# YuHui Chen > Tech Lead Manager at Google Core ML Location: Cupertino, California, United States Profile: https://flows.cv/yuhuichen I am currently a ML engineer in Google Core ML with 7+ years working experience who has been working on developing/applying new models in CV/NLP domains as well as establishing ML infrastructure to support ML development needs at scale. My recent focus has been around enabling the capabilities of running large foundation models, including large language models and image generation models, on mobile devices with production-ready performance. My passion has been around applying cutting edge machine learning technologies to solving real world problems. I am looking for ML engineering positions to fulfill this goal. My resume: https://drive.google.com/file/d/1EhW6eGSfFkOIoEwYhAkqQ88LYGhUbnEl/view?usp=sharing My Google profile: https://research.google.com/pubs/YuhuiChen.html I received my Ph.D. in Electrical and Computer Engineering from University of Michigan, working with Prof. Alfred Hero on multi-modality image fusion in biomedical and materials in 2015. The main idea of image fusion is to intelligently combine the information from multiple image modalities for better decision making, e.g. detecting anomaly. I received my B.S. in Electrical Engineering from National Taiwan University from 2005 to 2009, working with Prof. Lin-Shan Lee on speech recognition and information retrieval. Personal: My hometown is Taipei, Taiwan, where I was born and grew up. I came to United States in 2010 for my graduate degree and started to learn and enjoy snowboarding since then. I love music (classical, Rock, and R&B) and play a little bit piano and drums. Badminton is my favorite sport which I play regularly. ## Work Experience ### Staff Software Engineer at Google Research/Core ML @ Google Jan 2020 – Present Led Google's on-device generative AI initiatives to scale the high-performance GenAI inference framework to hundreds of millions of users. - Tech lead manager of Google's on-device LLM inference framework, LiteRT-LM(https://github.com/google-ai-edge/LiteRT-LM), enabling the deployment of Gemini Nano to hundreds of millions of devices across multiple platforms, optimizing performance for on-device accelerators (blogpost: https://developers.googleblog.com/en/on-device-genai-in-chrome-chromebook-plus-and-pixel-watch-with-litert-lm/), powering * Chrome built-in LLM API (https://developer.chrome.com/docs/ai/built-in) * LLM Inference API for Developers (https://developers.googleblog.com/en/large-language-models-on-device-with-mediapipe-and-tensorflow-lite/) * On-device GenAI on Chromebook Plus (https://9to5google.com/2024/10/08/recorder-app-chromebook/) * Gemini Nano on Android (https://ai.google.dev/gemini-api/docs/get-started/android_aicore) * Image generative in Pixel Studio (https://www.theverge.com/2024/8/13/24219655/google-pixel-studio-ai-image-generation-app) - Achieved world-record inference speeds for running Stable Diffusion models on-device, pushing the boundaries of mobile AI capabilities. (Paper: https://arxiv.org/abs/2304.11267, Blog: https://ai.googleblog.com/2023/06/speed-is-all-you-need-on-device.html) ### Senior Software Engineer at Google Brain @ Google Jan 2018 – Jan 2020 | Mountain View, California ML Engineer working on creating tools to assist in clinical note generation using the audio of provider-patient encounters. - Technical lead of a team to design and build the infrastructure for ingesting/hosting data to support product experiment and research development. - Developed several models to extract medical concepts from conversational transcripts and published the results in top conference. - Established the model evaluation and monitoring workflow to connect the model performance with product needs and streamlined the model deployment process. ### Software Engineer at Geo @ Google Jan 2015 – Jan 2018 | Mountain View, California - Designed a deep learning model to predict the weekly opening hours schedule from a single storefront image that reaches 90% precision production bar. - Established the system/pipeline to launch the above model that processed over 1.5M photos and contributed to 275K Google Maps edits by Q1 2018. ### Research Assistant @ University of Michigan, Ann Arbor Jan 2011 – Jan 2015 | Ann Arbor, Michigan Research on image registration for fMRI data ### Software Engineering Intern @ Google Jan 2014 – Jan 2014 | Cambridge, MA Work in Google Hotel Finder team. Research on helping the Finder to choose the most representative main image for each hotel to show in the search result. The proposed approach is proven to be able to correct more than %80 of the bad selected main images in the dataset. Manage large amount of images in the database (Bigtable/SSTable) through multi-threading and remote procedure call. ### Second Lieutenant @ R.O.C Army Jan 2009 – Jan 2010 Company Chief Counselor ### Periodic Employee @ ITRI Jan 2007 – Jan 2007 Research on flexible electronic, utilizing flexible solar cells, UV absorber and amplifiers to become flexible UV sensor device. ## Education ### Doctor of Philosophy (PhD) in Electrical Engineering: Systems University of Michigan ### Master of Science (M.S.) in Electrical Engineering: Systems University of Michigan ### Bachelor's degree in Electrical, Electronics and Communications Engineering National Taiwan University ## Contact & Social - LinkedIn: https://linkedin.com/in/yuhuic - Portfolio: https://research.google.com/pubs/YuhuiChen.html --- Source: https://flows.cv/yuhuichen JSON Resume: https://flows.cv/yuhuichen/resume.json Last updated: 2026-04-12