
Jiayuan Mao
Email: jiayuanm [at] mit [dot] edu Links: CV | Research Statement
Jiayuan Mao is a PhD candidate at MIT EECS, advised by Prof. Josh Tenenbaum and Prof. Leslie Kaelbling. She obtained her Bachelor's degree from Tsinghua University.
Email: jiayuanm [at] mit [dot] edu Links: CV | Research Statement
Jiayuan Mao is a PhD candidate at MIT EECS, advised by Prof. Josh Tenenbaum and Prof. Leslie Kaelbling. She obtained her Bachelor's degree from Tsinghua University.
Underrepresented groups: including but not limited to gender/racial/ethnic minority groups.
My long-term research goal is to build machines that can continually learn concepts (e.g., properties, relations, skills, rules and algorithms) from their experiences and apply them for reasoning and planning in the physical world. The central theme of my research is to decompose the learning problem into learning a vocabulary of neuro-symbolic concepts. The symbolic part describes their structures and how different concepts can be composed; the neural part handles grounding in perception and physics. I leverage structures to make learning more data-efficient, more compositionally generalizable, and also inference and planning faster.
How should we represent various types of concepts?
How to capture the programmatic structures underlying these concepts (The Theory-Theory of Concepts)?
How can we efficiently learn these concepts from natural supervisions (e.g., language, videos)?
How can we leverage the structures of these concepts to make inference and planning faster?
Topics:
Concept Learning and Language Acquisition /
Reasoning and Planning /
Scene and Activity Understanding
Past topics: Object Detection /
Structured NLP
(*/†: indicates equal contribution.)
ICRA 2025
Paper /
Project Page /
Code
CoRL Workshop on Learning Effective Abstractions for Planning 2024
ICRA 2025
Paper /
Project Page /
Code
CoRL 2024 Workshop on Language and Robot Learning (Best Paper)
ICLR 2025
Paper /
Project Page /
Data
ECCV Human-Inspired Computer Vision Workshop 2024
CoRL 2024
Paper /
Project Page
CoRL 2024 Workshop on Learning Effective Abstractions for Planning (Oral)
NeurIPS 2024 Datasets and Benchmarks Track (Oral)
SoCal NLP 2024 (Best Paper)
Paper /
Project Page /
Code /
Data
CogSci 2024 (Best Undergraduate Student Paper) Paper
RSS 2024
Paper /
Project Page
RSS Workshop on Task Specification for General-Purpose Intelligent Robots
ICLR 2024 (Spotlight) Paper / Project Page / Code / MIT News / TechCrunch
ICLR 2024 (Spotlight) Paper / Project Page / Code
NeurIPS 2023 (Spotlight) Paper / Project Page / Code
CoRL 2023
Paper /
Project Page
IROS 2023 Workshop on Leveraging Models for Contact-Rich Manipulation (Spotlight)
(Slides /
Video)
CVPR 2023
Paper /
Project Page /
Code
CVPR 2023 Workshop On Compositional 3D Vision (Oral)
ICLR 2023 (Notable Top 25%) Paper / Project Page
NeurIPS 2022 Datasets and Benchmarks Track Paper / Project Page / Code
NeurIPS 2022 Datasets and Benchmarks Track Paper / Project Page / Code
NeurIPS 2022 Datasets and Benchmarks Track Paper / Project Page / Code
IJCAI 2021 Paper / Project Page / Code
(First two authors contributed equally; order determined by coin toss.)
ACL 2021 (Findings)
Paper /
Talk /
Project Page
SpLU-RoboNLP 2021 (Oral)
CVPR 2021 Paper / Talk / Project Page / Code
ArXiv 2020 Paper
ICCV 2019 Paper / Project Page
(First two authors contributed equally; order determined by coin toss.)ACL 2019 (Best Paper Nomination) Paper / Project Page / Code
ICLR 2019 (Oral) Paper / Project Page / Code / MIT News / MIT Technology Review
ArXiv Preprint Paper