Jiajun Wu

Massachusetts Institute of Technology, Stanford University, Google (United States), Institute of Occupational Medicine, Ministry of Education, Shanghai University, Guangdong University of Technology, Jianghan University

Papers

57

Total Citations

2,079

H-Index

22

About

No biography available yet.

Research Focus

Artificial intelligence55 · 2,063 citations
Computer science55 · 2,063 citations
Robot41 · 1,155 citations
Human–computer interaction25 · 947 citations
Computer graphics (images)14 · 865 citations
Computer vision26 · 859 citations
Representation (politics)12 · 707 citations
Simulation12 · 593 citations
Physics engine6 · 456 citations
Robotics13 · 451 citations
Mathematics14 · 429 citations
Set (abstract data type)7 · 416 citations

Key Achievements

22
H-Index
57
Papers
2,079
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
223 citations · 2019
📈 Most Prolific Year: 2023 (15 Papers)
🤝 Key Collaborators: 357
🏛 Institutions: Massachusetts Institute of Technology, Stanford University, Google (United States), Institute of Occupational Medicine, Ministry of Education, Shanghai University

Top Papers

  1. 1
    ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
    223 citations · 2019
  2. 2
    Neural Radiance Flow for 4D View Synthesis and Video Processing
    209 citations · 2021
  3. 3
    See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion
    124 citations · 2019
  4. 4
    Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration<sup>0</sup>
    119 citations · 2024
  5. 5
    3D Shape Perception from Monocular Vision, Touch, and Shape Priors
    118 citations · 2018
  6. 6
    DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
    108 citations · 2024
  7. 7
    Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
    107 citations · 2018
  8. 8
    Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing
    95 citations · 2018
  9. 9
    Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
    88 citations · 2018
  10. 10
    DensePhysNet: Learning Dense Physical Object Representations Via Multi-Step Dynamic Interactions
    87 citations · 2019

Key Collaborators

JBJoshua B. Tenenbaum18 shared papersRGRuohan Gao7 shared papersJBJeannette Bohg6 shared papersSSShuran Song6 shared papersYLYunzhu Li6 shared papersSTStephen Tian6 shared papersCFChelsea Finn5 shared papersDSDorsa Sadigh5 shared papersARAlberto Rodríguez5 shared papersRMRoberto Martín-Martín4 shared papersLFLi Fei-Fei4 shared papersMBMaria Bauzá4 shared papersJGJensen Gao4 shared papersWYWenzhen Yuan4 shared papersNFNima Fazeli4 shared papersWTWilliam T. Freeman4 shared papersZXZhenjia Xu4 shared papersHWHomer Walke4 shared papersKHKyle Hsu4 shared papersCAChristopher Agia4 shared papers
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