Papers

11

Total Citations

177

H-Index

6

About

Lindsay Sanneman is a robotics and human-robot interaction researcher whose work sits at the intersection of explainable AI, robot learning, and human-centered design. Best known for her widely cited survey "The State of Industrial Robotics: Emerging Technologies, Challenges, and Key Research Directions" (accumulating nearly 80 citations across versions), she has helped map the landscape of modern manufacturing robotics and its trajectory under frameworks like Industry 4.0. Her 2020 work on a master-apprentice model using virtual reality teleoperation (43 citations) demonstrated innovative methods for training AI-driven robots through human demonstration, advancing how expertise is transferred from people to machines. Sanneman has also made meaningful contributions to explainable AI in robotic contexts, exploring how reward explanations and transparent value alignment can foster appropriate human trust — a thread running through several of her publications. Her 2020 piece on trust considerations for explainable robots reflects her commitment to human factors principles as a foundation for safe, effective collaboration. With a body of work spanning educational robotics, space mission operations, and autonomous team taxonomies, Sanneman brings both breadth and depth to the challenge of making robots understandable, trustworthy, and genuinely useful partners for humans.

Research Focus

Key Achievements

6
H-Index
11
Papers
177
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
The State of Industrial Robotics: Emerging Technologies, Challenges, and Key Research Directions
45 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Artificial Intelligence in Medicine (Canada), Massachusetts Institute of Technology, University of Alberta

Top Papers

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    Transparent Value Alignment
    8 citations · 2023
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago