Yanwu Xu, Ph.D.
Advancing fast, compact, and on-device generative media for image and video synthesis and editing.
I am a Senior Software Engineer at Google, where I focus on efficient and on-device generative models across text-to-image generation, generalist image editing, and video synthesis. Previously, I worked as a Senior Research Scientist at FinBone building generative tools for AI filmmaking workflows, and as a Research Scientist at Snap Inc. (Creative Vision) researching mobile-friendly image and video models.
I received my Ph.D. in Electrical and Computer Engineering from Boston University in 2024, advised by Dr. Kayhan Batmanghelich and co-advised by Dr. Mingming Gong, with a dissertation on improving the efficiency of conditional generative models. Earlier, I earned an M.S. in Intelligent Systems from the University of Pittsburgh (2022) and completed multiple research internships and student researcher terms at Google (2022–2023).
Bay Area, CA
01 / Acceleration
Few- & One-Step Diffusion
Hybrid Diffusion-GAN training and adversarial distillation for real-time synthesis (SIDDMs, UFOGen, SF-V).
02 / Mobile & Edge
On-Device Image & Video
Compact architectures and inference optimization for mobile deployment (BlazeEdit, MobileDiffusion, SnapGen, SnapGen-V, Mobile-VTON).
03 / Foundations & 3D
Generative Theory & Medical AI
Conditional GAN alignment, unpaired image translation, and text-guided 3D volumetric medical synthesis (MedSyn, TAC-GAN).
Featured Work & Public Releases
Publicly released models, research milestones, and product contributions spanning Google DeepMind, Google, and Snap Research.
Veo 3
Publicly credited under key research and engineering contributions to Google DeepMind’s Veo 3 video generation model.
BlazeEdit
A 195M-parameter generalist on-device image-to-image diffusion editor consolidating five tasks with 290 ms inference on Pixel 10.
SnapGen & SnapGen-V
379M-parameter on-device 1024×1024 text-to-image generation in 1.4s (Highlight), extended to generating 5s mobile videos within 5s.
UFOGen
You Forward Once: Diffusion-GAN hybrid enabling single-step large-scale text-to-image generation and editing.
MobileDiffusion
Subsecond text-to-image diffusion on mobile hardware via streamlined UNet attention and sampling optimization.
SF-V
Single Forward Video Generation Model achieving single-step video diffusion through adversarial fine-tuning.
Selected Publications
Recent representative work on efficient diffusion, mobile media generation, and medical imaging.
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BlazeEdit: Generalist Image Editing on Mobile Devices with Image-to-Image Diffusion Models
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Mobile-VTON: High-Fidelity On-Device Virtual Try-On
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SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training
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SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device
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UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANs
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MedSyn: Text-Guided Anatomy-Aware Synthesis of High-Fidelity 3D CT Images
Experience & Education
Industry engineering, research leadership, and academic training.
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Sep 2025 – Present · Sunnyvale, CA
Senior Software Engineer
Google
Developing efficient and on-device visual generation and editing models, latency optimization, and production deployment.
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Jun 2025 – Sep 2025 · Los Angeles, CA
Software Engineer
Google
Built on-device image and video generation pipelines balancing latency, memory footprint, and fidelity.
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Jan 2025 – May 2025 · Los Angeles, CA
Senior Research Scientist
FinBone
Researched generative image and video models for controllable AI filmmaking workflows.
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Aug 2024 – Dec 2024 · Los Angeles, CA
Research Scientist, Creative Vision
Snap Inc.
Worked on fast visual generation for mobile and server deployment (SF-V, SnapGen, SnapGen-V).
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May 2022 – Nov 2023 · Mountain View, CA & Boston, MA
Research Intern & Student Researcher
Google
Researched Diffusion-GAN hybrids, 2D/3D visual stylization, and subsecond mobile diffusion (SIDDMs, UFOGen, MobileDiffusion).
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2023 – 2024 · Boston, MA
Ph.D., Electrical & Computer Engineering
Boston University
Advised by Dr. Kayhan Batmanghelich and co-advised by Dr. Mingming Gong.
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2019 – 2022 · Pittsburgh, PA
M.S., Intelligent Systems Program
University of Pittsburgh
Research on generative modeling, domain generalization, and medical image analysis.
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2013 – 2017 · Changsha, China
B.S., Mechanical & Electronic Engineering
Central South University
News & Milestones
Recent announcements and recognitions.
- 2026 BlazeEdit accepted to CVPR 2026 EDGE Workshop; Mobile-VTON accepted to CVPR 2026; MatrixFSDP released on arXiv.
- 2025 Joined Google full-time (Jun) and promoted to Senior Software Engineer (Sep); SnapGen (CVPR 2025 Highlight) & SnapGen-V accepted to CVPR 2025.
- 2024 Completed Ph.D. at Boston University; joined Snap Inc.; SF-V (NeurIPS), MobileDiffusion (ECCV), UFOGen (CVPR), and MedSyn (IEEE TMI) published.
- 2023 SIDDMs accepted to NeurIPS 2023; Shortest Path Regularization accepted to CVPR 2023.
- 2022 MSPC accepted to CVPR 2022; Adversarial Consistency accepted to MICCAI 2022; Hierarchical Amortized GAN published in IEEE JBHI; started Google internship.
- 2021 Papers accepted to ICCV 2021, ACM MM 2021, and IJCAI WSRL Workshop.
- 2018–20 Two papers at AAAI 2020; TAC-GAN (NeurIPS 2019 Spotlight); Frontiers in Neuroscience 2020; ACCV 2018 & MICCAI BraTS 2018.
Published Patent Applications
Publicly published patent applications assigned to Google LLC.
US20250157008A1 · 2025
Image Generation with Minimal Denoising Diffusion Steps
US20250165756A1 · 2025
Resource-Efficient Diffusion Models
WO2024254328A1 · 2024