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4-6 years
6-10 years
10-15 years
More than 15 years
Software engineer
Algorithm Research & Development @適着三維科技股份有限公司 TG3D Studio Inc.2021 ~ Present
・
Software Engineer
Within one month
Patrick Hsu AI Research & Development As a seasoned AI engineer with six years of experience, I specialize in computer vision, 3D body model reconstruction, generative AI, and possessing some knowledge in natural language processing (NLP). | New Taipei City, [email protected] Work Experience (6 years) Algorithm Research & Design• TG3D Studio MayPresent A skilled engineer specialized in computer vision and generative AI with experience in developing and training AI models for digital fashion applications. Body AI: Virtual Try On Integrated cutting-edge technologies such as Stable Diffusion, ControlNet, and Prompt Engineering to create a sophisticated system for
Employed
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Full-time / Interested in working remotely
4-6 years
國立台灣大學
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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
Studying
Job Search Progress
Professions
Software Engineer, Python Developer, Machine Learning Engineer
Fields of Employment
Software, Artificial Intelligence / Machine Learning, Robotics
Work experience
Less than 1 year
Management
None
Skills
Languages
English
・
Professional
German
・
Fluent
Chinese
・
Native or Bilingual
Job search preferences
Positions
Software Engineer
Job types
Full-time
Locations
台灣台北市, 台灣新北市, 台灣新竹市新竹, 台灣桃園
Remote
Interested in working remotely
Freelance
No
Educations
School
國立清華大學
Major
資訊應用研究所
林佳縈 Chia Ying Lin
Computer Vision Reseacher
Computer Vision Lab, NTHU
With 4-year solid training in computer science fundamentals, 2-year independent research experience in computer vision, and diverse hands-on development experiences, I always pursue excellence, crave new challenges, and am open to all possibilities.
https://github.com/lykasbongbongbong
Skills
Languages
- Python (familiar)
- C++, C
- JAVA
Deep Learning Frameworks
- PyTorch (familiar)
- Tensorflow
CV & DL Libraries
- OpenCV
- Keras
Development Tools
- Git/Github
- RESTFul APIs
Web Development
- HTML, CSS, JS
- Python Flask
- PHP, Laravel
- MySQL, NoSQL(mongoDB)
- AWS
Others
- English TOEFL iBT 97
- English TOEIC 935
- German B2
Education
Master's Studies, Computer Vision Lab, NTHU
Dept. Information Systems and Application, Sep 2020~Now
- Anomaly detection and segmentation for smart manufacturing as primary research target
Bachelor Degree, WASN Lab, NCU
Dept. Computer Science, Sep 2016 ~ June 2020
Exchange Student, Hochschule München, Germany
Dept. Informatik (Computer Science), Sep 2019 ~ Feb 2020
Experiences
August 2021
Attendee,
Machine Learning Summer School, NTU
August 2021
Backend Developer (Anomaly Detection Demo Website),
CVLab, FUTEX 2021
- Use Python Flask, MySQL for RestFul APIs development
- Optimized backend system with Python threading to support sudden massive traffic
June 2018 ~ July 2019, 1y1m
Full-Stack Web Developer (NCU Internship Web)
Career Center NCU
- Reconstruct website with Laravel Framework
- Optimize backend and database to handle larger amounts of access
- Over 30% of users received intern opportunities via this site
- Website Link: https://ncuinternship.careercenter.ncu.edu.tw/
Master Thesis:
SABDN: Self-Attention Based Deviation Network for few-shot anomaly detection and segmentation (Under Review ECCV 2022)
Contributions
- Combine self-attention mechanism with feature extraction CNN network and anomaly synthesis mechanism for anomaly scoring to achieve outstanding anomaly detection accuracy under few-shot setting
- Reach SOTA performance on benchmark dataset MVTecAD dataset and BTAD dataset with over 90 percent reduction in training data requirements
Side Projects
GlueGAN: a generative model based on SuperGlue structure
- Extend MagicLeap’s SuperGlue end-to-end GNN concept for object synthesis to solve synthetic object image generation problem
- 10% accuracy improvement compared to initial GAN backbone
Let's play GAN with flows and friends!
