Papers
6
Total Citations
65
H-Index
4
About
Thao Nguyen is a robotics researcher whose work bridges natural language understanding and autonomous manipulation, with a focus on enabling robots to interpret and execute complex, context-rich human commands. Her key contributions lie in developing systems for **language-conditioned object retrieval**, **affordance-based reasoning**, and **hierarchical planning with temporal logic**. Her most influential work, "Robot Object Retrieval with Contextual Natural Language Queries" (2020, 43 citations), pioneered methods for robots to handle ambiguous, context-dependent commands—moving beyond simple object labels to interpret phrases like "the red one next to the cup." She further advanced this line of research with "Grounding Language Attributes to Objects using Bayesian Eigenobjects" (2019, 5 citations), which introduced probabilistic models for matching physical descriptions to observed objects. Nguyen has also made notable contributions to task planning, developing state abstraction techniques that allow robots to reason about non-Markovian specifications, such as "go to the kitchen before going to the second floor." Her work on hierarchical planning (2022, 6 citations) and language-conditioned observation models (2023) demonstrates a sustained effort to make robots more capable of understanding and acting upon natural language in unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1Robot Object Retrieval with Contextual Natural Language Queries43 citations · 2020
- 2Affordance-based robot object retrieval7 citations · 2021
- 3
- 4Grounding Language Attributes to Objects using Bayesian Eigenobjects5 citations · 2019
- 5Language-Conditioned Observation Models for Visual Object Search2 citations · 2023
- 6Planning with State Abstractions for Non-Markovian Task Specifications2 citations · 2019