Michelle Guo

I am Michelle, a final-year PhD student in the Computer Science Department at Stanford University, where I am fortunate to be co-advised by Jiajun Wu and C. Karen Liu. I am affiliated with the Stanford Artificial Intelligence Laboratory (SAIL), the Stanford Vision and Learning Lab (SVL), and The Movement Lab (TML).

My research is graciously funded by the Meta Research Fellowship and the NSF Graduate Research Fellowship. Previously, I received my BS and MS in Computer Science from Stanford University.

You can reach me at mguo95 [at] cs [dot] stanford [dot] edu!

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Research

My interests lie in the intersection of computer vision, computer graphics, and robotics. I am particularly interested in real-to-simulation (real2sim) problems: how can we create high-fidelity digital twins of the physical world that can be seamlessly integrated into simulators and rendering engines? In parallel, I explore the inverse direction — how to generate 3D objects from text or images that are not only visually plausible but also physically functional and fabricable in the real world.

	PGC: Physics-Based Gaussian Cloth from a Single Pose Michelle Guo, Matt Jen-Yuan Chiang, Igor Santesteban, Nikolaos Sarafianos, Hsiao-yu Chen, Oshri Halimi, Aljaž Božič, Shunsuke Saito, Jiajun Wu, C. Karen Liu, Tuur Stuyck, Egor Larionov CVPR, 2025 (Highlight) project page / arXiv / video Using a hybrid 3DGS + mesh representation allows reconstructing photorealistic, simulation-ready cloth from multi-view images of a static scene.
	CRAFT: Designing Creative and Functional 3D Objects Michelle Guo, Mia Tang, Hannah Cha, Ruohan Zhang, C. Karen Liu, Jiajun Wu (* equal contribution) WACV, 2025 project page / arXiv / paper / video CRAFT generates 3D shapes via a mesh optimization procedure guided by semantic prompts and contact constraints.
	Learning to Design 3D Printable Adaptations on Everyday Objects for Robot Manipulation Michelle Guo, Ziang Liu, Stephen Tian, Zhaoming Xie, Jiajun Wu, C. Karen Liu ICRA, 2024 project page / paper / video Jointly learning to design and control 3D-printable object adaptions, expanding the set of objects that robots can use.
	Learning to Design and Use Tools for Robotic Manipulation Ziang Liu, Stephen Tian, Michelle Guo, C. Karen Liu, Jiajun Wu (* equal contribution) CoRL, 2023 project page / arXiv / paper / video Learning designer and controller policies that allow to robots to rapidly design, prototype, and control tools for goal-conditioned tasks.
	Learning Object-Centric Neural Scattering Functions for Free-viewpoint Relighting and Scene Composition Hong-Xing Yu, Michelle Guo, Alireza Fathi, Yen-Yu Chang, Eric Ryan Chan, Ruohan Gao, Thomas Funkhouser, Jiajun Wu (* equal contribution) TMLR, 2023 project page / arXiv / code / video Making object-centric NeRFs relightable and scene-composable, for both opaque and translucent objects, by modeling neural scattering functions.
	Differentiable Physics Simulation of Dynamics-Augmented Neural Objects Simon Le Cleac'h, Hong-Xing Yu, Michelle Guo, Taylor A Howell, Ruohan Gao, Jiajun Wu, Zachary Manchester, Mac Schwager RA-L, 2023 arXiv / video / poster / slides Making object-centric NeRFs simulation-ready, using a differentiable contact model based on the density field.
	Benchmarking Rigid Body Contact Models Michelle Guo, Yifeng Jiang, Andrew Everett Spielberg, Jiajun Wu, C. Karen Liu L4DC, 2023 project page / paper Analyzing the capabilities of analytical, learned, and hybrid simulators in reproducing real-world rigid body contact behavior.