- Generate synthetic object images with multi-label conditions with conditional GAN manner
- Human faces generation by conditional normalizing flow
2048: by Temporal Difference Learning Approach (RL)
- Construct TD-learning algorithm and design own n-tuple network to solve 2048 game
- Reach 98% 2048-tile win rate in 1000 games
The LunarLander: under Deep Q-Network and DDPG manner (RL)
- Implement DQN and DDPG network to solve LunarLander game problem
- Thoroughly understand Deep Q-learning, actor-critic mechanism
Real-Time car detection and counting system
- Retrain YOLOv3 with our own hatchback dataset
- Reach average accuracy: 99% on both day-light and evening scenarios
林佳縈 Chia Ying Lin
Computer Vision Reseacher
Computer Vision Lab, NTHU
With 4-year solid training in computer science fundamentals, 2-year independent research experience in computer vision, and diverse hands-on development experiences, I always pursue excellence, crave new challenges, and am open to all possibilities.
https://github.com/lykasbongbongbong
Skills
Languages
- Python (familiar)
- C++, C
- JAVA
Deep Learning Frameworks
- PyTorch (familiar)
- Tensorflow
CV & DL Libraries
- OpenCV
- Keras
Development Tools
- Git/Github
- RESTFul APIs
Web Development
- HTML, CSS, JS
- Python Flask
- PHP, Laravel
- MySQL, NoSQL(mongoDB)
- AWS
Others
- English TOEFL iBT 97
- English TOEIC 935
- German B2
Education
Master's Studies, Computer Vision Lab, NTHU
Dept. Information Systems and Application, Sep 2020~Now
- Anomaly detection and segmentation for smart manufacturing as primary research target
Bachelor Degree, WASN Lab, NCU
Dept. Computer Science, Sep 2016 ~ June 2020
Exchange Student, Hochschule München, Germany
Dept. Informatik (Computer Science), Sep 2019 ~ Feb 2020
Experiences
August 2021
Attendee,
Machine Learning Summer School, NTU
August 2021
Backend Developer (Anomaly Detection Demo Website),
CVLab, FUTEX 2021
- Use Python Flask, MySQL for RestFul APIs development
- Optimized backend system with Python threading to support sudden massive traffic
June 2018 ~ July 2019, 1y1m
Full-Stack Web Developer (NCU Internship Web)
Career Center NCU
- Reconstruct website with Laravel Framework
- Optimize backend and database to handle larger amounts of access
- Over 30% of users received intern opportunities via this site
- Website Link: https://ncuinternship.careercenter.ncu.edu.tw/
Master Thesis:
SABDN: Self-Attention Based Deviation Network for few-shot anomaly detection and segmentation (Under Review ECCV 2022)
Contributions
- Combine self-attention mechanism with feature extraction CNN network and anomaly synthesis mechanism for anomaly scoring to achieve outstanding anomaly detection accuracy under few-shot setting
- Reach SOTA performance on benchmark dataset MVTecAD dataset and BTAD dataset with over 90 percent reduction in training data requirements
Side Projects
GlueGAN: a generative model based on SuperGlue structure
- Extend MagicLeap’s SuperGlue end-to-end GNN concept for object synthesis to solve synthetic object image generation problem
- 10% accuracy improvement compared to initial GAN backbone
Let's play GAN with flows and friends!
- Generate synthetic object images with multi-label conditions with conditional GAN manner
- Human faces generation by conditional normalizing flow
2048: by Temporal Difference Learning Approach (RL)
- Construct TD-learning algorithm and design own n-tuple network to solve 2048 game
- Reach 98% 2048-tile win rate in 1000 games
The LunarLander: under Deep Q-Network and DDPG manner (RL)
- Implement DQN and DDPG network to solve LunarLander game problem
- Thoroughly understand Deep Q-learning, actor-critic mechanism
Real-Time car detection and counting system
- Retrain YOLOv3 with our own hatchback dataset
- Reach average accuracy: 99% on both day-light and evening scenarios