Jeremy Roghair
Papers
2
Total Citations
11
H-Index
2
About
Jeremy Roghair is a researcher specializing in autonomous systems, reinforcement learning, and energy-efficient robotics, with a particular focus on unmanned aerial vehicles (UAVs). His work addresses a critical challenge in drone-based applications: optimizing flight paths and goal selection while accounting for real-world disturbances such as wind, which significantly impact both power consumption and camera performance. By applying reinforcement learning frameworks, Roghair has developed intelligent planning approaches that enable UAVs to conduct visual exploration and smart data collection more efficiently and autonomously. His two most recognized publications, both from 2019, collectively demonstrate a coherent research vision centered on making aerial robotics more practical and deployable in dynamic environments. These works, which have garnered a combined 11 citations, contribute to the growing intersection of machine learning and autonomous navigation — a field with broad applications in agriculture, surveillance, search and rescue, and environmental monitoring. Roghair's research is particularly valuable for students and engineers seeking to understand how reinforcement learning can be leveraged to solve real-world energy constraints in robotic systems, pushing the boundaries of what autonomous UAVs can achieve in complex, unpredictable conditions.
Research Focus
Key Achievements
Top Papers
- 1
- 2