Papers

1

Total Citations

3

H-Index

1

About

Joscha Wasser is a researcher specializing in human-machine interaction, autonomous systems, and gaze-based control technologies, with a particular focus on defense and reconnaissance applications. His most-cited work, "Gaze Based Interaction for Object Classification in Reconnaissance Missions Using Highly Automated Platforms" (2021), has garnered 3 citations, demonstrating his early contributions to integrating eye-tracking with autonomous platforms for enhanced situational awareness. Wasser's research bridges cognitive ergonomics and artificial intelligence, exploring how operators can intuitively classify objects in high-stakes environments using gaze as a primary input modality. This work addresses critical challenges in human-autonomy teaming, where rapid, accurate decision-making is paramount. While his citation count is modest, his focus on practical, mission-oriented applications—such as reducing cognitive load for drone operators—positions him as an emerging voice in the field of human-robot interaction. Wasser's contributions are particularly relevant for students and researchers interested in the intersection of computer vision, human factors, and military technology, offering a glimpse into how next-generation interfaces may reshape reconnaissance and surveillance operations.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Gaze Based Interaction for Object Classification in Reconnaissance Missions Using Highly Automated Platforms
3 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Fraunhofer Institute for Communication, Information Processing and Ergonomics

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago