Vinicius G. Goecks
Papers
4
Total Citations
27
H-Index
3
About
Vinicius G. Goecks is a leading researcher at the intersection of artificial intelligence, robotics, and human-machine interaction. His work focuses on developing frameworks that integrate human expertise into autonomous systems, particularly through reinforcement learning and data-driven methods. Goecks’ most influential contribution is the "Cycle-of-Learning" framework (2018, 14 citations), which provides a taxonomy for categorizing human-robot interaction paradigms and enables end-to-end training of autonomous systems with human feedback. He has also advanced human-in-the-loop approaches (2020, 4 citations) that address the gap between reinforcement learning theory and real-world robotics applications, emphasizing safety and alignment with human expectations. His innovative work extends to virtual reality for astronaut situational awareness during space robotic operations (2017, 6 citations), showcasing the practical impact of his research. Goecks’ cyber-human approach (2018, 3 citations) further explores learning human intention from demonstrations to shape robotic behavior, ensuring autonomous systems operate within safety bounds. With a growing citation record, his research is essential for students and engineers seeking to design interactive, human-aware AI systems that bridge the gap between simulation and real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1Cycle-of-Learning for Autonomous Systems from Human Interaction14 citations · 2018
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