Julian Jarrett
Papers
2
Total Citations
9
H-Index
2
About
Julian Jarrett’s research sits at the intersection of robotics, artificial intelligence, and data-driven decision-making, with a focus on developing intelligent systems that can perceive, reason, and act in complex environments. His most cited work, “Regression and Mental Models for Decision Making on Robotic Biped Goalkeepers” (2015), introduces a novel approach to behavior design for humanoid robots competing in the RoboCup 3D Soccer Simulation League. By combining linear regression with Kalman filters for enhanced perception and a heuristics-based mental model for decision-making, Jarrett demonstrated how robots can anticipate and react to dynamic situations—a core challenge in autonomous robotics. This work has accumulated 7 citations, reflecting its relevance to the RoboCup and robotics communities. In a more recent study (2019), Jarrett explored how social media signals can be refined through reusable query criteria to support crowd-sourced sentiment analysis for decision-making. His contributions highlight a versatile skill set, bridging low-level robotic control with high-level data analytics. Jarrett’s research continues to push the boundaries of how machines learn from and interact with their environments, offering practical tools for both physical and virtual decision-making systems.
Research Focus
Key Achievements
Top Papers
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- 2