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Shuang Ma


I am a senior researcher in the Autonomous Systems Research team at Microsoft. My research interests center around multimodal learning, computer vision, reinforcement learning, and robotics. Recently, I have been primarily focused on developing large-scale foundational models for perception and control. My particular interest lies in designing general-purpose model for sequential decision-making, utilizing unified approaches to learn from diverse and/or unlabeled sequential data, and boarder logistic and applications with large foundation models.


I obtained my Ph.D. degree in Computer Science from SUNY Buffalo, where I was a member of Ubiquitous Multimedia Lab (UBMM). I was lucky to have my advisor Prof. Chang Wen Chen and my mentors Daniel McduffYale Song, and Ashish Kapoor

Email: yunyikristy AT gmail DOT com


Research Interests

  • Foundation models

  • Multimodal Learning

  • Computer Vision

  • Robotics and Reinforcement Learning


  • I am organizing workshop "PerDream: PERception, Decision making and REAsoning through Multimodal foundational modeling" and co-organizing "Workshop on Robot Learning and SLAM" at ICCV 2023. Our websites are coming soon!

  • I am serving as Area Chair for NeurIPS 2023.

  • We announced SMART and released our code! [Blog][MSR Research Focus][Code]

  • Our paper 'SMART: Self-supervised Multi-task pretrAining with contRol Transformers' is accepted by ICLR 2023 as notable top 25% (Spotlight).

  • Our paper 'LaTTe: Language Trajectory TransformEr' is accepted by ICRA 2023. [Blog][Code]

  • Our team EgoMotion-COMPASS got the 2nd place on two tasks of Ego4D challenge (ECCV 2022). 

  • We announced COMPASS and released our code! [Blog][Code]

  • Our paper 'COMPASS: Contrastive multimodal pretraining for autonomous systems' is accepted by IROS 2022.

  • Our paper 'Reshaping robot trajectories using natural language commands: A study of multi-modal data alignment using transformers' is accepted by IROS 2022

  • Our paper 'CausalCity: Complex Simulations with Agency for Causal Discovery and Reasoning' is accepted by CLeaR 2022. [Blog][Code]


  • Jianchen Lei, Zhejiang University 2023

  • Yao Wei, Zhejiang University 2023

  • Ruijie Zheng, University of Maryland 2023

  • Yanchao Sun, University of Maryland 2022

  • Arthur Fender Coelho Bucker,  Technical University of Munich (TUM) 2022

  • Weijian Xu, UC San Diego 2021

  • Cherie Ho, Carnegie Mellon University 2021

  • Zhaoyang Zeng, Sun Yat-sen University 2020

  • Mingzhi Yu, University of Pittsburgh 2020

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