Daniil M. Grabar
Papers
1
Total Citations
3
H-Index
1
About
Daniil M. Grabar is a researcher focused on the critical intersection of artificial intelligence, robotics, and cybersecurity. His work centers on understanding and mitigating vulnerabilities in machine learning models deployed within robotic systems, particularly against adversarial attacks. Grabar’s major contribution, detailed in his 2023 paper "Analysis of Predictive Models Stability to Adversarial Attacks in Robotics Complexes," provides a foundational framework for evaluating how robust predictive algorithms are when faced with deliberately deceptive inputs. This research is vital for ensuring the safety and reliability of autonomous systems in real-world applications, from industrial automation to defense. While his work is still early in its citation lifecycle, its relevance to the rapidly evolving field of adversarial machine learning positions Grabar as a rising voice in securing next-generation robotics. His analysis offers practical insights for engineers and researchers seeking to harden AI-driven platforms against manipulation, marking a significant step toward trustworthy autonomous operations.
Research Focus
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Top Papers
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