Maxim Markitantov

Papers

Total Citations

H-Index

About

Maxim Markitantov is a researcher advancing the frontiers of **affective computing** and **human-robot interaction (HRI)**. His work sits at the intersection of artificial intelligence and psychology, focusing on how machines can perceive, interpret, and respond to human emotional and communicative signals. In his highly cited 2022 paper, "Analysis of infoware and software for human affective states recognition," Markitantov provides a comprehensive analytical review of the field, examining the methods, algorithms, and systems used to analyze human affective states during interactions with people or computers. This foundational work has garnered **7 citations**, establishing a key reference for researchers exploring emotion-aware AI. Markitantov also made a significant technical contribution with his 2022 paper on "End-to-end Visual Speech Recognition for Human-Robot Interaction," where he developed a novel word-level visual speech recognition method. By enabling robots to understand natural human speech through visual cues alone, his work directly addresses a critical bottleneck in creating seamless, intuitive human-machine communication. With a focus on bridging the gap between raw sensory data and meaningful social interaction, Markitantov’s research is paving the way for more empathetic and responsive robotic systems.