Wenbo Bao
Marketing Director at American Baby International Education Ltd.
Shanghai, Shanghai, China
Summary
🤩
Rockstar🎓
Top SchoolWenbo Bao is a marketing leader with 11 years of cross-industry experience directing brand and growth strategies from Shanghai, currently serving as Marketing Director at American Baby International Education. He has led marketing teams across education and construction sectors, progressing from assistant roles to head and director positions, with a strong foundation in business administration and finance. Wenbo combines strategic marketing with hands-on project execution—an unusual blend highlighted by technical contributions to an open-source CVPR 2019 project (DAIN) where he adapted a depth-aware frame interpolation model for slow-motion video. Comfortable bridging creative, data-driven, and technical domains, he focuses on improving product usability and campaign effectiveness. Fluent in navigating multinational organizational contexts, he brings pragmatic leadership and a track record of making complex initiatives operational.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Business Administration (B.B.A.), Business, Management, Marketing, and Related Support Services, Bachelor of Business Administration (B.B.A.), Business, Management, Marketing, and Related Support Services at Københavns UniversitetBachelor of Commerce (B.Com.), Accounting and Finance, Bachelor of Commerce (B.Com.), Accounting and Finance at Dalian University
Chinese, English
Github Skills (9)
mask-rcnn10
faster-rcnn10
machine-learning10
pytorch10
computer-vision10
tensor10
deep-learning10
tensorflow10
python9
Programming languages (5)
Github contributions (5)
baowenbo/DAIN
Mar 2019 - Oct 2020
Depth-Aware Video Frame Interpolation (CVPR 2019)
Role in this project:
ML Engineer
ML EngineerContributions:127 commits, 12 PRs, 109 pushes in 1 year 7 months
Contributions summary:Wenbo primarily contributed to the development and modification of a depth-aware video frame interpolation (DAIN) model. Their work included integrating the DAIN model, modifying the model structure, and adapting the model for slow-motion generation. The user also revised demo files and configurations for the project, suggesting active involvement in model deployment and evaluation. The changes indicate a focus on improving the model's functionality and usability for video processing.
frameoptical-flowcomputer-visiondepthvideo-frame
baowenbo/MEMC-Net
Mar 2019 - Jan 2020
Contributions:51 commits, 21 pushes, 2 comments in 9 months
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