Evangelos Karakasis

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About

Evangelos Karakasis is a researcher whose work spans robotics, decision-making methodologies, and autonomous systems. His research sits at the intersection of intelligent systems and applied engineering, tackling practical challenges in robot evaluation, multi-criteria decision-making, and pose estimation. Among his notable contributions is a comparative analysis of robot evaluation and selection methodologies (2014), which has garnered 15 citations and serves as a valuable reference for engineers and researchers navigating the complex landscape of robotic system selection. His 2020 work on Multi-Criteria Decision Making using Fuzzy Cognitive Maps introduced an innovative methodology capable of capturing interdependencies and feedback loops among decision criteria — an advancement over traditional MCDM approaches that has already attracted 8 citations within a short timeframe. Earlier in his career, Karakasis addressed the fundamental robotics challenge of pose estimation, proposing a monocular visuo-inertial system for volant platforms (2009) that combined vision-based techniques with inertial sensing. Across his body of work, Karakasis demonstrates a consistent drive to develop more nuanced, real-world-applicable solutions — whether optimizing robot selection processes, refining autonomous navigation, or pushing the boundaries of computational decision frameworks.