Stefanie Tellex Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Researcher

John Brown University

faculty

39 h-index 161 pubs 4,766 cited

Is this your profile? Verify and claim your profile

Biography and Research Information

OverviewAI-generated summary

Dr. Stefanie Tellex's research explores the intersection of robotics, natural language processing, and machine learning. She develops multimodal machine learning applications to improve robot manipulation and learning, with a focus on enabling robots to understand and respond to natural language commands. Her work incorporates topic modeling and speech/dialogue systems to facilitate more intuitive human-robot interaction. Recent research includes the development of collaborative pushing and grasping policies, multi-resolution POMDP planning for object search, and methods for detecting multi-modal grasps in cluttered environments. A recent publication highlights constraint enforcement for LLM-driven robot agents.

Metrics

  • h-index: 39
  • Publications: 161
  • Citations: 4,766

Selected Publications

  • λ: A Benchmark for Data-Efficiency in Long-Horizon Indoor Mobile Manipulation Robotics (2025) DOI
  • Verifiably Following Complex Robot Instructions with Foundation Models (2025) DOI
  • Lang2LTL-2: Grounding Spatiotemporal Navigation Commands Using Large Language and Vision-Language Models (2024) DOI
  • Skill Transfer for Temporal Task Specification (2024) DOI
  • Plug in the Safety Chip: Enforcing Constraints for LLM-driven Robot Agents (2024) DOI
  • Improved Inference of Human Intent by Combining Plan Recognition and Language Feedback (2023) DOI
  • Spatial Language Understanding for Object Search in Partially Observed City-scale Environments (2021) DOI
  • Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter (2021) DOI
  • Bootstrapping Motor Skill Learning with Motion Planning (2021) DOI

Collaborators

Researchers in the database who share publications

Similar Researchers

Based on overlapping research topics