C. Karen Liu
Professor of Computer Science
Develops physics-based character animation and learning methods for human motion and robot control.
C. Karen Liu's lab at Stanford works on planning, control & multi-robot systems and physics-based simulation & animation. 50 papers since 2023, 8 at top venues, mostly TOG and CGF. Applications close .
At a glance
- papers, 2023–2026
- 13/ year
- at T1 venues
- 16%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 1 papers2026 · T1 0 · collecting
- 18 papers2025 · T1 1
- 15 papers2024 · T1 2
- 16 papers2023 · T1 5
T1 venuesOtherVenues: TOG, CGF, CoRL, CVPR, RA-L
Research focuspaper titles that use each topic's words
- Planning, control & multi-robot systems6 papers
- Physics-based simulation & animation6 papers
- human motion6 papers
- character animation1 paper
- develops physics-based0 papers
Paper list
From the lab homepage.
20261 paper
- Nature biomedical engineeringGaitDynamics: a generative foundation model for analyzing human walking and running. (opens in a new tab)
202518 papers
- Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer VisionAddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale. (opens in a new tab)
- —ARCap: Collecting High-quality Human Demonstrations for Robot Learning with Augmented Reality Feedback
- —Chain-of-Modality: Learning Manipulation Programs from Multimodal Human Videos with Vision-Language-Models (opens in a new tab)
- —Crossing the Human-Robot Embodiment Gap with Sim-to-Real RL using One Human Demonstration
- The Journal of experimental biologyDetecting artificially impaired balance in human locomotion: metrics, perturbation effects and detection thresholds. (opens in a new tab)
- RA-LFlying Vines: Design, Modeling, and Control of a Soft Aerial Robotic Arm (opens in a new tab)
- —Generating Detailed Character Motion from Blocking Poses
- CGFGenerative Motion Infilling from Imprecisely Timed Keyframes (opens in a new tab)
- —HEAD: Hand-Eye Autonomous Delivery: Learning Humanoid Navigation, Locomotion and Reaching
- —Human-Object Interaction from Human-Level Instructions
- TOG (T1)Learning to Ball: Composing Policies for Long-Horizon Basketball Moves (opens in a new tab)
- —Lifting Motion to the 3D World via 2D Diffusion (opens in a new tab)
202415 papers
- PLoS computational biologyA simulation framework to determine optimal strength training and musculoskeletal geometry for sprinting and distance running. (opens in a new tab)
- —Behavior-1k: A human-centered, embodied ai benchmark with 1,000 everyday activities and realistic simulation
- —Controllable human-object interaction synthesis
- CGFCreating a 3D Mesh in A-pose from a Single Image for Character Rigging (opens in a new tab)
- —Dexcap: Scalable and portable mocap data collection system for dexterous manipulation
- —DiffusionPoser: Real-time Human Motion Reconstruction From Arbitrary Sparse Sensors Using Autoregressive Diffusion (opens in a new tab)
- SIGGRAPH Asia (T1)FürElise: Capturing and Physically Synthesizing Hand Motion of Piano Performance (opens in a new tab)
- —Iterative Motion Editing with Natural Language (opens in a new tab)
- IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology SocietyLower-Limb Exoskeletons Appeal to Both Clinicians and Older Adults, Especially for Fall Prevention and Joint Pain Reduction. (opens in a new tab)
- CVPR (T1)Motion Diffusion-Guided 3D Global HMR from a Dynamic Camera
- —Object-Centric Dexterous Manipulation from Human Motion Data
- —One-shot transfer of long-horizon extrinsic manipulation through contact retargeting
202316 papers
- —<i>NeMo</i>: 3D <i>Ne</i>ural <i>Mo</i>tion Fields from Multiple Video Instances of the Same Action (opens in a new tab)
- PLOS ONEAddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization. (opens in a new tab)
- TOG (T1)Anatomically Detailed Simulation of Human Torso (opens in a new tab)
- —Benchmarking Rigid Body Contact Models
- —CIRCLE: Capture In Rich Contextual Environments (opens in a new tab)
- SIGGRAPH (T1)DROP: Dynamics Responses from Human Motion Prior and Projective Dynamics
- —EDGE: Editable Dance Generation From Music (opens in a new tab)
- —Ego-Body Pose Estimation via Ego-Head Pose Estimation (opens in a new tab)
- TOG (T1)From Skin to Skeleton: Towards Biomechanically Accurate 3D Digital Humans (opens in a new tab)
- PROCEEDINGS OF THE ACM ON COMPUTER GRAPHICS AND INTERACTIVE TECHNIQUESHierarchical Planning and Control for Box Loco-Manipulation (opens in a new tab)
- TOG (T1)Object Motion Guided Human Motion Synthesis (opens in a new tab)
- CoRL (T1)Reinforcement Learning Enables Real-Time Planning and Control of Agile Maneuvers for Soft Robot Arms
Where alumni went
Alumni are not listed on the lab homepage.
Apply to StanfordFall 2027
Stanford Computer Science PhD
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- Opens
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- TOEFL/IELTS
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Confirmed on the program page.
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Data
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