Mohamad Alissa

Papers

Total Citations

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About

Mohamad Alissa is a researcher at the intersection of natural language processing and human-robot interaction, with a primary focus on sentiment analysis for conversational agents. His most cited work investigates the applicability of common sentiment analysis models to open-domain human-robot interaction, specifically using the Alana system—an Alexa Prize socialbot—as a testbed. By evaluating these models on a dataset of real user interactions, Alissa identified which approaches are most suitable for understanding user sentiment in dynamic, unconstrained dialogues. This contribution is critical for building more empathetic and responsive conversational agents. While his citation count is still growing, his work addresses a foundational challenge in making AI systems more attuned to human emotion during open-ended conversations. Alissa’s research is particularly relevant for developers of social robots and voice assistants, as it provides practical guidance for selecting sentiment analysis tools in real-world deployment scenarios. His efforts help bridge the gap between static sentiment models and the fluid, unpredictable nature of human speech, marking him as an emerging voice in affective computing and dialogue systems.