	Learning Diverse and Physically Feasible Dexterous Grasps with Generative Model and Bilevel Optimization Albert Wu, Michelle Guo, C. Karen Liu CoRL, 2022 arXiv / paper / code / video Dexterous grasping of diverse objects via a generative model and bilevel optimization to plan diverse, physically feasible grasps in the real world.
	DASH: Modularized Human Manipulation Simulation with Vision and Language for Embodied AI Yifeng Jiang, Michelle Guo, Jiangshan Li, Ioannis Exarchos, Jiajun Wu, C. Karen Liu SCA, 2021 arXiv / video / talk slides / code An embodied virtual human that, given natural language commands, performs grasp-and-stack tasks using its own perception, proprioception, and touch, without requiring human motion data.
	A Computer Vision System for Deep Learning-Based Detection of Patient Mobilization Activities in the ICU Serena Yeung, Francesca Rinaldo, Jeffrey Jopling, Bingbin Liu, Rishab Mehra, N. Lance Downing, Michelle Guo, Gabriel M. Bianconi, Alexandre Alahi, Julia Lee, Brandi Campbell, Kayla Deru, William Beninati, Li Fei-Fei, Arnold Milstein Nature (npj) Digital Medicine, 2019 paper
	Audio-Linguistic Embeddings for Spoken Sentences Albert Haque, Michelle Guo, Prateek Verma, Li Fei-Fei ICASSP, 2019 arXiv
	Neural Graph Matching Networks for Fewshot 3D Action Recognition Michelle Guo, Edward Chou, De-An Huang, Shuran Song, Serena Yeung, Li Fei-Fei ECCV, 2018 paper
	Focus on the Hard Things: Dynamic Task Prioritization for Multitask Learning Michelle Guo, Albert Haque, De-An Huang, Serena Yeung, Li Fei-Fei ECCV, 2018 paper
	Conditional End-to-End Audio Transforms Albert Haque, Michelle Guo, Prateek Verma Interspeech, 2018 arXiv
	Measuring the Severity of Depressive Symptoms from Spoken Language and 3D Facial Expressions Albert Haque, Michelle Guo, Adam S Miner, L Fei-Fei NeurIPS Workshop on Machine Learning for Health (ML4H), 2018 arXiv
	Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images Edward Chou, Matthew Tan, Cherry Zou, Michelle Guo, Albert Haque, Arnold Milstein, Li Fei-Fei NeurIPS Workshop on Machine Learning for Health (ML4H), 2018 arXiv
	3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities Bingbin Liu, Michelle Guo, Edward Chou, Rishab Mehra, Serena Yeung, N. Lance Downing, Francesca Salipur, Jeffrey Jopling, Brandi Campbell, Kayla Deru, William Beninati, Arnold Milstein (* equal contribution) Machine Learning for Health Care (MLHC), 2018 paper
	Viewpoint Invariant Convolutional Networks for Identifying Risky Hand Hygiene Scenarios Michelle Guo, Albert Haque, Serena Yeung, Jeffrey Jopling, Lance Downing, Alexandre Alahi, Brandi Campbell, Kayla Deru, William Beninati, Arnold Milstein, Li Fei-Fei NeurIPS Workshop on Machine Learning for Health (ML4H), 2017 paper
	Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance Albert Haque, Michelle Guo, Alexandre Alahi, Serena Yeung, Zelun Luo, Alisha Rege, Jeffrey Jopling, Lance Downing, William Beninati, Amit Singh, Terry Platchek, Arnold Milstein, Li Fei-Fei Machine Learning for Healthcare Conference (MLHC), 2017 arXiv
	Knowledge Distillation for Small-footprint Highway Networks Liang Lu, Michelle Guo, Steve Renals ICASSP, 2017 arXiv
	Lithium-Rich Giants in Globular Clusters Evan N Kirby, Puragra Guhathakurta, Andrew J Zhang, Jerry Hong, Michelle Guo, Rachel Guo, Judith G Cohen, Katia Cunha The Astrophysical Journal (ApJ), 2016 arXiv
	Carbon in Red Giants in Globular Clusters and Dwarf Spheroidal Galaxies Evan N Kirby, Michelle Guo, Andrew J Zhang, Michelle Deng, Judith G Cohen, Puragra Guhathakurta, Matthew D Shetrone, Young Sun Lee, Luca Rizzi The Astrophysical Journal (ApJ), 2015 arXiv

Website template from Jon Barron.