Linfeng Zhao

CS Ph.D. Student

Northeastern University

Biography

I am Linfeng Zhao (赵林风), a CS Ph.D. student at Khoury College of Computer Sciences of Northeastern University since 2019. I’m advised by Prof. Lawson L.S. Wong and also working with Prof. Robin Walters. My research interests lie in the intersection of machine learning, robotics and artificial intelligence.

I study how structure helps improve learning and generalization in model-based reinforcement learning and planning and focus on robotic manipulation and navigation, including: (1) structured representation learning of state and action, (2) factored/structured world modeling and planning, etc.

During PhD, I am interning in part-time at Boston Dynamics AI Institute with Jennifer L. Barry, and interned at Amazon Science with Kari Torkkola and Dhruv Madeka in 2021 Summer. During undergraduate, I interned at Microsoft Research Asia in fourth year and earlier worked with Prof. Hao Su at UC San Diego.

News

[2023/01] Starting internship at Boston Dynamics AI Institute locally in Boston.
[2023/01] Two papers (symmetric planning, implicit differentiable planning) accepted at ICLR 2023.
[2022/12] Physically attend NeurIPS in New Orleans.
[2022 Summer] I’ll physically attend RLDM (Providence), RSS (New York City), and ICML (Baltimore) this summer. Let’s chat!
[2022/06] Spotlight talk on symmetric planning at RSS 2022 workshop Implicit Representation for Robotic Manipulation.
[2022/05] Oral talk on compositional generalization (virtually) at ICRA 2022 workshop Compositional Robotics.
[2022/05] Our paper on compositional generalization is accepted to ICML 2022 as Long Presentation (117/5630, 2.1%, oral).
[2022/05] Another paper on symmetric embedding for equivariant world models is accepted to ICML 2022 as Short Presentation (poster).
[2022/03] Two papers (compositional generalization, symmetric planning) to appear at RLDM 2022 (non-archival).
[2021/06] Summer internship at Amazon Science in Seattle.

Featured Publications

Linfeng Zhao, Huazhe Xu, Lawson L.S. Wong

September 2022 In ICLR 2023

Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation

We study how implicit differentiation helps scale up and improve convergence of differentiable planning algorithms.

PDF OpenReview

Linfeng Zhao, Xupeng Zhu, Lingzhi Kong, Robin Walters, Lawson L.S. Wong

May 2022 In ICLR 2023, RLDM 2022

Integrating Symmetry into Differentiable Planning with Steerable Convolutions

We formulate how differentiable planning algorithms can exploit inherent symmetry in path planning problems, named SymPlan, and propose practical algorithms.

PDF Webpage (Available soon) OpenReview

Linfeng Zhao, Lingzhi Kong, Robin Walters, Lawson L.S. Wong

January 2022 In ICML 2022 (Long Presentation, 2.1%), RLDM 2022

Toward Compositional Generalization in Object‑Oriented World Modeling

We formulate compositional generalization in object-oriented world modeling, and propose a soft and efficient mechanism for practice.

PDF Code ICML Page Website (Available soon) Poster (RLDM, v1) Poster (ICML, v2)

Jung Yeon Park, Ondrej Biza, Linfeng Zhao, Jan-Willem van de Meent, Robin Walters

January 2022 In ICML 2022

Learning Symmetric Embeddings for Equivariant World Models

We learn latent representations enforced with known transformation laws (group action), and apply this idea on equivariant latent world modeling.

PDF Code ICML Page

Publications

Publication List

Linfeng Zhao, Huazhe Xu, Lawson L.S. Wong (2022). Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation. In ICLR 2023.

PDF OpenReview

Linfeng Zhao, Aswin Shriram Thiagarajan, Lawson L.S. Wong (2022). Learning to Navigate in Mazes with Novel Layouts Using Abstract Top-down Maps. Under Conference Review.

(Extended version coming soon)

Linfeng Zhao, Xupeng Zhu, Lingzhi Kong, Robin Walters, Lawson L.S. Wong (2022). Integrating Symmetry into Differentiable Planning with Steerable Convolutions. In ICLR 2023, RLDM 2022.

PDF Webpage (Available soon) OpenReview

Linfeng Zhao, Lingzhi Kong, Robin Walters, Lawson L.S. Wong (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 (RLDM, v1) Poster (ICML, v2)

Jung Yeon Park, Ondrej Biza, Linfeng Zhao, Jan-Willem van de Meent, Robin Walters (2022). Learning Symmetric Embeddings for Equivariant World Models. In ICML 2022.

PDF Code ICML Page

Linfeng Zhao, Lawson L.S. Wong (2020). Model-based Navigation in Environments with Novel Layouts Using Abstract 2-D Maps. In Deep RL workshop at NeurIPS 2020.

PDF Poster Slides Video

Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza, Linfeng Zhao, Lawson L.S. Wong, Rose Yu (2020). Deep Imitation Learning for Bimanual Robotic Manipulation. In NeurIPS 2020.

PDF Poster NeurIPS Page

Linfeng Zhao, Ziyan Luo, Wei Cheng, Sihao Chen, Qi Chen, Hui Xue, Haidong Wang, Chuanjie Liu, Mao Yang, Lintao Zhang (2020). Match Plan Generation in Web Search with Parameterized Action Reinforcement Learning. In WWW 2021.

PDF Video Source Document

Linfeng Zhao, Hao Su (2019). InterFact: Towards Interactive Factorization of Actionable Entities. In preparation.

Contact

zhao.linf@northeastern.edu