Federico Scholcover
Papers
1
Total Citations
16
H-Index
1
About
Federico Scholcover is a researcher at the forefront of Human–AI–Robot Teaming (HART), with a particular focus on the methodological challenges of studying these complex interactions. His most-cited work, "Remote research methods for Human–AI–Robot Teaming" (2021, 16 citations), emerged as a critical guide during the COVID-19 pandemic, systematically identifying key obstacles—from participant recruitment to maintaining experimental fidelity—and offering practical solutions for conducting rigorous remote studies. This contribution has proven invaluable for researchers navigating the shift to distributed collaboration, ensuring that HART research could continue despite physical distancing constraints. Beyond this methodological pivot, Scholcover’s broader work explores the dynamics of trust, communication, and coordination between humans and autonomous systems, addressing how teams can effectively integrate AI and robotic agents. His research is particularly notable for bridging the gap between theoretical frameworks and real-world application, making him a key voice in shaping how we study and design human-centered AI teams. With a growing citation footprint, Scholcover continues to influence both the practice and ethics of remote HART research.
Research Focus
Key Achievements
Top Papers
- 1Remote research methods for Human–AI–Robot Teaming16 citations · 2021