Reina Wang
Quantitative Developer
United States
Summary
👤
Senior🎓
Top SchoolReina Wang is a Quantitative Developer at D. E. Shaw with nine years of experience bridging machine learning research and production software engineering. A UC Berkeley EECS graduate, she has applied deep learning and uncertainty quantification techniques at Meta/Facebook internships and contributed to image-captioning and attention models in her open-source work. Reina has taught core CS and probability courses as a head TA, creating curriculum and coordinating large course operations, which reflects strong communication and mentorship skills. Her background spans reinforcement learning, graph and vision models, and applied ML for scientific discovery, including generative molecule work at Berkeley Lab. She combines rigorous probabilistic thinking with hands-on model and pipeline implementation, and outside of work she’s an avid table tennis player and sci-fi reader who explores Berkeley’s restaurants. An interesting detail: her GitHub highlights a DeepRNN image captioning project where she implemented multiple CNN backbones and refined attention and loss components, demonstrating both research depth and practical engineering.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Electrical Engineering and Computer Science, Bachelor of Science - BS, Electrical Engineering and Computer Science at University of California, Berkeley
Spanish, English, Chinese
Github Skills (11)
mask-rcnn10
faster-rcnn10
machine-learning10
rnn-model10
image-text10
tensorflow10
image-annotation10
n10
resnet9
python9
vggnet8
Github contributions (5)
bityangke/image_captioning
Sep 2016 - Sep 2016
Contributions:37 commits in 1 day
captionshow-attend-and-telldeep-learningimage-captioncomputer-vision
DeepRNN/visual_question_answering
Sep 2016 - Mar 2018
Contributions:46 commits, 45 pushes, 1 branch in 1 year 5 months
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