Theo Goulas

Institute for Language and Speech Processing

Papers

Total Citations

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About

Theo Goulas is a researcher specializing in human-robot interaction, assistive robotics, and multimodal communication systems. His work focuses on bridging the gap between humans and assistive robots through intuitive, data-driven interaction models. His most-cited paper, "Data Acquisition towards Defining a Multimodal Interaction Model for Human – Assistive Robot Communication" (2014, 17 citations), lays foundational groundwork for understanding how robots can interpret and respond to diverse human cues—such as speech, gesture, and gaze—to enable more natural and effective collaboration. This contribution is particularly significant in the context of assistive technologies, where seamless communication is critical for users with varying abilities. Goulas’s research integrates empirical data collection with interaction design, offering practical frameworks for developing robots that can adapt to human behavior in real-time. His work has implications for healthcare, rehabilitation, and everyday assistance, making him a notable voice in the evolution of socially aware robotics. By prioritizing user-centered design and multimodal integration, Goulas continues to advance the field toward more responsive and empathetic robotic systems.