Song Wang
Applied Scientist at ShortTok
Austin, Texas, United States
Summary
👤
Senior🎓
Top SchoolSong Wang is an applied scientist specializing in NLP and multimodal generative AI, who completed a Ph.D. in Electrical and Computer Engineering at UT Austin under Joydeep Ghosh and Ying Ding. With 11 years of industry and research experience, he has translated academic advances into product-focused work at ShortTok—where he moved from intern to full-time scientist building large-scale video AI—and at Amazon Robotics, where he cut annotation costs by ~25% using noisy-click supervision. He combines deep statistical grounding with practical LLM and multimodal model engineering, informed by a Master’s from UT Austin and an IoT engineering background from Beijing and Queen Mary. Based in Austin, Song blends rigorous research with production deployment experience across cloud-scale video and vision-language systems. An interesting thread through his career is optimizing data efficiency—getting near state-of-the-art results with weaker supervision—which informs his approach to scalable model development.
11 years of coding experience
5 years of employment as a software developer
Doctor's Degree Electrical and Computer Engineering, Doctor's Degree Electrical and Computer Engineering at The University of Texas at AustinBachelor of Engineering - BE Internet of Things Engineering, Bachelor of Engineering - BE Internet of Things Engineering at Beijing University of Posts and TelecommunicationsBachelor of Engineering - BE Internet of Things Engineering, Bachelor of Engineering - BE Internet of Things Engineering at Queen Mary University of London
Github Skills (77)
transformers10
language-model10
python10
deep-learning10
transformer10
nlp10
tensorflow10
natural-language-processing10
jupyter-notebook10
amazon10
pytorch10
machine-learning10
bert10
speech-recognition10
ctc9
Programming languages (3)
Github contributions (5)
songwang41/PhysicianReferral
Oct 2015 - May 2023
Contributions:23 pushes, 1 branch in 7 years 8 months
songwang41/unilm
Dec 2019 - Nov 2022
UniLM - Unified Language Model Pre-training
Contributions:2 PRs, 5 pushes, 2 branches in 2 years 11 months
pytorchnlplanguage-modeldeep-learningtraining
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