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Blockchain Enginner & AI Lead @Portal Network
Blockchain engineer & Blockchain consulting
Within one month
ICO project in Russia and co-founding a blockchain company where I developed the pioneering deep learning model for estimating the value of decentralized domain names. Currently, I manage ArgsData and MorphusAI, innovative companies focused on delivering cutting-edge data solutions and advancing digital human technology through advanced deep learning methodologies. Professional Skills: Artificial Intelligence Facial Recognition and Facial AI Technologies: Real-Time Facial Expression Tracking and Analysis: Utilizing advanced machine learning algorithms for immediate recognition and analysis of facial expressions, enhancing user interaction experiences. Emotion Recognition Systems: Developing AI systems capable of understanding and responding to
Full-time / Interested in working remotely
4-6 years
Past
Data Engineer @Rooit Inc. (XO App)2023 ~ 2023
・
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
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
6-10 years
中國醫藥大學(China Medical University)
・
臨床醫學研究所
Senior Data Scientist @TeamViewer GmbH2021 ~ Present
・
Data Scientist
Within one month
Develop, implement, and automating deployment of ETL workflows using DBT and Redshift DWH. - Competitive Intelligence - c rawl and analyze the data from competitors to drive insights using NLP. - Analyzing feature usage data to understand customer behavior, predict conversion, and lead generation. - Detecting product's commercial usage using machine learning to push for free-to-paid conversion. - Generated country embeddings using relational data to identify geographic/demographic resemblance. - Clustering 200Mn+ users to tune marketing campaigns and generate sales opportunities. - Conducting hiring interviews, providing mentorship and onboarding junior colleagues. Data Scientist • CHECK24, Münster
Employed
・
Not open to opportunities
Full-time / Interested in working remotely
4-6 years
University of Paderborn
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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.
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
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
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