Jingwen Wang
Software Develop Engineer at Tencent
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolJingwen Wang is a software development engineer with eight years of experience, currently focused on cloud-native back-end systems at Tencent's Cloud and Smart Industries Group. Based in Boston, she brings three years of focused web development experience alongside earlier full-stack and research roles delivering scalable classroom apps and intranet systems. Her background spans production deployment, database-driven services, and MVC-based web apps, with hands-on experience testing at scale (120–180 users) and porting web apps to Android. Jingwen combines enterprise cloud engineering at Tencent with academic rigor from Northeastern and a first-class undergraduate degree from Queen Mary University of London. She’s comfortable bridging research, front-end interfaces, and back-end infrastructure—an asset for teams building cloud-native platforms that require pragmatic optimization and cross-stack fluency.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Telecommunications Engineering with Management, Bachelor of Science - BS, Telecommunications Engineering with Management at Beijing University of Posts and TelecommunicationsMaster of Science in Information Systems, Computer Software Engineering, Master of Science in Information Systems, Computer Software Engineering at Northeastern UniversityBachelor of Science - BS, Telecommunications Engineering with Management, First-class Degree, Bachelor of Science - BS, Telecommunications Engineering with Management, First-class Degree at Queen Mary University of London
English, Chinese
Github Skills (20)
face10
action-localization10
super-resolution10
vision-and-language10
temporal9
stream9
prediction9
pytorch8
sentence7
video-processing7
sst7
ffmpeg7
transformer6
deep-learning6
tensorflow6
Programming languages (1)
Github contributions (5)
JaywongWang/CBP
Dec 2019 - Jan 2020
Official Tensorflow Implementation of the AAAI-2020 paper "Temporally Grounding Language Queries in Videos by Contextual Boundary-aware Prediction"
Contributions:22 commits, 10 PRs, 18 pushes in 23 days
video-analysisboundarypredictionvideo-groundingdeep-learning
JaywongWang/TGN
Dec 2019 - Feb 2020
Tensorflow Reproduction of the EMNLP-2018 paper "Temporally Grounding Natural Sentence in Video"
Contributions:19 commits, 4 PRs, 12 pushes in 2 months
sentencevideo-groundingdeep-learningreproductionvideo-moment-retrieval
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