Linfeng Zhao

Linfeng Zhao

CS Ph.D. Student

Northeastern University


I am Linfeng Zhao (赵林风), a CS Ph.D. student at Khoury College of Computer Sciences of Northeastern University. I’m advised by Prof. Lawson L.S. Wong and also working with Prof. Robin Walters. During PhD: I am visiting and collaborating with MIT Learning and Intelligent Systems group led by Prof. Leslie Kaelbling and Tomás Lozano-Pérez, was a research intern at Boston Dynamics AI Institute with Jennifer L. Barry (2023 Spring-Summer) and earlier at Amazon Science with Kari Torkkola and Dhruv Madeka (2021 Summer). During undergraduate: I interned at Microsoft Research Asia (2019) and earlier worked with Prof. Hao Su at UC San Diego (2018-19).

I focus on decision-making in robotics and work on the intersection of machine learning, robotics and artificial intelligence. My current research centers on improving open-world and long-horizon decision-making for mobile-manipulation robots, like Boston Dynamics Spot, which involves planning (in task and motion level) and learning (state/action representations, world models, skill policies). My recent work involves improving scalability, generalizability, and efficiency for robotic decision-making, including utilizing knowledge and capabilities in pre-trained multimodal models and leveraging symmetry and compositional structures.



Publication List

(2024). Equivariant Action Sampling for Reinforcement Learning and Planning. In Conference Submission.

(2024). Practice Makes Perfect: Planning to Learn Skill Parameter Policies. In Conference Submission.

PDF Code Project Video

(2023). Sample Efficient Modeling of Drag Coefficients for Satellites with Symmetry. In Workshop on Symmetry and Geometry in Neural Representations @ NeurIPS 2023.


(2023). E(2)-Equivariant Graph Planning for Navigation. In RA-L 2024, Present at IROS 2024.

Project arXiv

(2023). Can Euclidean Symmetry Help in Reinforcement Learning and Planning?. In TAGML Workshop @ ICML 2023.


(2023). Equivariant Single View Pose Prediction Via Induced and Restriction Representations. In NeurIPS 2023.


(2022). Integrating Symmetry into Differentiable Planning with Steerable Convolutions. In ICLR 2023, RLDM 2022.

PDF Code Poster Slides ICLR page OpenReview arXiv Webpage (Available soon)

(2022). Toward Compositional Generalization in Object‑Oriented World Modeling. In ICML 2022 (Long Presentation, 2.1%), RLDM 2022.

PDF Code ICML Page Website (Available soon) Poster (ICML) Slides (ICML oral)

(2022). Learning Symmetric Embeddings for Equivariant World Models. In ICML 2022.

PDF Code ICML Page

(2020). Model-based Navigation in Environments with Novel Layouts Using Abstract 2-D Maps. In Deep RL workshop @ NeurIPS 2020.

PDF Poster Slides Video

(2020). Deep Imitation Learning for Bimanual Robotic Manipulation. In NeurIPS 2020.

PDF Poster NeurIPS Page

(2020). Match Plan Generation in Web Search with Parameterized Action Reinforcement Learning. In WWW 2021.

PDF Video Source Document

(2019). InterFact: Towards Interactive Factorization of Actionable Entities. In preparation.