
FastAPI
Employed
Open to opportunities
Full-time / Interested in working remotely
4-6 years
國立台灣大學
Electrical Engineering
Avatar of Tsung Hsien Chen.
Avatar of Tsung Hsien Chen.
技術長(CTO) @雅匠科技股份有限公司
2019 ~ 2022
CTO、Sr.Software Manager、Sr.Software Engineer
Within one month
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
Python
Java
Dart(Flutter)
Employed
Full-time / Remote Only
4-6 years
ISU University
電機工程學系
Avatar of the user.
Avatar of the user.
資深經理 @緯創資通
2021 ~ Present
Technical Manager
Within six months
Research
Unsupervised Learning
Computer Science
Employed
Full-time / Interested in working remotely
10-15 years
National Taiwan University of Science and Technology
Master's degree Computer Science and Information Engineering
Avatar of 施冠宇.
Avatar of 施冠宇.
Data engineer @H2 Inc.
2021 ~ Present
AI engineer, ML engineer, data scientist
Within three months
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
Airflow
Docker
AWS
Employed
Open to opportunities
Full-time / Interested in working remotely
4-6 years
清華大學
動力機械工程學系
Avatar of 陳惠龍.
Avatar of 陳惠龍.
Data science lecturer @Ittraining
2020 ~ Present
Data Scientist 資料科學家_數據分析師
Within one month
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
nlp-rasa
recommender system
pytorch tensorflow
Employed
Open to opportunities
Part-time / Interested in working remotely
More than 15 years
Purdue University
School of civil engineering (Stochastic & statistical hydrology)
Avatar of the user.
Avatar of the user.
Senior Backend Engineer/Machine Learning Engineer @Calyx Inc.
2022 ~ Present
後端工程師/系統架構師/機器學習工程師
Within one month
Fortran
JavaScript
vue.js
Employed
Open to opportunities
Full-time / Interested in working remotely
6-10 years
國立臺灣師範大學
地球科學/大氣組
Avatar of Crystal Chang.
Avatar of Crystal Chang.
Marketing Specialist @TradeUP Securities
2021 ~ Present
Marketing Specialist
Within one month
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
Digital Marketing
Employed
Open to opportunities
Full-time / Remote Only
6-10 years
William Paterson University of New Jersey
Marketing/Marketing Management, General
Avatar of 張致瑋.
BI/DATA Engineer
Within one month
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...
SQL
my-sql
ETL
Full-time / Interested in working remotely
6-10 years

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Within one year
Software engineer at Microsoft
Logo of Microsoft.
Microsoft
2021 ~ Present
Taipei, 台灣
Professional Background
Current status
Employed
Job Search Progress
Not open to opportunities
Professions
Data Scientist
Fields of Employment
Software
Work experience
4-6 years
Management
I've had experience in managing 1-5 people
Skills
Python
AI & Machine Learning
Big Data
Computer Vision
Linux
Languages
Job search preferences
Positions
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
Job types
Full-time
Locations
Taipei, 台灣, Singapore, Japan
Remote
Interested in working remotely
Freelance
No
Educations
School
National Cheng Kung University
Major
Electrical Engineering
Print

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

Resume
Profile

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