Soroush Nasiriany

I am a CS PhD student at UT Austin, advised by Professor Yuke Zhu at the Robot Perception and Learning Lab. I'm also spending time as a Student Researcher at Google DeepMind. Previously, I recieved my undergraduate and master's degrees from UC Berkeley, where I was advised by Professor Sergey Levine.

I'm interested in building intelligent robot agents that can perform useful behaviors in diverse real world settings. Recently I've been working on harnessing diverse sources of data, namely internet data, robot simulation and real world robot data, to build a powerful foundation model for robotics.


Papers

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Soroush Nasiriany*, Fei Xia*, Wenhao Yu*, Ted Xiao*, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, Quan Vuong, Tingnan Zhang, Tsang-Wei Edward Lee, Kuang-Huei Lee, Peng Xu, Sean Kirmani, Yuke Zhu, Andy Zeng, Karol Hausman, Nicolas Heess, Chelsea Finn, Sergey Levine, Brian Ichter*
Technical report arXiv:2402.07872
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Collaboration
IEEE International Conference on Robotics and Automation (ICRA), 2024
MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
Ajay Mandlekar, Soroush Nasiriany*, Bowen Wen*, Iretiayo Akinola, Yashraj Narang, Linxi Fan, Yuke Zhu, Dieter Fox
Conference on Robot Learning (CoRL), 2023
Robot Learning on the Job: Human-in-the-Loop Manipulation and Learning During Deployment
Huihan Liu, Soroush Nasiriany, Lance Zhang, Zhiyao Bao, Yuke Zhu
Robotics: Science and Systems (RSS), 2023
Best Paper Award Finalist
Learning and Retrieval from Prior Data for Skill-based Imitation Learning
Soroush Nasiriany, Tian Gao, Ajay Mandlekar, Yuke Zhu
Conference on Robot Learning (CoRL), 2022
Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks
Soroush Nasiriany, Huihan Liu, Yuke Zhu
IEEE International Conference on Robotics and Automation (ICRA), 2022
Outstanding Learning Paper
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, Roberto Martín-Martín
Conference on Robot Learning (CoRL), 2021
Oral Presentation
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar, Roberto Mart ́ın-Mart ́ın, Abhishek Joshi, Soroush Nasiriany, Yifeng Zhu
Technical report, 2020
DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies
Soroush Nasiriany*, Vitchyr H. Pong*, Ashvin Nair*, Alexander Khazatsky, Glen Berseth, Sergey Levine
IEEE International Conference on Robotics and Automation (ICRA), 2021
Planning with Goal-Conditioned Policies
Soroush Nasiriany*, Vitchyr H. Pong*, Steven Lin, Sergey Levine
Advances in Neural Information Processing Systems, 2019

Teaching and Service

Teaching

Service