Momina Rizwan

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About

Momina Rizwan is a robotics and artificial intelligence researcher whose work sits at the intersection of human-robot collaboration, automated planning, and domain-specific programming languages. Her research addresses one of the central challenges in modern robotics: equipping robots with the cognitive and reasoning capabilities necessary to work alongside humans in complex, real-world tasks. Her most influential contribution, "Human Robot Collaborative Assembly Planning: An Answer Set Programming Approach" (2020, 15 citations), demonstrates how logic-based AI techniques can be leveraged to enable robots to plan assembly sequences while simultaneously accounting for geometric feasibility and human collaboration dynamics. This work builds on earlier investigations into hybrid conditional planning for assembly tasks, reflecting a sustained commitment to making collaborative robotics more intelligent and adaptable. More recently, Rizwan has turned her attention to software engineering challenges in robotics, exploring how embedded domain-specific languages can help developers detect bugs earlier in the development cycle — a practical contribution with significant implications for reducing the cost and risk of robot deployment. Across her portfolio, Rizwan's research advances both the theoretical foundations and practical tools needed to develop safer, smarter, and more collaborative robotic systems.