I currently work at the intersection of robotics, deep reinforcement learning, and computer vision.

Publications

• View-Invariant Policy Learning via Zero-Shot Novel View Synthesis
  Stephen Tian, Blake Wulfe, Kyle Sargent, Katherine Liu, Sergey Zakharov, Vitor Guizilini, Jiajun Wu
  Conference on Robot Learning (CoRL), 2024
  
  

• RoboPack: Learning Tactile-Informed Dynamics Models for Dense Packing
  Bo Ai*, Stephen Tian*, Haochen Shi, Yixuan Wang, Cheston Tan, Yunzhu Li, Jiajun Wu (* equal contribution)
  Robotics: Science and Systems (RSS), 2024
  
  

• Are These the Same Apple? Comparing Images Based on Object Intrinsics
  Klemen Kotar*, Stephen Tian*, Hong-Xing Yu, Daniel L.K. Yamins, Jiajun Wu (* equal contribution)
  Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, 2023
  
  

• Learning to Design and Use Tools for Robotic Manipulation
  Ziang Liu*, Stephen Tian*, Michelle Guo, C. Karen Liu, Jiajun Wu (* equal contribution)
  Conference on Robot Learning (CoRL), 2023
  
  

• Multi-Object Manipulation via Object-Centric Neural Scattering Functions
  Stephen Tian*, Yancheng Cai*, Hong-Xing Yu, Sergey Zakharov, Katherine Liu, Adrien Gaidon, Yunzhu Li, Jiajun Wu (* equal contribution)
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
  
  

• A Control-Centric Benchmark for Video Prediction
  Stephen Tian, Chelsea Finn, Jiajun Wu
  International Conference on Learning Representations (ICLR), 2023
  
  

• MaskViT: Masked Visual Pre-Training for Video Prediction
  Agrim Gupta, Stephen Tian, Yunzhi Zhang, Jiajun Wu, Roberto Martín-Martín, Li Fei-Fei
  International Conference on Learning Representations (ICLR), 2023
  
  

• A Workflow for Offline Model-Free Robotic Reinforcement Learning
  Aviral Kumar*, Anikait Singh*, Stephen Tian, Chelsea Finn, Sergey Levine
  Conference on Robot Learning (CoRL), 2021 (Oral)
  
  

• Model-Based Visual Planning with Self-Supervised Functional Distances
  Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine
  International Conference on Learning Representations (ICLR), 2021 (Spotlight)
  
  

• Learning Predictive Models From Observation and Interaction
  Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn
  European Conference on Computer Vision (ECCV), 2020
  
  

• OmniTact: A Multi-Directional High Resolution Touch Sensor
  Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine
  IEEE International Conference on Robotics and Automation (ICRA), 2020
  
  

• DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation
  Mike Lambeta*, Po-Wei Chou*, Stephen Tian*, Brian Yang*, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra (* equal contribution)
  IEEE Robotics and Automation Letters (RA-L) and IEEE International Conference on Robotics and Automation (ICRA), 2020
  
  

• RoboNet: Large-Scale Multi-Robot Learning
  Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn
  Conference on Robot Learning (CoRL), 2019
  
  

• Manipulation by Feel: Touch Based Control with Deep Predictive Models
  Stephen Tian*, Frederik Ebert*, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine (* equal contribution)
  IEEE International Conference on Robotics and Automation (ICRA), 2019