Ting Yan
US Partnership Lead at Google
Miami-Fort Lauderdale Area United States
Summary
🤩
Rockstar🎓
Top SchoolTing Yan is a US Partnership Lead at Google with 16 years of cross-functional experience marrying cloud and digital advertising strategy to revenue growth for Fortune clients. She manages a $40M+ annual book within a $200M CPG portfolio and has a track record of launching scalable sales enablement programs that drove product adoption and measurable reach expansion globally. Previously she led sales development, industry research, and marketing efforts that positioned Google as a thought leader in brandformance, winning internal awards for brand-building and operational excellence. Ting’s background in social and consumer psychology (NYU MA) and English (Yale BA) informs a rare blend of analytical rigor and narrative skill when aligning C-suite stakeholders and agency partners. Less obvious: she also contributes technical ML optimizations to resource-constrained inference (TensorFlow Lite Micro), showing hands‑on curiosity about deploying models to embedded targets. Based in the Miami–Fort Lauderdale area, she excels at translating complex product capabilities into new revenue streams and long-term partnerships.
6 years of coding experience
3 years of employment as a software developer
Master of Arts - MA, Psychology (specializing in Social & Consumer), Master of Arts - MA, Psychology (specializing in Social & Consumer) at New York UniversityB.A., English, B.A., English at Yale University
mandarin (conversational)
Github Skills (10)
quantization10
embedded10
machine-learning10
tensorflow-lite10
sys10
cprogramming-language9
xtensa9
neural-network9
c-language9
convolutional-neural-networks9
Programming languages (1)
Github contributions (5)
tensorflow/tflite-micro
Dec 2021 - Jun 2022
Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).
Role in this project:
ML Engineer
ML EngineerContributions:189 reviews, 38 commits, 44 PRs in 6 months
Contributions summary:Ting contributed to the optimization and adaptation of TensorFlow Lite for microcontrollers, specifically focusing on the HiFi4 and HiFi5 architectures. Their work involved updating and integrating HiFi4 nnlib libraries, enabling and optimizing convolutional neural network (conv2d) operations, and adding support for int16 and int8 quantization. The user also addressed issues with the existing kernels, including those related to the quantization of the softmax operator.
signalml-modelslow-powerprocessorsdeployment
tingyan19/tflite-micro
Dec 2021 - Jun 2022
TensorFlow Lite for Microcontrollers
Contributions:178 pushes, 38 branches in 6 months
tensorflow-litelitetensorflowmicrocontrollers
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